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HomeMy WebLinkAbout20140812Folsom Exhibit 1 DSM Report.pdf   2013 Annual Report  Demand‐Side Management  Idaho  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 1 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 2   Avista Utilities  I. Table of Contents  II. EXECUTIVE SUMMARY ................................................................................................................................ 3  III. COST‐EFFECTIVENESS.................................................................................................................................. 5  Electric Cost‐Effectiveness ........................................................................................................... 6  Natural Gas Cost‐Effectiveness Tests ........................................................................................... 8  Combined Fuel Cost‐Effectiveness Tests ................................................................................... 10  IV. NET‐TO‐GROSS .......................................................................................................................................... 12  V. EVALUATION, MEASUREMENT AND VERIFICATION (EM&V) .................................................................... 15  VI. PROGRAMS ............................................................................................................................................... 16  Residential .................................................................................................................................. 16  Low Income and Outreach ......................................................................................................... 21  Nonresidential ............................................................................................................................ 25  VII. REGIONAL MARKET TRANSFORMATION .................................................................................................. 28  VIII. ENERGY EFFICIENCY EXPENDITURES ......................................................................................................... 29  IX. TARIFF RIDER BALANCES ........................................................................................................................... 31  X. ACTUAL TO BUSINESS PLAN COMPARISON .............................................................................................. 32  APPENDICES ...................................................................................................................................................... 33  Appendix 1  Avista 2013 Idaho Electric Impact Evaluation Report ............................................ 34  Appendix 2  Avista 2013 Idaho Natural Gas Savings Memorandum ........................................ 165  Appendix 3  Avista 2012‐2013 Process Evaluation Report ...................................................... 169       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 2 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 3   Avista Utilities  II. EXECUTIVE SUMMARY  The 2013 Demand‐Side Management (DSM) Annual Report summarizes the Company’s annual energy  efficiency achievements for its Idaho electric and natural gas customers. These programs are intended  to deliver a cost‐effective, “least‐cost” resource with the funding provided through Avista’s Schedules 91  and 191, also known as the “Tariff Rider” which is a non‐bypassable system benefit charge applied to all  electric and natural gas retail sales.    In 2013, the electric DSM portfolio achieved 25,899 MWh and the natural gas portfolio delivered 51,774  therms in first year annual savings.  Based on the 2013 target established by the 2011 Electric Integrated  Resource Plan (IRP), the Company achieved 136 percent of the Idaho target while acquiring 14 percent  of the 2013 target from the 2012 Natural Gas IRP.  The Natural Gas IRP target was established prior to  the significant decline in natural gas commodity prices that resulted in the suspension of Idaho Schedule  191 and the subsequent suspension of the natural gas energy efficiency programs due to cost‐effective  challenges resulting from lower avoided costs.  The above mentioned acquisition has been delivered through local energy efficiency programs managed  by the utility or third‐party contractors.  Avista also funds regional market transformation effort through  the Northwest Energy Efficiency Alliance (NEEA), however, reported electric energy savings, cost‐ effectiveness and other related information is specific to local programs unless otherwise noted.    The savings indicated above are gross savings based on all program participants.  Net‐to‐gross (NTG)  adjustments to savings claims and cost‐effectiveness are included within the NTG section of this report.   Furthermore, net‐to‐gross analysis is being studied on 2013 participation, with NTG adjustments from  2013 participation.        Avista judges the effectiveness of the energy efficiency portfolio based upon a number of metrics.  Two  of the most commonly applied metrics are the TRC test, a benefit‐to‐cost test encompassing the entire  utility ratepayer population, and the PAC test, a benefit‐to‐cost test from the perspective of achieving a  minimization of the utility cost of delivering energy efficiency services.  Benefit‐to‐cost ratios in excess of  1.00 indicate that the benefits exceed the costs.  In 2013, the TRC benefit‐to‐cost ratios were 1.23 for  electric and 0.86 for natural gas.  The PAC test benefit‐to‐cost ratios were 1.86 for electric and 1.27 for  natural gas.  The low ratios for natural gas programs are due to the previously mentioned decline in  natural gas avoided costs and the natural gas program suspension, which resulted in very few natural  gas measures being completed in 2013 that were under contractual obligations or previous  commitments.  The measurement of portfolio energy savings has been independently verified through external third‐ party evaluators prior to being claimed as portfolio acquisition or being incorporated into the cost‐ effectiveness calculations.  The Cadmus Group was retained as the Company’s external evaluator to  independently measure and verify 2013 electric and natural gas portfolio results.    Though the nature of this report is to look at the performance of the previous year, successes and  lessons from this process are applied during the forward‐looking business planning process to inform  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 3 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 4   Avista Utilities  and improve program design, including program modification and termination where necessary.  Avista  remains committed to continuing to deliver responsible and cost‐effective energy efficiency programs to  our customers.     Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 4 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 5   Avista Utilities  III. COST­EFFECTIVENESS  The 2013 Demand‐Side Management (DSM) Annual Report summarizes the Company’s annual energy  efficiency achievements of its DSM programs.    Cost‐effectiveness was reviewed using four of the five California Standard Practice Tests including the  Total Resource Cost (TRC), Program Administrator Cost (PAC), Participant, and Rate Impact Measure  (RIM) tests.  For this annual report, cost‐effectiveness of DSM programs is based on evaluated gross  savings using the most recent applicable impact evaluation and methods consistent with those laid out  in the California Standard Practice Manual for Economic Analysis of Demand‐Side Programs and Projects  as modified by the Council.  Shown below in Tables 1 through 12 are results for these four California  Standard Practice Tests ‐ Total Resource Cost, Program Administrator Cost, Participant, and Rate Impact  Measure for electric and natural gas.  For estimating cost‐effectiveness, the only non‐energy benefits that are included are those that can be  documented and reliably quantified and, therefore, these estimates are conservative.  There are a  number of legitimate non‐energy benefits that the Company was unable to quantify with sufficient rigor  in order to include within the cost‐effectiveness analysis.    Electric and natural gas cost‐effectiveness results are based on verification and impact evaluations  conducted on 2013 programs.  These savings estimates represent gross energy acquisition.  Net‐to‐gross  evaluation and impacts on cost‐effectiveness will be addressed in the net‐to‐gross section of this report.    Avoided costs used for the cost‐effectiveness valuation of the 2013 programs are the avoided costs from  the most recently filed electric and natural gas IRPs.  In 2013, Avista’s biennial IRP efforts, described a  significant decrease in natural gas avoided costs.  This also impacts electric avoided costs since thirty‐ five percent of Avista’s generation is natural gas fueled.  The decline in natural gas avoided costs and the  corresponding impact on natural gas energy efficiency programs were communicated with the  regulatory commissions of the three states in which Avista operates.  The Idaho Public Utilities  Commission authorized the suspension of the natural gas programs effective October 1, 2012 due to the  cost‐ineffectiveness of the natural gas energy efficiency programs under the TRC benefit‐cost test.    While Schedule 190 was suspended in Idaho, a small number of customer projects were still in process  and, by contract, were allowed to be completed.     In summary, electric and natural gas TRC is 1.23 and 0.86, respectively.  Electric and natural gas PAC test  benefit‐cost ratios are 1.86 and 1.27, respectively.  Tables 1 through 12 illustrate Idaho electric, natural  gas, and combined fuel cost‐effectiveness, respectively.      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 5 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 6   Avista Utilities  Electric Cost‐Effectiveness    Table 1:  Electric Total Resource Cost  Regular Income portfolio Low Income portfolio Overall portfolio Electric avoided cost $11,267,342 $277,690 $11,545,032 Natural Gas avoided cost (82,904) (28,879) (111,782) Non-Energy Benefits 203,777 289,554 493,331 TRC benefits $11,388,215 $538,366 $11,926,581 Non-incentive utility cost $1,807,580 $106,238 $1,913,818 Customer cost 7,116,315 703,429 7,819,745 TRC costs $8,923,895 $809,668 $9,733,563 TRC ratio 1.28 0.66 1.23 Residual TRC benefits $2,464,320 ($271,302) $2,193,018   Table 2:  Electric Program Administrator Cost  Regular Income portfolio Low Income portfolio Overall portfolio Electric avoided cost $11,267,342 $277,690 $11,545,032 Natural Gas avoided cost (82,904)(28,879)(111,782) PAC benefits $11,184,438 $248,812 $11,433,250 Non-incentive utility cost $1,807,580 $106,238 $1,913,818 Incentive cost 3,527,631 703,429 4,231,061 PAC costs $5,335,211 $809,668 $6,144,879 PAC ratio 2.10 0.31 1.86 Net PAC benefits $5,849,227 ($560,856) $5,288,371       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 6 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 7   Avista Utilities  Table 3:  Electric Participant  Regular Income portfolio Low Income portfolio Overall portfolio Electric Bill Reduction $16,331,868 $515,439 $16,847,307 Gas Bill Reduction (137,862) (38,885) (176,746) Non-Energy benefits 203,777 289,554 493,331 Participant benefits $16,397,784 $766,109 $17,163,892 Customer cost $7,116,315 $703,429 $7,819,745 Incentive received (3,527,631)(703,429)(4,231,061) Participant costs $3,588,684 $0 $3,588,684 Participant ratio 4.57 NA 4.78 Net Participant benefits $12,809,100 $766,109 $13,575,208   Table 4:  Electric Rate Impact Measure  Regular Income portfolio Low Income portfolio Overall portfolio Electric avoided cost savings $11,267,342 $277,690 $11,545,032 Non-Participant benefits $11,267,342 $277,690 $11,545,032 Electric Revenue loss $16,194,007 $476,554 $16,670,561 Non-incentive utility cost 1,807,580 106,238 1,913,818 Customer incentives 3,527,631 703,429 4,231,061 Non-Participant costs $21,529,218 $1,286,222 $22,815,440 RIM ratio 0.52 0.22 0.51 Net RIM benefits ($10,261,876) ($1,008,532) ($11,270,408)       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 7 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 8   Avista Utilities  Natural Gas Cost‐Effectiveness Tests    Table 5:  Natural Gas Total Resource Cost  Regular Income portfolio Low Income portfolio Overall portfolio Natural gas avoided cost $105,675 $0 $105,675 Electric avoided cost 0 0 0 Non-Energy Benefits 0 0 0 TRC benefits $105,675 $0 $105,675 Non-incentive utility cost $44,478 $0 $44,478 Customer cost 77,978 0 77,978 TRC costs $122,456 $0 $122,456 TRC ratio 0.86 NA 0.86 Residual TRC benefits ($16,781) $0 ($16,781)   Table 6:  Natural Gas Program Administrator Cost  Regular Income portfolio Low Income portfolio Overall portfolio Natural gas avoided cost $105,675 $0 $105,675 Electric avoided cost 0 0 0 PAC benefits $105,675 $0 $105,675 Non-incentive utility cost $44,478 $0 $44,478 Incentive cost 38,974 0 38,974 PAC costs $83,453 $0 $83,453 PAC ratio 1.27 NA 1.27 Net PAC benefits $22,223 $0 $22,223       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 8 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 9   Avista Utilities  Table 7:  Natural Gas Participant  Regular Income portfolio Low Income portfolio Overall portfolio Natural gas bill reduction $184,106 $0 $184,106 Electric bill reduction 0 0 0 Non-energy benefits 0 0 0 Participant benefits $184,106 $0 $184,106 Customer cost $77,978 $0 $77,978 Incentive received (38,974)0 (38,974) Participant costs $39,004 $0 $39,004 Participant ratio 4.72 NA 4.72 Net Participant benefits $145,102 $0 $145,102   Table 8:  Natural Gas Rate Impact Measure  Regular Income portfolio Low Income portfolio Overall portfolio Natural gas avoided cost savings $105,675 $0 $105,675 Non-Participant benefits $105,675 $0 $105,675 Natural gas revenue loss $184,106 $0 $184,106 Non-incentive utility cost 44,478 0 44,478 Customer incentives 38,974 0 38,974 Non-Participant costs $267,558 $0 $267,558 RIM ratio 0.39 NA 0.39 Net RIM benefits ($161,883)$0 ($161,883)       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 9 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 10   Avista Utilities  Combined Fuel Cost‐Effectiveness Tests    Table 9:  Electric and Natural Gas Total Resource Cost  Regular Income portfolio Low Income portfolio Overall portfolio Electric avoided cost $11,267,342 $277,690 $11,545,032 Natural Gas avoided cost 22,772 (28,879) (6,107) Non-Energy Benefits 203,777 289,554 493,331 TRC benefits $11,493,890 $538,366 $12,032,256 Non-incentive utility cost $1,852,058 $106,238 $1,958,296 Customer cost 7,194,293 703,429 7,897,723 TRC costs $9,046,351 $809,668 $9,856,019 TRC ratio 1.27 0.66 1.22 Residual TRC benefits $2,447,539 ($271,302)$2,176,237   Table 10:  Electric and Natural Gas Program Administrator Cost  Regular Income portfolio Low Income portfolio Overall portfolio Electric avoided cost $11,267,342 $277,690 $11,545,032 Natural Gas avoided cost 22,772 (28,879)(6,107) PAC benefits $11,290,113 $248,812 $11,538,925 Non-incentive utility cost $1,852,058 $106,238 $1,958,296 Incentive cost 3,566,606 703,429 4,270,035 PAC costs $5,418,664 $809,668 $6,228,331 PAC ratio 2.08 0.31 1.85 Net PAC benefits $5,871,450 ($560,856) $5,310,594       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 10 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 11   Avista Utilities  Table 11:  Electric and Natural Gas Participant  Regular Income portfolio Low Income portfolio Overall portfolio Electric Bill Reduction $16,331,868 $515,439 $16,847,307 Gas Bill Reduction 46,244 (38,885) 7,360 Non-Energy benefits 203,777 289,554 493,331 Participant benefits $16,581,890 $766,109 $17,348,998 Customer cost $7,194,293 $703,429 $7,897,723 Incentive received (3,566,606)(703,429)(4,270,035) Participant costs $3,627,688 $0 $3,627,688 Participant ratio 4.57 NA 4.78 Net Participant benefits $12,954,202 $766,109 $13,720,310   Table 12:  Electric and Natural Gas Rate Impact Measure  Regular Income portfolio Low Income portfolio Overall portfolio Avoided Cost Savings $11,373,017 $277,690 $11,650,707 Non-Participant benefits $11,373,017 $277,690 $11,650,707 Revenue Loss $16,378,113 $476,554 $16,854,667 Non-incentive utility cost 1,852,058 106,238 1,958,296 Customer incentives 3,566,606 703,429 4,270,035 Non-Participant costs $21,796,776 $1,286,222 $23,082,998 RIM ratio 0.52 0.22 0.50 Net RIM benefits ($10,423,759) ($1,008,532) ($11,432,291)      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 11 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 12   Avista Utilities  IV. NET­TO­GROSS  During 2013, as part of Avista‘s portfolio process and impact review conducted by Cadmus, various net‐ to‐gross analyses were performed on the residential and nonresidential energy efficiency programs.   These findings are used by the Company to determine what, if any, portion of the gross energy savings  have been influenced by and are attributable to the utility’s energy efficiency programs rather than to  other influences such as consumer self‐motivation or other motivators such as tax credits.  While net‐to‐gross is comprised of freeridership, participant spillover and nonparticipant spillover, due  to the time lag necessary to measure the effects of spillover, the net‐to‐gross study as performed by  Cadmus most likely underestimates the spillover.    The following table summarizes the net‐to‐gross (NTG) findings on 2013 and 2011 programs for the  residential program categories.  When reviewing 2013 programs for NTG, some program categories that  had been reviewed in 2011 were revisited in 2013.  In addition, some new program categories were  added to the 2013 program review.  NTG for Low Income is assumed to be 100 percent, as the utility  pays the entire cost.  Table 13:  Residential Net‐to‐Gross Results  Program Category        NTG on 2013  Programs    NTG on 2011  Programs   Appliances 23.0% 41.9%  Heating, Cooling and Ventilation   29.0% 45.5%  Shell 46.0% 68.3%  ENERGY STAR Homes     74.0% N/A  Appliance Recycling‐Refrigerator 32.0% 41.0%  Appliance Recycling‐Freezer   32.0% 42.0%  Water Heater Efficiency 46.0% N/A  Space and Water Conversions   39.0% N/A    The difference in NTG estimates between 2013 and 2011 are statistically significant for all the residential  programs.  The NTG has decreased in 5 of the programs and 3 programs were new to separate  evaluation.    The following table summarizes the net‐to‐gross (NTG) findings on 2013 and 2011 programs for the  nonresidential program categories.        Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 12 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 13   Avista Utilities  Table 14:  Nonresidential Net‐to‐Gross Results  Program Category        NTG on 2013  Programs    NTG on 2011  Programs   EnergySmart Grocer 86.5% 96.0%  Prescriptive     91.7% 67.4%  Site Specific      70.4% 83.3%    The difference in NTG estimates between 2013 and 2011 are especially statistically significant for the  nonresidential prescriptive program category while the differences in the other program categories are  not as statistically significant.  Nonresidential programs showed lower freeridership than residential programs.  The high freeridership  scores on residential programs could indicate that the market has truly been transformed.  Residential electric net Total Resource Cost (TRC) and Program Administrator Cost (PAC) benefits and  cost by program are summarized in Table 15.  Residential electric gross TRC benefit‐cost ratio of 0.50  becomes 0.22 when adjusted for NTG.   The residential electric gross PAC benefit‐cost ratio of 0.59  decreased to 0.21 when adjusted for NTG.  The following tables provide more detail by program on  residential electric and natural gas net benefits, costs and resulting ratios.  Table 15:  Residential Electric Program Net Benefits and Costs  Measure        Net TRC  Benefits    Net TRC  Costs  TRC   Net PAC  Benefits    Net PAC  Costs  PAC   E Electric Water Heater  $1,248 $4,311 0.29 $1,248  $4,877 0.26   E Attic Insulation With Electric Heat    $7,599 $30,627 0.25 $7,599  $26,949 0.28   E Floor Insulation With Electric Heat  $5,341 $20,334 0.26 $5,341  $16,978 0.31   E Wall Insulation With Electric Heat    $14,680 $50,159 0.29 $14,680  $45,160 0.33   E Energy Star Home ‐ Stick Built  $8,008 $27,733 0.29 $8,008  $17,205 0.47   E Electric To Natural Gas Water Heater  $6,068 $24,870 0.24 $6,068  $25,254 0.24   E Electric To Natural Gas Furnace  $56,722 $262,994 0.22 $56,722  $266,812 0.21   X E Freezer      $54 $353 0.15 $54  $440 0.12   X E Refrigerator  $1,201 $7,375 0.16 $1,201  $9,366 0.13   X E Clothes Washer With Elect Water Heat  $7,002 $13,110 0.53 $1,880  $14,350 0.13   E Air Source Heat Pump  $5,566 $33,194 0.17 $5,566  $41,909 0.13   E Electric To Air Source Heat Pump    $34,737 $174,614 0.20 $34,737  $187,706 0.19   E Variable Speed Motor  $17,883 $97,959 0.18 $17,883  $103,001 0.17   X E Ductless Heat Pump      $212 $1,330 0.16 $212  $2,324 0.09   Total Idaho Electric      $166,321 $748,962 0.22 $161,199  $762,331 0.21    Nonresidential electric net Total Resource Cost (TRC) benefits and Program Administrator Cost (PAC)  benefits and cost by program are summarized in the following table.  The nonresidential electric gross  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 13 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 14   Avista Utilities  TRC of 1.22 becomes 1.19 when adjusted for NTG.  The nonresidential electric gross PAC of 2.22  decreased to 1.78 when adjusted for NTG.   Table 16 provides more details by program on  nonresidential electric net benefits, costs and resulting ratios.  Table 16:  Nonresidential Electric Program Net Benefits and Costs  Program        Net TRC  Benefits    Net TRC  Costs  TRC   Net PAC  Benefits    Net PAC  Costs  PAC  Site Specific Other $188,088 $266,291 0.71 $188,088  $115,750 1.62  Site Specific Shell     $15,940 $15,805 1.01 $15,940  $12,288 1.30  Prescriptive Food Service $20,696 $87,913 0.24 $20,696  $7,872 2.63  Prescriptive Green Motors   $8,500 $6,548 1.30 $8,500  $4,284 1.98  Prescriptive Variable Frequency Drives $174,161 $74,215 2.35 $174,161  $43,041 4.05  Prescriptive Standby Generator Block   $1,245 $2,683 0.46 $1,245  $516 2.41  EnergySmart Grocer Industrial Process $688,119 $464,500 1.48 $688,119  $242,396 2.84  EnergySmart Grocer Case Lighting   $53,165 $78,412 0.68 $53,165  $65,648 0.81  Prescriptive Windows and Insulation $20,032 $19,928 1.01 $20,032  $7,454 2.69  Prescriptive Exterior Lighting   $1,170,396 $919,591 1.27 $1,152,958  $761,941 1.51  Prescriptive Interior Lighting $1,694,456 $1,563,490 1.08 $1,600,360  $1,297,733 1.23  Site Specific Multifamily     $272,521 $64,444 4.23 $272,521  $69,443 3.92  Site Specific Energy Star Clothes Washer $205 $870 0.24 $205  $100 2.05  Site Specific Energy Star Refrigerator   $185 $149 1.24 $185  $173 1.07  Site Specific Renewable $388 $23,684 0.02 $388  $205 1.89  Site Specific Appliances     $1,621 $197 8.22 $1,621  $197 8.22  Site Specific Compressed Air $520,568 $349,965 1.49 $520,568  $266,901 1.95  Site Specific Industrial Process   $12,935 $15,653 0.83 $12,935  $10,670 1.21  Site Specific Motor Controls $8,802 $6,421 1.37 $8,802  $4,756 1.85  Site Specific Motors     $284,307 $736,011 0.39 $284,307  $218,118 1.30  Site Specific HVAC Combined $121,580 $258,074 0.47 $121,580  $55,239 2.20  Site Specific HVAC Cooling   $5,617 $3,424 1.64 $5,617  $2,611 2.15  Site Specific HVAC Heating $47,272 $97,998 0.48 $47,272  $20,979 2.25  Site Specific Exterior Lighting   $362,484 $205,785 1.76 $356,004  $145,718 2.44  Site Specific Interior Lighting $1,506,806 $791,619 1.90 $1,471,134  $596,782 2.47                      Total Idaho Electric       $7,180,089 $6,053,668 1.19 $7,026,403  $3,950,815 1.78      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 14 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 15   Avista Utilities  V. EVALUATION, MEASUREMENT AND VERIFICATION (EM&V)  Cadmus was retained to provide impact and process evaluations for the 2013 electric and natural gas  programs.  The Company has committed to a three‐year cycle to evaluate all programs.  Avista continues  to take a portfolio approach for evaluation while leveraging the findings of past evaluations to inform  future evaluation efforts that may require a “deeper dive.”  Evaluations for 2013 are included as part of this DSM Annual Report.  The following evaluation reports  are included within the Appendices as noted:  • Avista 2013 Idaho Electric Impact Evaluation Report prepared by Cadmus is included as  Appendix 1.  This report summarizes the findings and recommendations resulting from the  impact evaluation on 2013 electric programs.    • Avista 2013 Idaho Natural Gas Savings Memorandum prepared by Cadmus is included as  Appendix 2.  This report summarizes the findings and recommendations resulting from Cadmus’  impact evaluation on 2013 natural gas programs. • Avista 2012‐2013 Process Evaluation Report prepared by Cadmus is included as Appendix 3.   This report summarizes findings and recommendations resulting from the process evaluation on  2012 and 2013 DSM programs.     Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 15 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 16   Avista Utilities  VI. PROGRAMS  Residential  Home Improvement/Appliances  The Company’s Residential portfolio includes two primary methods of program delivery to encourage  customers to make energy efficiency choices for their home.  The traditional rebate application  approach is the main method of program implementation and the largest component of the residential  portfolio.  This process uses financial incentives to encourage customers to adopt a qualifying electric  energy efficiency measure. Program eligibility typically covers single family homes up to a 4‐plex.   Customers must complete the installation, apply for a rebate, and provide the proper proof of purchase  and/or other documentation to the Company typically within 90 days from project completion.   Customers can submit the application in hard copy or on‐line at  http://www.avistautilities.com/savings/rebates/Pages/idahorebates.aspx    Rebate programs offered to existing residential homes in 2013 were for electric efficiency improvements  only and included the following:    • High‐efficiency equipment   o Water heater  o Air source heat pump  o Variable speed motor  • Electric space to natural gas conversions  • Electric hot water to natural gas conversions  • Electric straight resistance to air source heat pump   • Insulation improvements for electrically heated homes:  o Attic  o Floor   o Wall     For new construction homes rebates were available for the same high efficiency equipment mentioned  above as well as for homes with electric space heat built to the Energy Star specification.  Notable changes to the Idaho residential portfolio in 2013 included the following:  • Discontinued rebates for natural gas heated homes  • Discontinued rebates for ENERGY STAR appliances  • Discontinued rebates for  ductless heat pump   • Reduction in rebate offered for the following measures:  o  Air source heat pumps  o ENERGY STAR Homes   o High efficiency electric water heaters  • Increase in rebate offered for the following measures:  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 16 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 17   Avista Utilities  o Electric to natural gas space heat conversion  o Electric to natural gas water heat conversion  • Change program eligibility for existing levels of attic insulation in electrically heated homes:  o Reduced to a R‐12 from an R‐19    Energy efficiency outreach continued in 2013 through a variety of channels.  Annual bill inserts  promoting rebate programs along with website messaging and a dedicated energy efficiency rebate  page offers a consistent presence of the rebate programs available.  The Company continued energy  efficiency outreach at select community events, energy fairs and vendor meetings and teamed up with  local media outlets to promote energy efficiency opportunities featured in the examples below.  In the early spring, the Company partnered with the local weekly paper The Inlander to encourage  people to sign up for the Home Energy Advisor tool. This on‐line audit tool provides customers with a  way to evaluate their home to identify potential energy saving opportunities.  People who sign up for  the Home Energy Advisor tool are entered for a chance to win a gift card for a local home improvement  store, an Avista Housewarming Gift Certificate and a personal photo shoot that will be featured in an  Inlander advertisement announcing the winners.  This engaged customers, built awareness around this  on‐line tool and offered suggestions to improve the energy efficiency in their home.  In the second quarter of the year, the Company teamed up with local CBS affiliate, KREM 2 as well as  Toyota in support of energy efficiency. Throughout the campaign homeowners were informed what  they can do to help manage their energy use. By watching KREM 2 news at 5pm or 6pm viewers could  enter a chance to win a new Prius from Toyota.  Impact and process evaluations will continue on 2013 residential programs, providing an on‐going  opportunity to improve program design and delivery as well as optimizing the savings achieved for the  dollars spent.  As recommendations from these evaluations become available, the DSM team continues  to evaluate, respond and implement changes, providing continuous improvement of program offerings.  Under the traditional rebate program, Idaho residential customers completed nearly 800 electric  projects and had a spillover of 14 natural gas projects from the programs conclusion in November 2012  (plus clothes washer projects).  Over $130,000 in rebates were provided directly to Idaho residential  customers to offset the cost of implementing these energy efficiency measures.  All programs within the  residential portfolio contributed over 788 MWh and nearly 2,000 therms in annual first‐year energy  savings.  Tables 17 and 18 summarize the results from the electric and natural gas home improvement  and appliance programs.  The following tables summarize residential electric and natural gas results through traditional DSM  offerings operated in‐house by Avista DSM staff.  These include number of projects and savings  acquisition, as well as interactive effects associated with electric and natural gas measures.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 17 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 18   Avista Utilities  Table 17:  Electric Residential Home Improvement and Appliances1  Measure     Project  Count Incentives kWh Therms  kWh  Avoided  Costs  Therms  Avoided  Costs  Non‐ energy  Benefits  Customer  Incremental  Costs  Non‐ incentive  Utility Costs  E Electric Water Heater 38  $1,440 5,487  0  $2,714  $0  $0 $1,900 $3,437  E Attic Insulation With Electric Heat   20  $6,027 24,891  0  $16,520  $0  $0 $21,097 $20,923  E Floor Insulation With Electric Heat 7  $2,272 17,496  0  $11,612  $0  $0 $12,233 $14,707  E Wall Insulation With Electric Heat   10  $4,742 48,084  0  $31,912  $0  $0 $21,176 $40,418  E ENERGY STAR Home ‐ Stick Built 5  $3,500 12,550  0  $10,821  $0  $0 $18,956 $13,705  E Electric To Natural Gas Water Heater 6  $1,200 26,202  (648) $18,992  ($3,434) $0 $2,093 $24,054  E Electric To Natural Gas Furnace 28  $21,000 267,764  (9,180) $194,084  ($48,643) $0 $44,058 $245,812  X E Freezer   7  $140 326  0  $237  $0  $0 $231 $300  X E Refrigerator 110  $2,750 7,207  0  $5,224  $0  $0 $3,300 $6,616  X E Clothes Washer With Elect Water Heat2 160  $4,000 21,479  0  $8,172  $0  $22,272 $12,000 $10,350  E Air Source Heat Pump 101  $17,600 33,989  0  $19,194  $0  $0 $30,635 $24,309  E Electric To Air Source Heat Pump   48  $36,000 212,112  0  $119,781  $0  $0 $78,995 $151,706  E Variable Speed Motor 249  $24,900 109,199  0  $61,666  $0  $0 $68,475 $78,101  X E Ductless Heat Pump   7  $1,400 1,292  0  $730  $0  $0 $1,400 $924  Total Idaho Electric    796  $126,971 788,078  (9,828) $501,657  ($52,077) $22,272 $316,549 $635,360    Table 18:  Natural Gas Residential Home Improvement and Appliances3  Measure     Project  Count Incentives kWh Therms  kWh  Avoided  Costs  Therms  Avoided  Costs  Non‐ energy  Benefits  Customer  Incremental  Costs  Non‐ incentive  Utility Costs  G Natural Gas Furnace 7  $2,800 0  722  $0  $3,826 $0 $27,841 $3,965  G Natural Gas Boiler   1  $400 0  141  $0  $747 $0 $800 $774  G Attic Insulation With Natl Gas Heat 4  $1,128 0  279  $0  $1,391 $0 $3,020 $1,441  G Wall Insulation With Natl Gas Heat   2  $586 0  370  $0  $1,844 $0 $1,800 $1,912  X G Clothes Washer W/ Nat Gas Water Heat4 99  $0 0  420  $0  $0 $0 $0 $0  Total Idaho Natural Gas          113  $4,914 0       1,932  $0  $7,808 $0 $33,461 $8,092                                                                    1 All kWh and therm values reported in this table are gross, excluding the effect of applicable NTG ratios.  2 As referenced in the Cadmus “2013 Idaho Natural Gas Savings” memorandum dated June 14, 2014 on page 3,”… ninety‐nine  clothes washer measures were actually processed as electric measures, but upon evaluation, found to have natural gas water  heating, so there were additional gas savings from the electric dryer savings”.  3 All kWh and therm values reported in this table are gross, excluding the effect of applicable NTG ratios.  4 As referenced in the Cadmus “2013 Idaho Natural Gas Savings” memorandum dated June 14, 2014 on page 3,”… ninety‐nine  clothes washer measures were actually processed as electric measures, but upon evaluation, found to have natural gas water  heating, so there were additional gas savings from the electric dryer savings”.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 18 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 19   Avista Utilities  Simple Steps Smart Savings  Avista continues to participate in the regional manufacturer buy‐down of CFL twists, specialty bulbs, LED  bulbs, and showerheads through Northwest Energy Efficiency Alliance (NEEA) and its contactor.  Over  178,000 bulbs and over 200 showerheads were purchased from participating retailers.  The bulbs  resulted in 4,734 MWh and the showerheads resulted in 17 MWh in annual first‐year savings during  2013 (see Tables 19 and 20).  The Company contributed over $195,000 in incentives toward this buy‐ down effort to this program.   Refrigerator/Freezer Recycling  Avista has partnered with JACO, one of the nation’s leading appliance recyclers, to provide third‐party  administration of the refrigerator/freezer appliance recycling program.  During 2012, over 300  appliances were recycled through this program.  Customers received $30 per appliance for participating  which equated to over $10,000 in incentives.  This appliance recycling program resulted in over 368  MWh in annual first‐year savings in 2013 (see Table 19).  The Company contributed nearly $40,000 to  cover the administrative costs for this program.    Customer Outreach (formerly Geographic Saturation)  Residential programs have benefited from continued customer outreach that promotes the availability  of Avista’s energy efficiency programs and encourages customers to take action through participation in  currently offered programs.  Outreach efforts have included targeted media, online, print and previously  widespread participation at local community events.  In 2013, Avista’s DSM‐led outreach participated in  community workshops, energy fairs and vendor meetings.  Avista continues to maintain DSM tools for  other departments to leverage for use at public gatherings where a non‐DSM employee leads the effort  and wants to include energy efficiency messaging and materials.  This approach, also known as  “Outreach‐in‐a‐Box” has been successful in increasing the availability of DSM messaging and support.  Mobile outreach also known as the Avista Energy Resource Van (ERV) travels to events and food banks  where information is provided about Avista online tools, payment options, assistance resources, and  obtain low‐cost/no‐cost energy management information and light weatherization and energy savings  items.  During 2013, nearly 1,800 bulbs were distributed at events throughout Avista’s Idaho service  territory which resulted in 27 MWh of annual first‐year savings (see Table 19).  The incentive cost of  providing these bulbs to customers was nearly $4,000 and is offered at minimal utility cost. Opower Home Energy Reports  Avista launched a Home Energy Reports program in June 2013, targeting 48,300 Washington and 24,500  Idaho high use electric customers. In an effort to reduce energy usage through behavioral changes,  Home Energy Reports show personalized usage insights and energy saving tips. Customers also see a  ranking of similar homes, comparison to themselves and a personal savings goal on the Reports. In  addition to closely matching usage curves, the similar home comparisons are also based on the following  four criteria, square footage, home type, heat type and proximity.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 19 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 20   Avista Utilities  Opt‐Outs:  Customers always have the choice of not receiving the reports and can opt‐out at anytime.   As of the end of 2013, 0.88% opted‐out in Idaho.   Attrition:  Before the end of 2013, 2,323 customers receiving Opower reports in Idaho closed their  Avista account and therefore are no longer counted in the Program.   Savings Results:  The method for measuring energy savings in this program is to use a Randomized  Control Trial method.  Avista’s control groups therefore include 13,000 customers in each state.  Using  this method for calculating savings, Avista’s 3rd party evaluator determined energy savings results in  Idaho to be 2,871 MWh and nearly 31,000 therms (see Tables 19 and 20).    Table 19:  Other Electric5  Measure        Unit  Count Incentives kWh Therms  Non‐incentive  Utility Costs  Customer Outreach CFLs (Low Income) 1,528 $3,429 22,920 0  $3,429  Customer Outreach CFLs (Residential) 248 $557 3,720 0  $557  Refrigerator/Freezer Recycling (Res) 348 $10,440 368,174 0  $40,362  Simple Steps CFL (Res)     169,290 $178,710 4,459,787 0  $76,716  Simple Steps LED (Res) 9,455 $15,725 273,812 0  $6,750  Simple Steps Showerheads (Res)   212 $797 16,706 0  $342  Opower Home Energy Reports (Res) 24,501 $0 2,870,905 0  $287,300  Total Electric Idaho (Low Income) 1,528 $3,429 22,920 0  $3,429  Total Electric Idaho (Residential)    204,054 $206,229 7,993,104 0  $412,028    Table 20:  Other Natural Gas6  Measure        Unit  Count Incentives kWh Therms  Non‐incentive  Utility Costs  Simple Steps Showerheads (Res) 101 $253 0 630  $109  Opower Home Energy Reports (Res)   24,501 $0 0 30,631  $0  Total Gas Idaho (Residential)    24,602 $253 0 31,261  $109                                                                   5 All kWh and therm values reported in this table are gross, excluding the effect of applicable NTG ratios.  6 Ibid.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 20 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 21   Avista Utilities  Low Income and Outreach  The Company leverages the infrastructure of a single Community Action Program agency (CAP) to  deliver energy efficiency programs for the Company’s low income residential customers in the Idaho  service territory. The CAP has resources to income qualify, prioritize and treat clients homes based upon  a number of characteristics.  In addition to the Company’s annual funding, the agency has other  monetary resources that may be leveraged when treating a home with weatherization or other energy  efficiency measures.   The Idaho agency has an in‐house crew that handles the bulk of the efficiency  measures of the program.    Eligible efficiency measures are similar to those offered under the traditional residential rebate  programs, as well as mirroring a variety of the same measures found of the state program priority list.  A  Company approved measure list is provided to the agency in an attempt to manage the cost‐ effectiveness of the low income program. The agency is only allowed to treat electrically heated homes  in Idaho due to the suspension of natural gas programs in November 2012.  Eligible measures include  improvements to insulation, infiltration, ENERGY STAR® doors and refrigerators along with fuel  conversion from electric resistance space and water heat to natural gas.  Avista’s funding covers the full  cost of the improvement from the “Approved Measure” list.  Example of 2013 Approved Measure List  • Air infiltration   • Duct sealing  • Insulation for attic, walls and floors   • ENERGY STAR doors  • ENERGY STAR refrigerators (for replacement of a refrigerator that is not fully operational)   • Variable speed motor  • Electric to natural gas furnace  • Electric to natural gas combination (furnace and water heater)    If agencies identify other efficiency measures that are not on the approved measure list, those projects  can be submitted to Avista for funding consideration on a case by case basis.  The review process  considers the program’s overall cost‐effectiveness in a near real‐time basis as to whether or not those  measures may be installed in the home.    Example of 2013 Needs Approval Measure List  • Duct insulation  • High efficiency electric water heaters (0.93 Energy Factor)  • Energy Star Refrigerators (for replacement of refrigerator that is currently operating)  • Energy Star Windows  • Electric to air source heat pump (when natural gas is not a viable option)   • Electric to natural gas water heater  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 21 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 22   Avista Utilities  In 2013, the Idaho agency received a total funding amount of $700,000 dollars.  The annual contract  allows the agency to charge a 15 percent administration fee towards the cost of each measure.  In  addition, up to 15 percent of their annual funding allocation may be used towards Health and Safety  improvements.  It is at the agencies discretion whether or not to utilize their funds for health and safety  and other home repairs to ensure the habitability of the home where the energy efficiency  improvements were made.    There was significant effort by the Idaho Public Utilities Commission (IPUC), investor‐owned utilities  (IOUs) and other stakeholders to consider modifications to Low Income program implementation in  order to improve cost‐effectiveness.  The end result was an IPUC order no. 32788 (case no. GNR‐E‐12‐ 01) provided to IOUs in April 2013.    The most notable change in 2013 was the suspension of natural gas programs.  At Avista’s request, the  IPUC approved suspending the offerings of Schedule 190 in 2012.  The filing was approved in November  with a transition plan that allowed agencies to continue to serve low income customers in Avista natural  gas heated homes through the end of their contract year, which concluded in December 2012.   The  2013 calendar year was the first for the agency to focus on only electric heated with Avista funding.  It is  estimated that approximately 118 Avista natural gas customer’s weatherization applications expired  because current funding streams were unavailable for those types of homes. The agency was able to  spend out their allocation for the year in part due to increasing contractor‐delivered electric to natural  gas conversions, however, this did create a barrier to weatherize the home with agency crews (due to  the home now being served with natural gas heat). The agency performed well given these challenges  along with reduced leveraging opportunities from regular and stimulus‐based federal funding that  resulted in reductions of weatherization and program personnel.    For the 2013 program year, Idaho income‐qualified customers had over 300 individual measures  installed in 100 individual homes, acquiring nearly 500 MWh while spending the full $700,000 funding  allocation.  Refer to table 21 for details on electric low income programs.  There were no natural gas low  income programs.      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 22 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 23   Avista Utilities  Table 21:  Electric Low Income7  Measure   Project  Count Incentives kWh Therms  kWh  Avoided  Costs  Therms  Avoided  Costs  Non‐ energy  Benefits  Customer  Incremental  Costs  Non‐ incentive  Utility Costs  E Air Infiltration 78  $103,383  23,238  0  $18,727  $0  $0  $103,383  $7,107   E Duct Sealing 34  $26,279  44,553  0  $35,904  $0  $0  $26,279  $13,626   E ENERGY STAR Doors 46  $44,220  15,310  0  $21,278  $0  $51,262  $44,220  $8,075   E ENERGY STAR Windows 23  $41,991  657  0  $913  $0  $51,619  $41,991  $346   E He Air Hpump 2  $1,511  4,578  0  $802  $0  $3,000  $1,511  $304   E Ins ‐ Ceil/Attic 32  $47,790  15,761  0  $21,904  $0  $0  $47,790  $8,313   E Ins ‐ Floor 50  $151,485  73,147  0  $101,658  $0  $0  $151,485  $38,582   E Ins ‐ Wall 7  $17,414  6,963  0  $9,676  $0  $0  $17,414  $3,672   E to G Furnace Conversion 19  $108,418  200,864  (2,528) $41,841  ($20,817) $28,500  $108,418  $15,880   E to G H2O Conversion 17  $43,724  104,522  (1,473) $12,489  ($8,061) $8,500  $43,724  $4,740   E to G Hpump Conversion 2  $9,242  10,309  0  $5,699  $0  $3,000  $9,242  $2,163   Health & Human Safety 0  $104,542  0  0  $0  $0  $143,673  $104,542  $0   Total Idaho Electric       310  $700,000       499,901       (4,001) $270,889  ($28,879) $289,554  $700,000  $102,809       In Idaho, a $50,000 conservation education (ConEd) grant funded through the DSM tariff rider was  provided to the Community Action Partnership (CAP) in Lewiston. The grant resulted from an Idaho  General Rate Case settlement and covers the salary/wage, benefits travel, space costs for a Community  Education Specialist along with supplies and administration costs for ConEd activities.  The objectives of  CAP’s low income consumer energy conservation education program include:   • Increase ConEd knowledge and awareness of low income individuals  • Build capacity for ConEd in local communities, and  • Decrease energy consumption  These objectives are achieved through low, medium and high impact strategies.  These strategies start  with basic awareness building (low impact) activities through a rotating presentation that is visible to  individuals as they wait for their energy assistance appointment in CAP offices as well as the distribution  of print materials and Compact Fluorescent Lamps (CFLs) to those seeking assistance from the CAP.   Medium impact includes workshops and participation in community events to increase individual  knowledge of energy conservation.  Finally, high impact activities include one‐on‐one education with  those are receiving weatherization and other energy efficiency installations in their home.  The CAP  recognizes this strategy as providing the greatest opportunity for lasting behavioral change, although it  is the highest cost and serves the fewest number of individuals.  To monitor program performance, CAP submits a quarterly report to Avista providing a summary of the  ConEd activities.  The report captures information regarding the number of Avista customers reached  through the various strategies and results from the program evaluation.                                                               7 All kWh and therm values reported in this table are both gross and net, as the NTG ratio is assumed to be 100%.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 23 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 24   Avista Utilities  In 2013, the community education specialist facilitated workshops and participated in community events  reaching 1,704 people.  Seventeen one‐on‐one education activities were conducted in conjunction with  home weatherization in Avista‐heated homes. Additionally, the community education specialist  participates in Avista sponsored mobile outreach and energy fairs.   In addition to the ConEd activities conducted by the CAP, Avista Consumer Affairs and DSM staff  conducts workshops, mobile outreach and general outreach to engage senior and low‐income  customers in education to effectively manage home energy use, learn about bill payment options and  community assistance resources. Visitors to the Energy Resource Van and participants at workshops are  provided with samples of low cost energy saving items such as weather stripping, plastic window kits,  refrigerator coil cleaners and an Energy Resource Guide that provides information about managing  energy costs. At Energy Fairs, customers can access energy assistance resources, make arrangements on  their bills, see demonstrations on how to install energy saving materials and learn more about  community resources.  In 2013, the company hosted education and outreach activities reached a total of  2,092 senior and low income customers; 404 participants through 11 Avista facilitated workshops, 345  individuals through two energy fairs and 1,343 individuals visited the Energy Resource Van.        Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 24 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 25   Avista Utilities  Nonresidential  Within the nonresidential segment, programs are offered to retail electric customers through a  combination of prescriptive rebates and site specific assessments.  Prescriptive rebates are geared  toward relatively uniform measures, applications and energy savings.  This delivery method reduces  implementation expense while simplifying the ease of participation for both customers and trade allies.   The site specific offerings are available for all other efficiency measures and applications.  In these  situations, each energy efficiency project is individually analyzed based on the measure being installed  and considers other variables that may be present in the building or in the process operation.  Site specific is the most comprehensive offering of the nonresidential segment and brings in more than a  third of the nonresidential savings.  Avista’s Account Executives work with nonresidential customers to  provide assistance in identifying energy efficiency opportunities.  Customers receive technical assistance  in determining potential energy and cost savings as well as identifying and estimating incentives for  participation.  Site specific incentives, in which the tier structure applies, are capped at seventy percent  of the incremental project cost for lighting projects with simple paybacks of less than 3 years and non‐ lighting projects (or lighting projects with a verified life of 40,000 hours or more) with simple paybacks  less than 5 years.  All other project incentives calculated under the tier structure will be capped at fifty  percent of the incremental project cost.  Simple payback criteria for eligible projects is greater than 1  year and less than 8 years for lighting measures or less than 13 years for non‐lighting and LED lighting  measures.  Site specific projects include appliances, compressed air, HVAC, industrial process, motors  (non‐prescriptive), shell and lighting with the majority being HVAC, lighting and shell.  Schedule 191 was suspended in late 2012 and the natural gas programs were discontinued.  Due to  declining natural gas avoided costs, Avista requested the suspension of Schedule 191 until changes in  avoided cost make it possible to again offer cost‐effective natural gas programs.  The IPUC approved this  filing in November 2012.  Some projects were started before the deadline for discontinuation and are  being allowed to be completed.  In 2013, over 800 prescriptive and site specific nonresidential projects were incented.  Avista  contributed over $3.2 million for energy efficiency upgrades in nonresidential applications.   Nonresidential programs contributed over 16,595 MWh and 18,000 therms in annual first‐year energy  savings.  Tables 22 and 23 provide detail on the electric and natural gas nonresidential programs.      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 25 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 26   Avista Utilities  Table 22:  Electric Nonresidential8  Program     Project  Count Incentives kWh Therms  kWh  Avoided  Costs  Therms  Avoided  Costs  Non‐ energy  Benefits  Customer  Incremental  Costs  Non‐ incentive  Utility Costs  Site Specific Other 1  $92,876 446,464  0  $267,171  $0 $0 $345,762 $22,874  Site Specific Shell   2  $8,832 54,655  0  $16,178  $0 $0 $15,267 $4,637  Prescriptive Food Service 17  $5,940 47,137  0  $22,570  $0 $0 $93,763 $1,932  Prescriptive Green Motors   15  $3,490 24,362  0  $9,269  $0 $0 $6,275 $794  Prescriptive Variable Frequency Drives 4  $26,780 317,379  0  $189,924  $0 $0 $63,200 $16,261  Prescriptive Standby Generator Block 1  $400 2,269  0  $1,358  $0 $0 $2,799 $116  EnergySmart Grocer Industrial Process 57  $175,778 1,381,386  0  $792,846  $0 $0 $456,911 $69,223  EnergySmart Grocer Case Lighting   44  $60,386 290,753  0  $61,462  $0 $0 $84,567 $5,262  Prescriptive Windows and Insulation 4  $5,584 27,928  0  $21,845  $0 $0 $19,692 $1,870  Prescriptive Exterior Lighting   149  $654,293 2,746,926  0  $1,257,315  $0 $19,016 $885,434 $107,648  Prescriptive Interior Lighting 442  $1,148,309 3,812,964  (12) $1,745,259  ($47) $102,613 $1,542,056 $149,424  Site Specific Multifamily   1  $36,300 494,895  0  $387,104  $0 $0 $44,462 $33,143  Site Specific ENERGY STAR Clothes Washer 3  $75 692  0  $291  $0 $0 $1,200 $25  Site Specific ENERGY STAR Refrigerator 2  $150 496  0  $263  $0 $0 $180 $23  Site Specific Renewable 1  $158 760  0  $551  $0 $0 $33,575 $47  Site Specific Appliances   1  $0 6,051  0  $2,302  $0 $0 $0 $197  Site Specific Compressed Air 3  $203,592 1,589,810  0  $739,443  $0 $0 $407,182 $63,309  Site Specific Industrial Process   1  $9,097 43,728  0  $18,374  $0 $0 $20,000 $1,573  Site Specific Motor Controls 1  $3,685 22,141  0  $12,503  $0 $0 $7,600 $1,071  Site Specific Motors   1  $183,542 882,302  0  $403,845  $0 $0 $996,356 $34,576  Site Specific HVAC Combined 6  $40,350 305,963  0  $172,400  $0 $0 $345,381 $14,911  Site Specific HVAC Cooling   3  $1,928 13,334  0  $7,979  $0 $0 $3,893 $683  Site Specific HVAC Heating 2  $12,595 163,647  (6,650) $97,929  ($30,780) $0 $127,292 $8,384  Site Specific Exterior Lighting   26  $102,422 743,075  0  $505,687  $0 $9,205 $230,809 $43,296  Site Specific Interior Lighting 41  $417,870 3,176,224  0  $2,089,679  $0 $50,671 $870,322 $178,912                                   Total Idaho Electric    828  $3,194,432 16,595,340  (6,662) $8,823,546  ($30,827) $181,505 $6,603,978 $760,191                                                                    8 All kWh and therm values reported in this table are gross, excluding the effect of applicable NTG ratios.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 26 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 27   Avista Utilities  Table 23:  Natural Gas Nonresidential9  Program     Project  Count Incentives kWh Therms  kWh  Avoided  Costs  Therms  Avoided  Costs  Non‐ energy  Benefits  Customer  Incremental  Costs  Non‐ incentive  Utility Costs  Site Specific Shell 2  $11,386 0  3,064  $0  $10,619 $0 $979 $7,617  EnergySmart Grocer Industrial Process 2  $0 0  1,571  $0  $3,166 $0 $67 $2,417  Prescriptive HVAC Combined 1  $1,631 0  564  $0  $2,613 $0 $3,323 $1,314  Site Specific ENERGY STAR Clothes Washer 1  $75 0  26  $0  $90 $0 $450 $45  Site Specific HVAC Combined 3  $15,236 0  9,652  $0  $33,734 $0 $28,486 $17,067  Site Specific HVAC Heating   3  $5,479 0  3,703  $0  $15,540 $0 $10,958 $7,817                                    Total Idaho Natural Gas    12  $33,807 0  18,581  $0  $65,761 $0 $44,264 $36,277                                                                    9 All kWh and therm values reported in this table are gross, excluding the effect of applicable NTG ratios.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 27 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 28   Avista Utilities  VII. REGIONAL MARKET TRANSFORMATION  Avista’s local energy efficiency portfolio consists of programs and supporting infrastructure designed to  enhance and accelerate the saturation of energy efficiency measures through a combination of financial  incentives, technical assistance, program outreach and education.  It is not feasible for Avista to  independently have a meaningful impact upon regional or national markets.  Consequently, utilities within the northwest have cooperatively worked together through the Northwest  Energy Efficiency Alliance (NEEA) to address those opportunities that are beyond the ability or reach of  individual utilities.  Avista has been participating in and funding NEEA since the 1997 founding of the  organization.  NEEA is currently in its fourth funding cycle (2010‐2014).  This fourth five‐year period saw  a doubling of the contractual funding from $20 million to $40 million regionally.  Concurrently, Avista’s  share of NEEA funding increased from 4.0% to 5.4% due to shifts in the distribution of regional retail  end‐use load.  Avista’s criteria for funding NEEA’s electric market transformation portfolio calls for the portfolio to  deliver incrementally cost‐effective resources beyond what could be acquired through the Company’s  local portfolio alone.  Avista has historically communicated with NEEA the importance of NEEA  delivering cost‐effective resources to our service territory.  The Company believes that NEEA will  continue to offer cost‐effective electric market transformation in the foreseeable future.  During 2013, Avista contributed $801,838 to fund NEEA’s electric market transformation activities.  The  funding resulted in a corresponding 4,643 MWh in energy savings.  Avista will continue to play an active role in the organizational oversight of NEEA.  This will be critical to  insure that geographic equity, cost‐effectiveness and resource acquisition continue to be primary areas  of focus.  NEEA has initiated a preliminary investigation of the prospects for a natural gas market transformation  portfolio.  Avista has actively encouraged NEEA to explore this role and believes that regional market  transformation may be a valuable addition to the delivery mechanisms available to the utility industry in  the cost‐effective acquisition of natural gas resources.      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 28 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 29   Avista Utilities  VIII. ENERGY EFFICIENCY EXPENDITURES  During 2013, Avista incurred over $7.6 million in costs for the operation of electric and natural gas  energy efficiency programs, with $7.5 million for electric energy efficiency and $145 thousand for  natural gas energy efficiency.  Of this amount, $802 thousand was contributed to the Northwest Energy  Efficiency Alliance to fund regional market transformation ventures.  Sixty‐four  percent of expenditures were returned to ratepayers in the form of incentives or products  (e.g. CFLs).  During the 2013 calendar year, over $76 thousand, or 1.0 percent, was spent on evaluation  in an effort to continually improve program design, delivery and cost‐effectiveness.  Incentives are directly charged to the state where the customer resides and receives utility service.   Nonresidential site‐specific incentives tend to be somewhat “lumpy” in nature due to the size and  longer installation lead times on these larger projects.  Starting in 2012, there was a market  transformation effort on the conversion of fluorescent T12 to T8 bulbs and this contributed to increased  incentives toward the end of 2012 and continued into 2013.  Prescriptive and site specific lighting  incentives contributed significantly to the total incentives.  Evaluation, as well as other implementation expenditures, can be directly charged to the appropriate  state and/or segment(s).   In cases where the work benefits multiple states or segments, these  expenditures are charged to a “general” category and are allocated based on avoided costs for cost‐ effectiveness purposes.  The expenditures illustrated in the following tables represent actual payments incurred in the 2013  calendar year and often differ from the cost‐effectiveness section where all benefits and costs  associated with projects completing in 2013 are evaluated in order to provide matching of benefits and  expenditures resulting in a more accurate look at cost‐effectiveness.  Tables 24 and 25 provide a summary of energy efficiency expenditures by fuel type.      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 29 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 30   Avista Utilities  Table 24:  Electric Energy Efficiency Expenditures    Segment    Incentives Implementation EM&V NEEA Total  Residential    $337,831 $649,853 $39,794 $0  $1,027,478  Low Income   $677,267 $73,386 $6,766 $0  $757,419  Nonresidential    $3,743,030 $293,156 $53,184 $0  $4,089,370  Regional   $0 $5,178 $23,678 $801,838  $830,695  General    $0 $815,575 ($30,951) $0  $784,624      $4,758,128 $1,837,148 $92,472 $801,838  $7,489,586      Table 25:  Natural Gas Energy Efficiency Expenditures  Segment    Incentives Implementation EM&V Total  Residential    $5,151 $975 $2,570 $8,696   Low Income   $22,716 ($230) $603 $23,089   Nonresidential    $70,474 $12,076 $3,858 $86,408   Regional   $0 $0 $0 $0   General    $0 $50,262 ($23,176) $27,086       $98,341 $63,082 ($16,145) $145,278        Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 30 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 31   Avista Utilities  IX. TARIFF RIDER BALANCES  As of the start of 2013, the Idaho electric and natural gas (aggregate) tariff rider balances were  overfunded by $296,627.  During 2013, $4.6 million in tariff rider revenue was collected to fund energy  efficiency while $7.6 million was expended to operate energy efficiency programs.  The $3.1 million  under‐collection of tariff rider funding resulted in a year‐end balance of $2.8 million underfunded  balance.  During the first quarter of 2014, the underfunded balance has decreased to a total underfunded amount  of $2.0 million.  This amount is attributable to Idaho electric which ended the year with an underfunded  balance of $3.5 million mostly due to the nonresidential prescriptive and site specific lighting programs.  Table 26 illustrates the 2013 tariff rider activity by fuel type.  Table 26:  Tariff Rider Activity   Idaho    Electric    Natural Gas   Beginning Balance (Underfunded)  ($522,697)$819,324   Energy Efficiency Funding  $4,553,054 $0   Net Funding for Operations  $4,030,356 $819,324   Energy Efficiency Expenditures  $7,489,545 $145,266   Ending Balances (Underfunded)  ($3,459,189)$674,059     Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 31 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 32   Avista Utilities  X. ACTUAL TO BUSINESS PLAN COMPARISON  For 2013 operations, Avista exceeded budgeted electric energy efficiency expenditures by $2.0 million,  or 36 percent and natural gas expenditures were $145 thousand with no budget.  The biggest driver of  expenditures was incentives.  This demand for incentives was higher than anticipated and its impact  resulted in the underfunding in the Idaho electric programs.  Idaho natural gas had no budget but some  projects were permitted to be completed, due to contractual obligations and prior approval.  While the business plan provides an expectation for operational planning, Avista is required to incent all  energy efficiency that qualifies under Schedules 90 and 190.  Since customer incentives are the largest  component of expenditures, customer demand can easily impact the funding level of the Tariff Riders.  Table 27 provides detail on the budget to actual comparison of energy efficiency expenditures by fuel  type.  Table 27:  Business Plan to Actual Comparison10   Idaho        Electric    Natural Gas    Incentives Budget  $2,580,797  $0   Non‐incentives and Labor  $2,910,298  $0   Total Budgeted Expenditures  $5,491,095  $0   Actual 2013 Expenditures    Incentives  $4,758,128 $98,341   Non‐Incentives & Labor  $2,731,458 $46,937   Total Actual Expenditures  $7,489,586 $145,278   Variance (Unfavorable)  ($1,998,491) ($145,278)                                                                 10 Budget values from 2013 Business Plan  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 32 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 33   Avista Utilities                  APPENDICES        Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 33 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 34   Avista Utilities              Appendix 1    Avista 2013 Idaho Electric Impact Evaluation Report  June 17, 2014  The Cadmus Group, Inc.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 34 of 296     Avista 2013 Idaho Electric  Impact Evaluation Report  June 17, 2014    Avista Corporation  1411 E Mission Avenue  Spokane, WA 99252      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 35 of 296                             This page left blank.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 36 of 296                             Prepared by:  Danielle Côté‐Schiff Kolp, MESM  Andrew Wood  Jeff Cropp  Scott Reeves  Jim Stewart  Matei Perussi  Michael Visser  Andrew Reitz  Madison Busker  Zachary Horvath  M. Sami Khawaja, Ph.D.    Cadmus                        Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 37 of 296                             This page left blank.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 38 of 296   i  Table of Contents  Definitions ..................................................................................................................................................... 1  Portfolio Executive Summary ........................................................................................................................ 2  1. Residential Impact Evaluation ................................................................................................................ 9  1.1. Introduction .................................................................................................................................. 9  1.2. Methodology ................................................................................................................................ 9  1.3. Program Results and Findings .................................................................................................... 12  1.4. Residential Conclusions .............................................................................................................. 55  1.5. Residential Recommendations ................................................................................................... 56  2. Residential Behavior Program .............................................................................................................. 58  2.1. Program Description ................................................................................................................... 58  2.2. Residential Behavior Program Impact Evaluation Methodology ............................................... 60  2.3. Program Results and Findings .................................................................................................... 67  2.4. Residential Behavior Program Conclusions ................................................................................ 72  2.5. Residential Behavior Program Recommendations ..................................................................... 73  3. Nonresidential Impact Evaluation ........................................................................................................ 74  3.1. Introduction ................................................................................................................................ 74  3.2. Methodology .............................................................................................................................. 77  3.3. Results and Findings ................................................................................................................... 82  3.4. Nonresidential Conclusions ........................................................................................................ 91  3.5. Nonresidential Recommendations ............................................................................................. 92  4. Low Income Impact Evaluation ............................................................................................................ 93  4.1. Introduction ................................................................................................................................ 93  4.2. Data Collection and Methodology .............................................................................................. 94  4.3. Data Screening and Modeling Approach .................................................................................... 95  4.4. Results and Findings ................................................................................................................... 97  4.5. Comparison to Previous Billing Analysis ..................................................................................... 99  4.6. Benchmarking ........................................................................................................................... 101  4.7. Low Income Conclusions .......................................................................................................... 102  4.8. Low Income Recommendations ............................................................................................... 103  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 39 of 296   ii  5. Portfolio Savings and Goals ................................................................................................................ 105  5.1. Gross Portfolio Savings ............................................................................................................. 105  5.2. NTG Adjustment ....................................................................................................................... 105  5.3 Net Portfolio Savings ................................................................................................................ 107  5.4 IRP Goals Achievement ............................................................................................................. 108  Appendix A: Residential Billing Analysis Model Specifications ................................................................. 109  Appendix B: Residential Behavior Program Data Cleaning Procedures .................................................... 112  Appendix C: Residential Behavior Program Regression Model Estimates ................................................ 114  Appendix D: Low Income Weatherization Participant Survey .................................................................. 115  Appendix E: Low Income Weatherization – Billing Analysis Model Specification .................................... 123      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 40 of 296   1  Definitions     Reported Savings Electricity savings that are reported in Avista’s tracking database.  Gross Evaluated  Savings  Electricity savings that have been verified through evaluation activities such as  records review, verification surveys or site visits, and engineering analysis.  Realization Rate The ratio of gross evaluated savings over the reported savings.  Net Evaluated  Savings  The portion of savings directly attributable to the program; savings that would  have otherwise not occurred without program influence. These also include  participant and nonparticipant spillover.  Net‐to‐Gross Ratio Ratio of net evaluated savings to gross evaluated savings.  Savings Goal Integrated Resource Planning or Avista Business Plan savings goal.  Achievement Rate Ratio of evaluated savings over the savings goal.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 41 of 296   2  Portfolio Executive Summary  For several decades, Avista Corporation has been administering demand‐side management (DSM)  programs to reduce electricity and natural gas energy use for its portfolio of customers. Avista  contracted with Cadmus to complete process and impact evaluations of the company’s program year  (PY) 2013 electric DSM programs in Idaho; this report presents our impact findings.  Evaluation Activities  We conducted the evaluation using a variety of methods and activities shown in Table 1.  Table 1. PY 2012‐PY 2013 Electric Programs’ Evaluation Activities  Sector Program  Document/  Database  Review  Verification/  Metering  Site Visit  Survey Billing  Analysis  Engineering  Simulation  Residential  Simple Steps, Smart  Savings™ 9         Second Refrigerator and  Freezer Recycling 9  9     ENERGY STAR® Products 9 9     Heating and Cooling  Efficiency 9  9     Weatherization/Shell 9  9 9   Water Heater Efficiency 9  9     ENERGY STAR Homes 9         Space and Water  Conversions 9  9 9   Geographic CFL  Giveaway 9       Behavior Program 9   9   Nonresidential  Prescriptive programs 9 9 9     Site‐Specific 9 9 9 9 9 EnergySmart Grocer 9 9 9     Low Income Low income programs 9  9 9     Savings Results  Overall, the Idaho portfolio achieved a 102.7% realization rate, and acquired 25,899,345 kWh in annual  gross savings (Table 2).  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 42 of 296   3  Table 2. PY 2013 Reported and Gross Evaluated Savings   Segment* Reported Savings  (kWh)  Gross Evaluated  Savings (kWh) Realization Rate  Residential 5,130,507 5,933,197 115.6% Nonresidential 17,602,253 16,595,342 94.3% Low Income 292,767 499,901 170.8% Residential Behavior* 2,194,322 2,870,905 130.8% Total  25,219,849 25,899,345 102.7% * Note that residential Behavior Program savings are inherently calculated as net, and are therefore presented  here as net.    The overall net to gross ratio was estimated at 85% leading to 21,999,099 kWh of net savings (Table 3).   Table 3. 2013 Idaho Net Savings  Sector Gross Evaluated  Savings (kWh) NTG Net Evaluated Savings  (kWh)  Residential 8,804,102 92%8,063,080 Nonresidential 16,595,342 81%13,436,118 Low Income 499,901 100%499,901 Total  25,899,345 85%21,999,099   Goal Achievement  Table 4 and Table 5 show achieved savings toward the IRP and Avista Business Plan goals. Both goals  were exceeded. The IRP goal is set at the portfolio‐level. In order to conduct sector‐level analysis,  Cadmus adopted the Avista Business Plan goals by sector, and applied the corresponding proportions to  the IRP targets. The tables also show saving achievements for the portfolio excluding the residential  Behavior program. The IRP goal is still met, but the more aggressive Business Plan goal falls short.  Table 4. PY 2013 IRP Goals and Achieved Savings  Sector Savings Goal (kWh) Achieved (kWh) Achievement  Rate  Residential 7,697,009 8,063,080 104.8% Nonresidential 10,849,696 13,436,118 123.8% Low Income 462,495 499,901 108.1% Total  19,009,200 21,999,099 115.7%    Excluding Residential Behavior 19,009,200 19,128,194 100.6%   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 43 of 296   4  Table 5. PY 2013 Avista Business Plan Goals and Achieved Savings  Sector Savings Goal (kWh) Achieved (kWh) Achievement  Rate  Residential 8,547,340 8,063,080 94.3% Nonresidential 12,048,322 13,436,118 111.5% Low Income 513,589 499,901 97.3% Total  21,109,251 21,999,099 104.2%    Excluding Residential Behavior 21,109,251 19,128,194 90.6%   Key Findings and Conclusions  Portfolio Level  As shown in Figure 1, realization rates have remained fairly steady for the nonresidential sector and  increased over the last several years for residential and low income.   Figure 1. Realization Rates of Portfolio Savings      The national environment for DSM is becoming more challenging with the implementation of the Energy  Independence and Security Act of 2007 (EISA), and more stringent codes and standards. Avista is  meeting these challenges with new measure and program ideas. On the residential side, light‐emitting  diodes (LEDs) have been added to their upstream lighting program. For the nonresidential portfolio in  2014, Avista is starting a large fleet engine block heater program, targeting gas station canopy LED  lighting, and an exterior LED signage program.   82% 99% 27% 104%96%102% 116% 94% 171% 0% 20% 40% 60% 80% 100% 120% 140% 160% 180% Residential Nonresidential Low Income 2010‐2011 2012 2013 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 44 of 296   5  In future years, Avista may consider devoting additional resources to investigate new technologies and  program offerings. Some initial examples include the following:  • Home Performance with ENERGY STAR;  http://www.energystar.gov/index.cfm?fuseaction=hpwes_profiles.showsplash,  • Central air conditioners for residential application (as our general population research supports  a sizable load with customer stated intentions of potential increased saturations),  • A refresh of commercial direct install measures (either new, or repeat of measures installed 5‐10  years ago),   • Investigate the upcoming Tenant Star for leased commercial space,  • Commercial retrocommissioning or continuous commissioning (primarily for larger, complex  facilities such as hospitals and college campuses; for example,  http://www.pge.com/en/mybusiness/save/rebates/retrocommissioning/index.page),  • Comprehensive compressed air system audits and upgrades to address both demand and  supply‐side operation (based on Compressed Air Challenge best practices;  http://www.compressedairchallenge.org/),  • Strategic energy management (similar to Energy Trust of Oregon’s SEM program;  http://energytrust.org/library/GetDocument/1876).  Residential  For PY 2013, Avista’s residential electric programs produced 8,063,080 kWh in net savings, yielding a  120% overall realization rate of reported savings, and 105% of equivalent residential IRP goals.  • Overall, residential electric customers responded well to the programs, often installing several  measures within the same year.  • Tracking databases proved adequate for evaluation purposes, providing sufficient contact  information and measure and savings information. During the database review, Cadmus  confirmed the information was reliable and accurate.  • All rebated measures had been installed and continued to operate.   • Homes participating in the Behavior Program saved on average 0.674 kWh (1.57%) per day. The  percentage savings were higher than expected (1.2%).   Nonresidential  For PY 2013, Avista’s nonresidential electric programs produced 13,436,118 kWh in net savings, yielding  a 94% overall realization rate of reported savings, and 124% of equivalent nonresidential IRP goals.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 45 of 296   6  Cadmus evaluated 142 of 6,476 measures installed through the programs, representing 16% of reported  savings. In general, Cadmus determined that Avista implemented the programs well. Cadmus identified  the following key issues that led to adjusted energy savings:  • Metering on post‐installation power consumption for several industrial process measures  indicated that the evaluated energy savings varied from the reported value.  • Some participants did not operate the incented equipment correctly or did not complete the  improvements expected for the measure.  • Some participant post‐installation heating or cooling loads did not achieve the level of projected  consumption, which reduced energy savings.  • Simulation models sometimes did not accurately represent the actual as‐built building or system  operation.  • There were instances where thorough analysis of energy‐savings calculations provided by  participants or third‐party contractors was lacking.  • Some projects had data entry errors in characterizing building or measure performance.  Low Income  For PY 2013, Avista’s low income electric programs produced 499,901 kWh in net savings, yielding a  171% overall realization rate of reported savings and 108% of equivalent low income IRP goals.  Compared to PY 2010, Avista’s PY 2013 low income program demonstrated an increase in average  electric savings per participant, in addition to an increase in the overall program realization rate. Several  factors may have contributed to the increase in participant savings, including:  • An increased frequency of installing high‐saving measures (e.g., shell), and  • Changes in agency delivery protocols or energy‐saving installations made with non‐utility  funding.  One factor contributing to higher realization rates are lower average reported savings occurring in the  evaluation period compared to previous years.   Recommendations and Further Analysis  Residential  Cadmus recommends the following changes to Avista’s residential electric programs:  • Consider updating per‐unit assumptions of recycled equipment to reflect the findings in this  evaluation.  • If clothes washer rebates are ever reinstated, Avista should continue to track them all within the  electric program unless there is a large increase in penetration of gas dryers.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 46 of 296   7  • Increase measure level detail capture on applications. Specific additional information should  include energy factors or model numbers for appliances, baseline information for insulation, and  home square footage, particularly for the ENERGY STAR Homes.  • Consider tiered incentives by rating as higher SEER systems generally require ECM fan motors.   • Consider completing a lighting logger study within its territory if Avista believes the results of  the forthcoming Residential Building Stock Assessment (RBSA) study do not accurately represent  usage in their territory.  • Consider researching the percentage of Simple Steps, Smart Savings bulb purchase that are  installed in commercial settings. This will increase the average installed hours of use and  increase estimated program savings.  • Perform a billing analysis on ENERGY STAR homes using a non‐participant comparison group  once enough homes have participated under the new requirements.  • Consider researching the current variable speed motor market activity to determine if this  measure should continue as a stand‐alone rebate or be packaged with other equipment  purchases.  • Continue to promote efficiency programs in the Behavior Program energy reports, as the reports  increased both the rate of efficiency program participation and savings.   • Avista should consider performing additional research about the peak‐coincident demand  savings from the behavior program   Nonresidential  We have the following recommendations for improving program energy‐savings impacts and evaluation  effectiveness:  • Create a quality control system to double‐check all projects with savings over 300,000 kWh.   • Avista may want to consider tracking and reporting demand reduction to better understand  measure load profiles and peak demand reduction opportunities.  • Update prescriptive measure assumptions and sources on a regular basis.  • Streamline file structure to enable reviewers more easily identify the latest documentation.  • Continue to perform follow‐up measure confirmation and/or site visits on a random sample of  projects (at least 10%).  • Consider flagging sites for additional scrutiny when the paid invoice does not include installation  labor as it may indicate that the work was not yet performed.  • Avista may consider adding a flag to their tracking database to automatically detect potential  outliers (e.g., savings per dollar (kWh/$ or therm/$)).   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 47 of 296   8  • In the case of redundant equipment, Avista may want to consider incenting pump projects  through the Site‐Specific Program to more accurately characterize the equipment operating  hours.  • Avista may want to set minimum standards for modeling design guidelines. The Energy Trust of  Oregon provides an example on their website.  Low Income  Cadmus recommends the following enhancements in order to improve program impact results:   • Consider including a control/comparison group in future billing analyses.   • Consider options for increasing the analysis sample size due to small program populations (such  as combining Washington and Idaho program participants).   • Obtain a full list of weatherization measures from agencies.   • Consider targeting high‐use customers.   • Track and compile additional data from agency audits.   • Consider performing quantitative, non‐energy benefit analyses.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 48 of 296   9  1. Residential Impact Evaluation  1.1. Introduction  We designed our impact evaluation to verify reported program participation and energy savings. We  used data collected and reported in the tracking database, online application forms, phone surveys,  billing analyses, RTF savings review, and applicable updated deemed savings values.  1.2. Methodology  1.2.1. Sampling  Record Review Sampling  To determine the percentage of measures incented that qualified for the program, Cadmus designed  sample sizes to yield result at the 90% level of confidence and ±10% precision level for each application  type, across both states and both fuel types. Cadmus randomly selected participant measures for a  record qualification review from the 2013 gas and electric program populations across both states  served. We sampled participants using a single measure record. However, if a customer applied for  multiple rebates on the same application form during the program year, we checked all measures  included in the application for qualification, whether the fuel was electric or gas.  Table 6 shows the number of record reviews we completed of unique accounts and unique measures.  Table 6. Measure‐Level Record Reviews Completed  Application Type 2013 Applications Reviewed 2013 Measures Reviewed  ENERGY STAR Products 99 135  Home Improvement 102 142  ENERGY STAR Homes 18 18    Survey Sampling  Cadmus conducted the participating customer surveys in February 2014. Table 7 provides a summary of  unique customers (identified using Avista account number) and surveys completed in each effort.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 49 of 296   10  Table 7. Residential Participant Details and Survey Sample—Combined Washington and Idaho  Measure Type 2013  Participants Surveys  Percent   Natural Gas and Electric Programs  ENERGY STAR Products 782 65 8% Heating and Cooling Efficiency 2,490 70 3% Water Heating 316 60 19% Weatherization and Shell Measures 313 60 19% Electric‐Only Programs  Second Refrigerator and Freezer Recycling 1,319 65 5% Space and Water Conversions 156 37 24% Total 5,376 357 7%   Cadmus designed participant survey completion targets to yield results with 90% confidence and ±10%  precision levels at the measure‐category and state level. Cadmus deemed this necessary as data  collected through these surveys—specifically installation rates—were used to inform an impact  assessment of Avista’s residential programs. The participant survey sampling plan also drew upon  multiple factors, including feasibility of reaching customers, program participant populations, and  research topics of interest.   Cadmus did not conduct participant surveys with Simple Steps, Smart Savings customers, as that  program has an upstream focus and therefore does not track participant contact information. Similarly,  for ENERGY STAR Homes, Cadmus did not survey residential customers purchasing rebated homes as the  rebates were paid to the builders. Cadmus also did not survey Residential Behavior program  participants.  Within each program, Cadmus randomly selected program participant contacts included in survey  sample frames. A review of collected data shows geographic distribution of survey respondents  clustered around urban centers, specifically the cities of Spokane, Coeur d’Alene, Pullman, Moscow, and  Lewiston. This aligns with population distributions in Avista’s service territory. Figure 2 provides the  distribution of participating customer survey respondents.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 50 of 296   11  Figure 2. Geographic Distribution of PY 2012 ‐ PY 2013 Participating Customer Survey Respondents      1.2.2. Data Collection and Analysis   Record Review  Cadmus reviewed all records for the selected sample of accounts, checking them for completeness and  program compliance using the data they contained. Measures qualified if all data found in the  application complied with the program specifications. As Cadmus randomly sampled customers by  application type (and several measures can be found on different application forms), we tracked  qualification rates by the type of application. All 2013 sampled applications qualified for program  incentives.  Surveys  Cadmus contracted with market‐research firm Discovery Research Group (DRG) to conduct surveys with  the selected participants. To minimize response bias, DRG called customers during various hours of the  day and evening, as well as on weekends, and made multiple attempts to contact selected participants.  Cadmus monitored survey phone calls to ensure accuracy, professionalism, and objectivity. We analyzed  the survey data at the program level, rather than at the measure level. Survey results at the portfolio  level are weighted by program participation to ensure proper representation.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 51 of 296   12  Database Analysis   Cadmus reviewed the participant database provided by Avista to check for inconsistencies in reported  savings and measure duplications. This review is necessary as Avista uses the database to track both  achieved savings and rebates paid. Our review revealed multiple cases for the tracked savings did not  follow the 2012 Avista TRM. These differences are described later in the report.   Unit Energy Savings  Cadmus reviewed every high impact prescriptive measure except the weatherization and shell measures  for which we determined savings from a billing analysis. During each program year, Avista updates unit  energy savings (UES) to reflect the gross energy savings achieved by a measure’s installation. Details on  each measure are included in the program sections below.  Billing Analysis  Cadmus conducted a statistical billing analysis of monthly meter data to determine the adjusted gross  savings and realization rates for the following electric measures: weatherization, conversions to air  source heat pump, and conversions to natural gas. We used a pre‐ and post‐installation combined  Conditional Savings Analysis (CSA) and Princeton Score Keeping Method (PRISM) approach.   Verification Rates  Cadmus determined verification rates for each program. Where applicable, we administered verification  site visits and surveys, which included:   • Checking correct measures were tracked in the database;   • Correct quantities were accounted for; and   • Units remained in place and were operable.   1.2.3. Measure Qualification Rates  Cadmus considered a measure qualified if it met the requirements in its category, such as being ENERGY  STAR‐certified or meeting the minimum efficiency standards for the program. We ensured all  qualifications were met and, when necessary, conducted online database searches of the model  numbers and noted qualifying characteristics. All measures reviewed qualified for program incentives.  The total qualification rate for all 2013 residential electric programs was therefore 100%.   1.3. Program Results and Findings  1.3.1. Overview  Cadmus analyzed data records, maintained by either Avista or an implementation contractor, to  determine appropriate unit energy savings (UES) and measure counts for each supported measure  within each program. The end result is the total adjusted gross savings for each measure and program,  as well as the overall realized savings for each program.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 52 of 296   13  We followed the same steps for calculating adjusted gross measure savings for all programs except  Simple Steps, Smart Savings, Second Refrigerator and Freezer Recycling, and Residential Weatherization:   • Review program database to determine if the adjusted measure counts correctly represent the  number of installations.   • Conduct a phone survey or site visit to verify that the installation is within Avista’s service  territory.   • Calculate verification and qualification rates.  • Calculate deemed measure savings for products rebated during the program period.  • Apply verification and qualification rates and deemed savings to the measure counts to  determine the adjusted gross savings for each measure.  Details on the calculation methods used for Simple Steps, Smart Savings™, Second Refrigerator and  Freezer Recycling, and Residential Weatherization are included in their specific sections below.  1.3.2. Simple Steps, Smart Saving  Program Description  Avista’s Simple Steps, Smart Savings is an upstream incentive program that is an effective alternative to  traditional mail‐in incentives because of its ease of participation, widespread accessibility, and low  administrative costs. This type of program allows utilities’ incentives to pass directly from manufacturers  to retailers, which then reduce bulb prices to their customers. The program motivates retailer  participation by reducing bulb prices without a loss in profits. For the customer, participation may be so  seamless they are unaware they have purchased an incentivized bulb or participated in a utility  program.   Upstream programs, however, pose particular evaluation challenges because calculating metrics, such  as in‐service rates (ISR) and attributions, traditionally relies on surveying purchasers of incentivized  products. As part of our determination of program savings, we referred to the Northwest Regional  Technical Forum (RTF) UES assumptions, Avista’s program records, and metering data collected by  Cadmus for similar measure installations.   This program incents various CFLs and LEDs from standard twist to specialty bulbs that include 3‐way,  reflector, dimmable, globe, and other specialty bulbs. There are unique assumptions for standard twist  bulbs and specialty bulbs; therefore, each was analyzed separately. Based on program funding, 30% of  all bulb sales are assumed to be associated with residential sockets in Idaho.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 53 of 296 Analysis  This prog compone factor (W   W The annu the meth methodo CFL Watt Table 8 s determin discrepa either an  T S L L T T   ram has six d nt: CFL watt HF), and ISR.  Where:   Meas DWM  HOU   DAYS  WHF   ISR   al savings alg dology use ogy compon age  hows the rep d from ven cy is likely d over‐ or und T Twist  pecialty  ED Bulb  ED Fixture  Total  Totals may diff ifferent para ge, delta wa The followin re Watts  =    =   =   =   =   =   orithm is de  by the RTF f nt is discuss rted and ev or provided d ue to monthl r‐counting o Table 8. To pe  er from the su meters to inf t multiplier (  algorithm s Wattage of  The differe measure b Daily lightin Days per ye An adjustm measures o In‐service r ived from in or calculatin ed in detail b aluated bulb a data docum  adjustment f the total sa tal Reported  m of values du 14  orm the calc DWM), hour hows the an the purchas ce in wattag lb divided b g operating h ar, 365.25  ent represen n heating an te, or perce ustry‐stand  energy use a below.  and fixture s nting sales a  made in th les volume. and Evaluat Reported  12 3 17 e to rounding. ulation of gro ‐of‐use (HO ual energy li d CFL or LED e between t  the wattage  hours  ting the inte  cooling equ tage of unit rd engineeri nd savings f les for this p llocated to A  database, w ed CFLs Sold  8,960 5,652 9,446 9 4,068 ss savings fo ), days‐per‐y ghting savin e baseline b of the meas active effect ipment oper  installed  ng practices,  or residentia rogram. Eval ista’s territo hich in turn m by Year  Evaluate r the lighting  year, waste h s:   ulb and the  ure bulb  s of lighting  ation  consistent w  lighting. Eac uated sales w ry. This  may have led  d  129,707 39,583 9,446 9 178,745   eat    ith  h  were  to  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 54 of 296   15  Avista sales data included CFL wattage, units sold, and bulb type. Savings for each bulb type is analyzed  separately. For 3‐way bulbs, the middle wattage was used for the analysis. The average weighted CFL  wattage sold in PY 2013, for standard twist, specialty, LED bulb, and LED fixture, was 16.15 watts, 14.23  watts, 10.19 watts, and 13.94 watts, respectively.   Delta Watt Multiplier  Cadmus followed the lumens equivalence method as laid out in the Uniform Methods Project (UMP) to  evaluate the baseline wattage and the DWM for each wattage and type of bulb sold. The evaluation  team matched the reported SKU numbers against the ENERGY STAR lighting database1 to determine the  lumens associated with each bulb. Once the lumens value was determined, the baseline wattage was  evaluated in accordance with the guidelines outlined in the Energy Independence and Security Act (EISA)  of 2007.   In PY 2013, Cadmus was able to match 83.1% of the roughly 600,000 bulbs incented through the  program. For the remaining 16.9% of bulbs, we determined the lumens value with an interpolation  equation that is based on the relationship between CFL wattage and lumen output from the ENERGY  STAR lighting database:   DDD DDDDDD DD DD 2013 70.952 DDD DDDDDDD 86.11   Figure 3 and Figure 4 show a comparison of the lumens determined by lookup to the lumens determined  by regression model, along with the PY 2013 sales data for the given wattage. The figures shows that the  regression equation used in PY 2013 is a good estimate of the lumens output for a given measure  wattage, especially considering the low percentage of total program sales. Cadmus accepted the lumen  output estimated by the regression for both types of bulbs due to the low percentage of sales volume  used in the regression analysis.                                                               1  http://www.energystar.gov/ia/products/prod_lists/compact_fluorescent_light_bulbs_prod_list.xls  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 55 of 296   16  Figure 3. Results of PY 2013 Lumens Determination, Standard Twist CFLs      Figure 4. Results of PY 2013 Lumens Determination, Specialty CFLs      Cadmus then determined the baseline wattage for each bulb based on the lumen output and whether  the bulb includes a reflector (which is not impacted by EISA).2 Table 9 and Table 10 show the schedules  Cadmus used to determine the baseline wattage, for reflector and non‐reflector bulbs, respectively. We  then calculated the DWM for each bulb using the baseline wattage and purchased CFL wattage.                                                               2  Federal exemptions for some reflector‐style bulbs were set to expire in late 2012. In order to maintain  consistency between this evaluation and the PY 2012 evaluation, Cadmus assumed that the exemptions  expired on January 1, 2014. These exemptions would have caused a 0.69% decrease in overall PY 2013 savings.  0% 6% 12% 18% 24% 30% 0 1,000 2,000 3,000 4,000 5,000 8 9 10 13 14 15 18 19 20 21 22 23 26 32 40 42 55 68 Pe r c e n t  of  Pr o g r a m  Sa l e s Lu m e n s CFL Wattage % of Sales, Lumens by Lookup % of Sales, Lumens by Regression Lumens by Lookup Lumens by Regression 0% 3% 6% 9% 12% 15% 0 500 1,000 1,500 2,000 2,500 7 9 11 12 13 14 15 16 18 19 20 21 22 23 24 25 26 Pe r c e n t  of  Pr o g r a m  Sa l e s Lu m e n s CFL Wattage % of Sales, Lumens by Lookup % of Sales, Lumens by Regression Lumens by Lookup Lumens by Regression Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 56 of 296   17  Table 9. 2013 Baseline Wattage Based on Measure Lumens, Non‐Reflector Bulbs  Lumens Range Incandescent  Baseline (W)  Average CFL  Wattage Bulbs Rebated Percentage of  Program Sales  0 ‐ 309 25 0.00 0 0.0% 310 ‐ 749 40 9.55 75,356 12.6% 750 ‐ 1,049 60 13.43 283,365 47.6% 1,050 ‐ 1,489 53 18.85 47,596 8.0% 1,490 ‐ 2,600 72 23.27 96,976 16.3% 2,601 ‐ 3,300 150 41.77 954 0.2% 3,301 ‐ 4,815 200 62.34 593 0.1%   Table 10. 2013 Baseline Wattage based on Measure Lumens, Reflector Bulbs  Lumens Range Incandescent  Baseline (W)  Average CFL  Wattage Bulbs Rebated Percentage of  Program Sales  0 ‐ 419 30 11.00 509 0.1% 420 ‐ 560 45 13.24 1,060 0.2% 561 ‐ 837 65 14.82 77,336 13.0% 838 ‐ 1,203 75 16.65 4,116 0.7% 1,204 ‐ 1,681 90 23.92 6,943 1.2% 1,682 ‐ 2,339 120 24.26 1,013 0.2% 2,340 ‐ 3,075 175 0.00 0 0.0%   Hours‐of‐Use  Cadmus estimated standard twist CFL HOU for residential installations using Avista’s survey of room  types and a multistate modeling approach, built on light logger data collected from five states: Missouri,  Michigan, Ohio, Maine, and Maryland.3 A regression statistical model calculated the average HOU, using  combined multistate, multiyear data. Cadmus used the multistate model’s estimate of HOU by room  type, weighted based on Avista’s survey results to determine an overall average HOU of 2.38.  Though the Simple Steps, Smart Savings™ program could introduce bulbs into residential and  commercial applications, an all‐residential application presented the more conservative assumption. As  compelling evidence did not exist to assume a proportion of commercial sales, Cadmus exclusively used  residential assumptions in this analysis.  Waste Heat Factor  The WHF is used to account for the change in annual HVAC energy, either lost or gained, due to a  reduction in facility lighting energy. Cadmus based the WHF on SEEM building models, developed by the                                                               3  The Cadmus Group, Inc. 2010 Evaluation, Measurement, and Verification Report. Prepared for Dayton Power  and Light. March 15, 2011.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 57 of 296   18  Regional Technical Forum (RTF). These SEEM building models estimate the change in HVAC equipment  energy use resulting from a change in lighting technology (e.g., from incandescent lamps to CFLs). In  general, the models account for the interaction using load shape profiles of the HVAC and lighting  equipment, based on dwelling occupancy.  The RTF uses an inherently conservative method, as it assumes a closed shell (i.e., all interior lamps),  including ceiling recessed cans contained in a closed system. Thus, heat produced by the bulbs enters  the building. In reality, waste heat could transfer out of the conditioned space.  Cadmus based the calculation on Avista’s share of electric heating equipment,4 along with its associated  efficiencies and surveys of interior and exterior distributions, producing a WHF of 89.8%.5   In‐Service Rate  Cadmus used the same CFL ISR accepted and approved by the RTF of 74.48%.6 This a storage rate of 24%  and a removal rate of 2%. The Council’s method to determining ISR is inherently conservative, because it  assumes that the remaining 24% of bulbs in storage never provide energy savings. However, research  has revealed that almost all program bulbs are installed within three years of purchase. Cadmus used  the same LED ISR accepted and approved by the RTF of 100%.7  Results and Findings  Overall Program Savings  Avista’s total reported and evaluated savings for PY 2013 are shown in Table 11.                                                                4  Avista equipment‐type saturations derived from a 2011 participant survey for the Geographic CFL Giveaway  Program.   5  The default RTF WHF is 86.4%.  6  See: http://rtf.nwcouncil.org/measures/measure.asp?id=142.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 58 of 296   19  Table 11. Simple Steps, Smart Savings PY 2013 Reported and Evaluated Total Savings  2013  Reported Savings Evaluated Savings  Bulbs  Purchased  Program  Savings  (kWh)  Savings Per  Bulb (kWh)  Bulbs  Purchased  Program  Savings  (kWh)  Savings Per  Bulb (kWh)  Twist 128,960 3,095,050 24.0 129,707 3,437,438 26.5 Specialty 35,652 588,258 16.5 39,583 1,022,349 25.8 LED Bulb 9,446 196,366 20.8 9,446 273,572 29.0 LED Fixture 8.7 209 24.0 8.7 240 27.6 Total 174,068 3,879,883 22.3 178,745 4,733,600 26.5 Realization Rate 103%122% 119% Totals may differ from the sum of values due to rounding.   Showerheads  Though primarily a lighting program, Simple Steps, Smart Savings also incentivized low‐flow, energy‐ saving shower heads in PY 2013. The evaluation assumes that 52.1% of the units purchased were  installed in homes with an electric water heater and 47.9% of the units were installed in homes with a  gas water heater. This assumption is based on the responses of almost 400 of Avista’s residential  customers in Idaho to Cadmus’ general population survey. The program sold showerheads with flow  rates ranging from 1.5 gallons per minute (gpm) to 2.0 gpm. The unit energy savings for each flow rate  sold are based on the net savings values currently approved by the RTF8 for showerheads purchased  through a “Retail” program and installed in “Any Shower” in the home. Evaluated savings follow the RTF  methodology and include the electricity savings due to reduced water and sewer requirements for all  units purchased through the program. The assumptions used and unit energy savings (UES) calculated  for this evaluation are shown in Table 12.                                                               8  http://rtf.nwcouncil.org/measures/measure.asp?id=126  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 59 of 296   20  Table 12. Showerhead Assumptions  Evaluated Showerhead Savings – Idaho  Units Sold  2013 Showerheads Sold 212  Survey Results, Fuel Distribution Percent Gas DHW 47.9%  Percent Electric DHW 52.1%  Water Heater Savings –Fuel Specific UES 2013 Electric Water Heater Savings (kWh)139.2  2013 Gas Water Heater Savings (therms)6.2  Water & Sewer Savings ‐All Units Sold UES 2013 Water & Sewer Savings (kWh)6.2    The total savings for these units are shown in Table 13. The Electric Savings per Unit Purchased shown in  the table apply to all units purchased through the program as it accounts for the saturation or electric  and gas equipment as well as the water and sewer savings.  Table 13. Simple Steps, Smart Savings, 2013 Showerhead Savings  2013 Idaho Showerhead Savings Reported Totals Evaluated Totals Realization Rates  Units Purchased 212 212 100% Program Savings (kWh) 12,344 16,706 135% Electric Savings Per Unit Purchased (kWh) 58.2 78.8 135%   1.3.3. Second Refrigerator and Freezer Recycling  Summary of Program Participation  Cadmus reviewed the participant database, maintained by JACO, the program implementer, to test the  reliability of program data. As shown in Table 14, the program recycled 348 units during PY 2013, a slight  increase relative to PY 2012. Some participants recycled more than one appliance through the program.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 60 of 296   As shown PY 2013 t applianc years. Th   As shown PY 2012.  Y 2010  2011  2012  2013  Total   in Figure 5, s han in previ  recycling pr  proportion   in Figure 6, c Table 1 ar  Re Re To Re Re To Re Re To Re Re To Re Re To side‐by‐side r ous years. Inc grams. The p of single doo Figure 5. R chest freezer 4. Idaho Prog Meas cycled Refrige cycled Freeze tal  cycled Refrige cycled Freeze tal  cycled Refrige cycled Freeze tal  cycled Refrige cycled Freeze tal  cycled Refrige cycled Freeze tal  refrigerators m reasing quan roportion o r units decre Refrigerator C s made up a l 21  ram Particip re  rator ator ator ator ator ade up a la ities of side‐ f bottom fre sed slightly s Configuratio arger propor ation by Mea Par rger percent by‐side refri zer units wa ince PY 201 ns by Progra tion of total p sure  ticipation  1 1 age of progra erators is ty  unchanged f 2.   m Year  participation  317  75  392  412  121  533  257  70  327  275  73  348  ,261  339  ,600  m participati ical of matu rom previou   in PY 2013 t   on in  ring  s  han in  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 61 of 296   In 2013, r freezers a Determi Cadmus d and freez compose evaluatio applianc UMP an Recent g evaluatio “strength consisten The UMP  enlisted s Refrigera the UMP                     9  U.S. D http:/ savin ecycled refri veraged 35 y ning Avera developed a m ers. We esti  of over 600 s conducte  ages, sizes, c d RT  Proto uidelines dev  methodolo en the credi cy and trans identifies se et of subject  tor recycling w process and t                         epartment of  /energy.gov/e s/about‐unifo Figure 6 gerators aver ears old, wit ge Annual G multivariate r ated the m  appliances (  between 20 onfiguration cols  eloped by th y for PY 201 ility of ener arency of h en common  matter expe as one of t o serve as t                     Energy. About  ere/about‐us/ rm‐methods.  6. Freezer Co aged 28 yea  18.6 cubic f ross Saving egression m del coefficie hich we m 09 and 2012 s, usage sce  U.S. Depart 2 and PY 20 y savings de w energy sa residential a ts who draft e seven ide e lead autho the Unifo m M uniform‐meth 22  nfigurations b rs old, with 1 eet of intern s  odel to estim ts using an a etered as par . These eval arios (prima ent of Ener 3. In 2011, D erminations  vings are det d commerci d evaluatio tified measu r for the refr Methods Proje ods‐project‐d by Program Y 7.9 cubic feet al capacity.  ate the gross  aggregated in t of five Calif ations refle y or second y (DOE) inf OE launched  by improvin rmined.”9   al DSM mea  protocols f res. The DOE  igerator recy ct. Accessed A termining‐en Year   of internal c savings of re  situ meterin rnia, Wiscon ted a wide d ry), and clim rmed Cadm the UMP, in  EM&V, incr ures, reporti r each meas recruited Ca ling protoco ril 24, 2014. A ergy‐efficienc   apacity. Rec ired refriger g dataset  sin, and Mic stribution of  ate conditio s’ impact  tending to  easing the  ng results fr re category. dmus to ma l.   Available onlin ‐program‐   ycled  ators  higan  ns.  om an    nage  e:  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 62 of 296   23  Through a collaborative process that included reviews by a technical advisory group and a steering  committee, as well as a public review and response period, the UMP resulted in a set of protocols  capturing the collective consensus of the evaluation community. Each protocol establishes broadly  accepted best practices for evaluating key measures in that category, including methods for identifying  and explaining key parameters, data sources, and gross‐ and net‐related algorithms.  This evaluation of the Avista’s PY 2013 ARP in Idaho followed the complete UMP methodology outlined  in the refrigerator recycling protocol. The DOE website10 provides more information about the UMP  Refrigerator Regression Model.  Refrigerator Regression Model  Table 15 shows the variables we used to estimate refrigerators’ annual energy consumption, along with  the estimated parameters.  Table 15. Refrigerator UEC Regression Model Estimates   (Dependent Variable = Average Daily kWh, R2 = 0.30)  Independent Variables Coefficient p‐Value  Intercept 0.805 0.166 Age (years) 0.021 0.152 Dummy: Manufactured Pre‐1990 1.036 <.0001 Size (cubic feet) 0.059 0.044 Dummy: Single Door  ‐1.751 <.0001 Dummy: Side‐by‐Side 1.120 <.0001 Dummy: Primary 0.560 0.008 Interaction: Unconditioned Space x HDDs  ‐0.040 0.001 Interaction: Unconditioned Space x CDDs 0.026 0.188   The results of our analysis indicated the following:  • Older refrigerators experienced higher consumption due to year‐on‐year degradation.  • Refrigerators manufactured before the 1990 National Appliance Energy Conservation Act  (NAECA) standard consumed more energy.  • Larger refrigerators consumed more energy.  • Single‐door units consumed less energy, as these units typically did not have full freezers.  • Side‐by‐side refrigerators experienced higher consumption due to greater exposure to outside  air when opened and due to the through‐door features common in these units.  • Primary appliances experienced higher consumption due to increased usage.                                                                10  U.S. Department of Energy. “Uniform Methods Project for Determining Energy Efficiency Program Savings.”  Accessed April 24, 2014. http://energy.gov/eere/about‐us/initiatives‐and‐projects/uniform‐methods‐project‐ determining‐energy‐efficiency‐program‐savings.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 63 of 296   24  • At higher temperatures, refrigerators in unconditioned spaces consumed more energy.  • At colder temperatures, refrigerators in unconditioned spaces consumed less energy.  Freezer Regression Model  Table 16 shows the freezer model details.  Table 16. Freezer UEC Regression Model Estimates   (Dependent Variable = Average Daily kWh, R‐square = 0.38)  Independent Variables Coefficient p‐Value  Intercept  ‐0.955 0.237 Age (years) 0.045 0.001 Dummy: Manufactured Pre‐1990 0.543 0.108 Size (cubic feet) 0.120 0.002 Dummy: Chest Freezer 0.298 0.292 Dummy: Primary  ‐0.031 <.0001 Interaction: Unconditioned Space x HDDs 0.082 0.028 Interaction: Unconditioned Space x CDDs  ‐0.955 0.237   The results of our analysis indicated the following:  • Older freezers experienced higher consumption due to year‐on‐year degradation.  • Freezers manufactured before the 1990 NAECA standard consumed more energy.  • Larger freezers consumed more energy.  • Chest freezers experienced higher consumption.  • At higher temperatures, freezers in unconditioned spaces consumed more energy.  • At colder temperatures, freezers in unconditioned spaces consumed less energy.  Extrapolation  After estimating the final regression models, Cadmus analyzed the corresponding characteristics (the  independent variables) for participating appliances (as captured in the JACO database). Table 17  summarizes program averages for each independent variable.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 64 of 296   25  As an example, using values from Table 16 and Table 17, Cadmus calculated the estimated annual UEC  for PY 2013 freezers as:  2013 Freezer UEC 365.25 DDDD O0.955 0.045 O34.58 DDDDD DDDO 0.543 O79% DDDDD DDDDDDDDDDDD DDD 1990O 0.120 O18.56 DD.HO 0.298 O36% DDDDD DDDD DDD DDDDD DDDDDDDDO 0.082 O0.43 DDDDDDDDDDDDD DDDDO 0.031 O9.47 DDDDDDDDDDDDD DDDDOO 1,139 DDD/year11 Table 17. PY 2013 Participant Mean Explanatory Variables  Appliance Independent Variables PY 2013 Participant Population  Mean Value  Refrigerators  Age (years) 28.33 Dummy: Manufactured Pre‐1990 0.72 Size (cubic feet) 17.85 Dummy: Single Door 0.01 Dummy: Side‐by‐Side 0.21 Dummy: Primary 0.40 Interaction: Unconditioned Space x Heating Degree Days 6.66 Interaction: Unconditioned Space x Cooling Degree Days 0.31 Freezers  Age (years) 33.58 Dummy: Manufactured Pre‐1990 0.79 Size (cubic feet) 18.56 Dummy: Chest Freezer 0.36 Interaction: Unconditioned Space x Heating Degree Days 9.47 Interaction: Unconditioned Space x Cooling Degree Days 0.43   Figure 7 compares distributions of estimated UEC values for refrigerators and freezers.                                                               11  The UEC shown is higher than that calculated from the coefficients and means shown in the UEC equation,  which are rounded. Cadmus used unrounded coefficients and means for calculating the evaluated UEC.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 65 of 296   Table 18 p freezers r arrive at g Appl Refrigerat Freezers     Table 19 p the U.S. A Figure 7 presents the  ecycled by A ross per‐uni iance  ors   presents the  Avista’s UECs  . PY 2013 Di estimated, p ista in PY 20  saving esti Table 18. Es Ex Post A PY 2013 UEC  are similar t stribution of E er‐unit, aver 13. After the  mates for par timate of Per‐ nual UEC (k results for A  the utilities w 26  Estimated A age annual e table, we de icipant refri ‐Unit Annual h/year)  1,238 1,139 ista, compa e benchma nnual UECs b nergy consu scribe how w gerators and f  Energy Con Relativ red to other u rked.  y Appliance T mption for ref e adjusted t reezers.  sumption  e Precision(9 utilities locat Type    rigerators an ese estimat 0% confiden ed in Canada    d  es to  ce)  8% 17% and  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 66 of 296   27  Table 19. Benchmarking: Average UEC Values  Utility Years  Implemented  Average UEC (kWh/Year)  Refrigerator Freezer  Avista (ID, PY 2013) 8 1,238 1,139 Avista (WA, PY 2012 & PY 2013) 8 1,225 1,098 Avista (ID, PY 2012) 7 1,199 1,117 Avista (WA & ID, PY 2011) 6 1,147 1,074 Avista (WA & ID, PY 2010) 5 1,158 1,073 Ontario Power Authority (2012) 6 1,153 1,270 Ontario Power Authority (2011) 5 1,240 1,172 Pacific Power (WA, 2011‐2012) 8 1,239 1,087 Rocky Mountain Power (ID, 2011‐2012) 8 1,217 1,111 Rocky Mountain Power (UT, 2011‐2012) 10 1,323 1,082 Rocky Mountain Power (WY, 2011‐2012) 4 1,256 1,098   Part­Use   Part‐use is as an adjustment factor specific to appliance recycling, which is used to convert the UEC into  average per‐unit gross savings value. The UEC does not equal gross savings value, due to the following:   • The UEC model yields an estimate of annual consumption.   • Not all recycled refrigerators would have operated year‐round if they had not been  decommissioned through the program.   The first time Cadmus used the UMP part‐use methodology to evaluate an Avista program was in Idaho  for PY 2012. Cadmus applied this methodology again for the PY 2013 Idaho evaluation.  While the UMP part‐use methodology uses information from surveyed customers regarding pre‐ program usage patterns, the final part‐use estimate reflects the way appliances would likely be operated  if they had not been recycled (not how they were previously operated). For example, a primary  refrigerator operated year‐round could become a secondary appliance and be operated part‐time.   The UMP methodology Cadmus employed for the PY 2013 evaluation accounts for potential shifts in  usage types. Specifically, we calculated part‐use using a weighted average of the following, prospective  part‐use categories and factors:  • Appliances that would have run full‐time (part‐use = 1.0).  • Appliances that would not have run at all (part‐use = 0.0).  • Appliances that would have operated for a portion of the year (part‐use between 0.0 and 1.0).   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 67 of 296   28  Using information gathered through the participant surveys,12 Cadmus used the multistep process  outlined in the text below to determine part‐use, as outlined in the UMP.   First, we used the survey information to determine if recycled refrigerators were primary or secondary  units (considering all stand‐alone freezers as secondary units).  We asked participants who recycled a secondary refrigerator or freezer if the unit was unplugged,  operated year‐round, or operated for a portion of the preceding year (assuming all primary units  operated year‐round).   Cadmus asked participants who indicated that their secondary refrigerator or freezer operated for only a  portion of the preceding year to estimate how many months during that time their appliance was  plugged in. This subset of participants estimated 5.88 and 3.24 months for secondary refrigerators and  freezers, respectively. Dividing both values by 12 provided the annual part‐use factors of 0.49 for all  secondary refrigerators and 0.27 for all freezers operated for only a portion of the year (Table 20).   Table 20. Historical Part‐Use Factors by Category  Usage Type and  Part‐Use Category  Refrigerators Freezers  Percent of  Recycled  Units  Part‐ Use  Factor  Per‐UES  (kWh/Year)  Percent of  Recycled  Units  Part‐ Use  Factor  Per‐UES  (kWh/Year)  Secondary Units Only n=29    Not in Use 8% 0.00 ‐ Used Part Time 13% 0.49 610 Used Full Time 79% 1.00 1,238 Weighted Average 100% 0.86 1,060 All Units (Primary  and Secondary) n=48 n=15  Not in Use 4% 0.00 ‐12%0.00  ‐ Used Part Time 8% 0.49 610 12%0.27 311 Used Full Time 88% 1.00 1,238 75%1.00 1,139 Weighted Average 100% 0.91 1,132 100%0.78 894   Cadmus then asked participants how they would likely have operated their appliance if they had not  recycled it through the program. For example, if surveyed participants indicated they would have kept a  primary refrigerator independent of the program, we asked if they would have continued to use the  appliance as their primary refrigerator or would have relocated it and used as a secondary refrigerator.  We did not ask similar questions of participants who indicated they would have discarded their                                                               12  Due to the relatively small number of Idaho participant survey respondents, Cadmus combined the participant  survey data from the Washington and Idaho PY 2013 surveys for the NTG analysis.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 68 of 296   29  appliance independent of the program, as the future usage of their appliance would be determined by  another customer.  Combining the historically based, part‐use factors shown in Table 20 with participants’ self‐reported  action had the program not been available resulted in the distribution of likely future usage scenarios  and corresponding part‐use estimates. Table 21 shows the weighted average of these future scenarios,  revealing the program part‐use factor for refrigerators (0.89) and freezers (0.78).13   Table 21. Part‐Use Factors by Appliance Type  Use Prior to  Recycling  Likely Use  Independent of  Recycling  Refrigerator Freezer  Part‐Use  Factor  Percent of  Participants  Part‐Use  Factor  Percent of  Participants  Primary  Kept (as primary unit) 1.00 7%   Kept (as secondary unit)0.86 7% Discarded  0.91 20% Secondary Kept  0.86 38%0.78 56% Discarded  0.91 29%0.78 44% Overall 0.89 100%0.78 100%   Table 22 presents the part‐use factors compared with other utilities located in Canada and the U.S.  Cadmus found that Avista Idaho has a similar part‐use factor for refrigerators, and a slightly lower part‐ use factor for freezers, than other utilities. The refrigerator part‐use factor for PY 2013 is lower than for  PY 2012, but the freezer part‐use factor is higher.                                                               13  As the future usage type of discarded refrigerators cannot be known, Cadmus applied the weighted part‐use  average of all units (0.89) to all refrigerators that would have been discarded independent of the program.  This approach allows for discarded appliances to be used as primary or secondary units in a would‐be  recipient’s home.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 69 of 296   30  Table 22. Benchmarking: Part‐Use Factors by Appliance Type  Utility Years  Implemented  Part‐Use Factors  Refrigerator Freezer  Avista (ID, PY 2013) 8 0.89 0.78 Avista (ID, PY 2012) 7 0.95 0.74 Avista (WA, PY 2012 & PY 2013) 8 0.89 0.82 Avista (WA & ID, PY 2010 & PY 2011) 6 0.94 0.82 Ameren Illinois 5 0.88 0.88 Pacific Gas & Electric (2012) 10 0.94  Pacific Power (WA, 2011‐2012) 8 0.93 0.90 Rocky Mountain Power (ID, 2011‐2012) 8 0.84 0.93 Rocky Mountain Power (UT, 2011‐2012) 10 0.93 0.90 Southern California Edison (2012) 12 0.94    Net­to­Gross  Cadmus used the following formula to estimate net savings for recycled refrigerators:  DDD DDDDDDD DDDDD DDDDDDD DDDDDDDDDDDDD DDD DDDDDDDDD DDDDDD DDDDDDD DDDDDDD DDDDDDDDDDD  Gross savings are the evaluated in situ UEC for the recycled unit, adjusted for part‐use. Freeridership and  secondary market impacts are program savings that would have occurred in the program’s absence.  Induced replacement is the average, additional energy consumed by replacement units purchased due  to the program.  Applying the UMP protocol introduced an additional parameter related to net savings—secondary  market impacts—which required Cadmus to use a decision‐tree approach to calculate and present net  program savings. This decision tree—populated by the responses of surveyed participants—presented  savings under all possible scenarios of what could happen to the discarded equipment. Cadmus used a  weighted average of these scenarios to calculate net savings attributable to the program. The text below  includes specific portions of the decision tree to highlight specific aspects of the net savings analysis.   Freeridership  To determine freeridership, Cadmus first asked participants if they considered discarding the  participating appliance prior to learning about the program. If the participant did not indicate a previous  consideration to dispose of the appliance, Cadmus categorized them as a non‐freerider and excluded  them from the subsequent freeridership analysis.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 70 of 296   31  Next, Cadmus asked all remaining participants (i.e., those who had considered discarding their existing  appliance before learning about the program) a series of questions to determine the distribution of  participating units likely to have been kept versus those likely to have been discarded absent the  program. Three scenarios independent of program intervention could have occurred:  • The unit would be discarded and transferred to someone else.  • The unit would be discarded and destroyed.  • The unit would be kept in the home.  To determine the percentage of participants in each of the three scenarios, Cadmus asked surveyed  participants about the likely fate of their recycled appliance had it not been decommissioned through  the program. Cadmus categorized their responses into the following options:  • Kept the appliance.  • Sold the appliance to a private party (either an acquaintance or through a posted  advertisement).   • Sold or gave the appliance to a used appliance dealer.  • Gave the appliance to a private party, such as a friend or neighbor.  • Gave the appliance to a charity organization, such as Goodwill Industries or a church.  • Had the appliance removed by the dealer who provided the new or replacement unit.  • Hauled the appliance to a landfill or recycling center, or had someone else pick it up for junking  or dumping.  Cadmus also asked surveyed participants if they had considered getting rid of their old appliance before  hearing about the program. The distribution of their responses to this question are summarized in Table  23.   Table 23. Distribution of Participants’ Pre‐Program Disposal Intentions  Had Considered Disposing of  Recycled Appliance Prior to Hearing  About Program  Indicative of  Freeridership  Refrigerators   (n=48)  Freezers   (n=16)  Yes Varies by Discard Method 85% 73% No No 15% 27% Total 100% 100%   Once Cadmus determined the final assessments of participants’ actions independent of the Second  Refrigerator and Freezer Recycling Program, we calculated the percentage of refrigerators and freezers  that would have been kept or discarded (Table 24).  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 71 of 296   32  Table 24. Final Distribution of Kept and Discarded Appliance  Stated Action Absent Program Indicative of  Freeridership  Refrigerators   (n=46)  Freezers   (n=15)  Kept No 18% 37% Discarded Varies by Discard Method 82% 63% Total 100% 100%   Cadmus benchmarked these values against Avista Idaho’s PY 2012 evaluation and those of other  appliance recycling programs in Idaho, Utah, Washington, and Wyoming, as shown in Table 25. Avista’s  PY 2013 result for Idaho is most similar to Rocky Mountain Power’s Wyoming result, though the  percentage of freezers likely to be kept is higher than any of the benchmarked programs. Within the  Avista Idaho program, the percentage of refrigerators likely to have been kept decreased relative to PY  2012, though the percentage for freezers increased substantially.  Table 25. Benchmarking Kept Appliances  Utility Years  Implemented  Percent Likely to Have Been Kept  Independent of the Program  Refrigerator Freezer  Avista (ID, PY 2013) 8 18% 37% Avista (ID, PY 2012) 7 25% 17% Avista (WA, PY 2012 & PY 2013) 8 31% 36% Pacific Power (WA, 2011‐2012) 8 22% 22% Rocky Mountain Power (ID, 2011‐2012) 8 32% 29% Rocky Mountain Power (UT, 2011‐2012) 10 20% 24% Rocky Mountain Power (WY, 2011‐2012) 4 16% 27%   Secondary Market Impacts  If, absent the program, a participant would have directly or indirectly (through a market actor)  transferred the program‐recycled unit to another Avista customer, Cadmus determined what actions the  would‐be acquirer might have taken with that unit.   Some would‐be acquirers would find another unit; others would not. This reflects that some acquirers  would be in the market for a refrigerator (and would acquire another unit), while others would not (and  would have taken the unit opportunistically). Absent program‐specific information, it is difficult to  quantify changes in the total number of refrigerators and freezers in use (overall and specific to used  appliances) before and after implementing the program. Without this information, the UMP  recommends assuming that one‐half of the would‐be acquirers would obtain an alternate unit. Without  information to the contrary, Cadmus applied the UMP recommendation to this evaluation.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 72 of 296   33  Next, Cadmus determined what percentage of the alternate units would likely be another used  appliance (similar to those recycled through the program) versus a new, standard‐efficiency unit  (presuming fewer used appliances remained available due to program activity).14   As discussed, estimating this distribution definitively proves difficult. The UMP recommends taking a  midpoint approach when primary research is unavailable: evaluators should assume that one‐half of the  would‐be acquirers would obtain a similar used appliance, and one‐half would acquire a new, standard‐ efficiency unit.   Cadmus used the ENERGY STAR website15 to determine the energy consumption of new, standard‐ efficiency appliances. Specifically, Cadmus averaged the reported energy consumption of new, standard‐ efficiency appliances of comparable sizes and configurations as the program units.   Figure 8 details Cadmus’ methodology for assessing the program impact on the secondary refrigerator  market and for applying the recommended midpoint assumptions when primary data were unavailable.  As shown, accounting for market effects resulted in three savings scenarios:   • Full per‐unit gross savings;  • No savings; and   • Partial savings (i.e., the difference in energy consumption between the program unit and the  new, standard‐efficiency appliance that was acquired instead).  Figure 8. Secondary Market Impacts—Refrigerators      Integration of Freeridership and Secondary Market Impacts  After estimating the parameters of the freeridership and secondary market impacts, Cadmus used the  UMP decision tree to calculate the average, per‐unit program savings, net of their combined effect.  Figure 9 shows how Cadmus integrated these values into an estimate of savings, net of freeridership and  secondary market impacts. Cadmus calculated the weighted average freeridership and secondary                                                               14  The would‐be acquirers could also select a new ENERGY STAR unit. However, Cadmus assumed that most  customers in the market for a used appliance would upgrade to the next lowest price point (a standard‐ efficiency unit).  15  http://www.energystar.gov/index.cfm?fuseaction=refrig.calculator.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 73 of 296   34  market impacts (778 kWh per unit) as the sum product of the program proportions and the per‐unit  energy consumption with the program for each scenario.  Figure 9. Savings Net of Freeridership and Secondary Market Impacts—Refrigerators      Induced Replacement   The UMP states that evaluators must account for the energy consumption of replacement units only  when the program induced that replacement (i.e., when the participant would not have purchased the  replacement refrigerator without the recycling program).   In the case of non‐induced replacements, the energy consumption of the replacement appliance does  not prove germane to the savings analysis, as the appliance would have been purchased or acquired  regardless of the program. The acquisition of another appliance in conjunction with participation in the  program does not necessarily indicate induced replacement. Again, this is consistent with the methods  outlined in the UMP.  Cadmus used the results of the participant surveys to determine which replacement refrigerators and  freezers program participants acquired due to the program. Survey results indicated that the program  reduced the total number of used appliances operating within Avista’s Idaho service territory, and that  the program raised the average efficiency of the active appliance stock.   Cadmus then used participant survey results to estimate the proportion of replacements induced by the  customer’s participation in the program. Specifically, Cadmus asked each participant that indicated they  replaced the participating appliance: “Would you have purchased the replacement appliance without  the $30 incentive you received for recycling the old one?”   As a $30 incentive will likely not provide sufficient motivation for most participants to purchase an  otherwise unplanned for replacement unit (which can cost $500 to $2,000), Cadmus asked a follow‐up  question of participants who responded “No.” Intended to confirm the participant’s assertion that only  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 74 of 296   35  the program caused them to replace their appliance, the question was: “Just to confirm: you would not  have replaced your old refrigerator/freezer without the Avista incentive for recycling, is that correct?”  To further increase the reliability of these self‐reported actions in the induced replacement analysis, we  also considered whether the refrigerator was the primary unit and the participant’s stated intentions in  the program’s absence.   For example, if a participant would have discarded their primary refrigerator independent of the  program, the replacement could not be program induced (since it is extremely unlikely a participant  would live without a primary refrigerator). However, for all other usage types and stated intention  combinations, induced replacement was a viable response.   As expected, results indicated that the program only induced a portion of the total replacements: the  program induced 8% of all refrigerator participants and 8% of freezer participants to acquire a  replacement unit, as shown in Table 26.   Table 26. Induced Replacement Rates  Appliance Induced Replacement Rates  Refrigerator 8%  Freezer 8%    As shown in Table 27, Avista’s induced replacement was higher than both the comparison utilities and  higher than Avista’s previous evaluations, and was most similar to Rocky Mountain Power’s 2011‐2012  results in Idaho.  Table 27. Benchmarking: Induced Replacement  Utility Years  Implemented  Induced Replacement  Refrigerators Freezers  Avista (ID, PY 2013) 8 8% 8% Avista (ID, PY 2012) 7 0% 0% Avista (WA & ID, PY 2010 & PY 2011) 6 4% 4% Avista (WA, PY 2012 & PY 2013) 8 7% 11% Pacific Power (WA, 2011‐2012) 8 4% 5% Rocky Mountain Power (ID, 2011‐2012) 8 7% 7% Rocky Mountain Power (UT, 2011‐2012) 10 3% 4% Rocky Mountain Power (WY, 2011‐2012) 4 2% 5%   Figure 10 shows Cadmus’ calculated induced replacement within the decision tree. Cadmus calculated  the weighted average induced consumption per unit as the sum product of the program proportions and  the per‐unit energy consumption resulting from the program.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 75 of 296   Final NT As summ minus fre Applianc Refrigerat Freezer    Summar Using the  Refrigera Table 29) Me Refrigerat Freezer R Total    As shown result wa would ha to other p G  arized in Tabl eridership, s e Gross P Unit Sa or 1 y of Impact Fi above per‐u or and Free   Table 29. Id sure  or Recycling  ecycling   in Table 30, A s driven dow e been disc rograms. Th Figur e 28, Cadmu condary ma T Per‐ vings  Freeri S Mar 1,101  894  ndings  nit values, C er Recycling  aho PY 2013 S Evaluat Participa Avista’s NTG  nward from t arded absent  e NTG for fre e 10. Induced  s determine ket impacts,  Table 28. PY 2 dership and  econdary  ket Impacts  778 400 dmus calcul Program in I Second Refri ed  tion  Ev S 275 73 348 for refrigera he previous e the program zers, howe 36  Replaceme d final net sa and induced  2013 NTG Ra Induce Replacem ated the total aho as 117, gerator and F aluated Gro vings (kWh) 302,9 65,2 368,1 tors is less th valuation, p , as well as t er, is similar t nt Refrigerat vings as gross  replacemen tios (kWh)  d  ent  Ind Addi Sa (Spil 33 36  program sa 99 kWh, aft Freezer Recy s    Evalu Savin 06 8 74 an all the be imarily due t o the mature  to the bench ors  savings and s t.   uced  tional  vings  lover)  N S 13  11  vings for the P er adjustmen cling Progra ted Net  gs (kWh)  83,456  34,243  117,699  nchmarked p o the ratio o nature of th marked prog pillover savi Net Per‐ Unit  Savings  N 303 469 Y 2013 Seco s (as shown i m Savings  Precision at  Confiden rograms. Thi  appliances t e program rel rams.       ngs,  NTG  28% 52% nd  in  90%  ce  32% 42% 26% s NTG  that  ative  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 76 of 296   37  Table 30 Benchmarking NTG Ratios  Utility Years  Implemented  NTG Ratio  Refrigerator Freezer  Avista (ID, PY 2013) 8 28% 52% Avista (ID, PY 2012) 7 46% 33% Avista (WA, PY 2012 & PY 2013) 8 41% 55% Avista(WA & ID, PY 2010 & PY 2011) 6 57% 56% Ontario Power Authority (2012) 6 47% 48% Ontario Power Authority (2011) 5 53% 53% Pacific Power (CA, 2009‐2010) 3 64% 67% Pacific Power (WA, 2011‐2012) 8 51% 51% Rocky Mountain Power (ID, 2011‐2012) 8 54% 48% Rocky Mountain Power (UT, 2011‐2012) 10 56% 56% Rocky Mountain Power (WY, 2011‐2012) 4 39% 51%   1.3.4. ENERGY STAR Products  Program Description  The ENERGY STAR Products Program includes the following measures:  • Clothes Washer (Electric and Gas)  • Freezer (Electric)  • Refrigerator (Electric)  Through the program, Avista offers direct financial incentives to motivate customers to use more  energy‐efficient appliances; this indirectly encourages market transformation by increasing the demand  for ENERGY STAR products. The program includes electric and gas measures, but Cadmus only considers  electric savings in this report.  Analysis  Energy savings credited to the ENERGY STAR Products Program had to meet the following criteria:  • Measures had to remain in place and be operating properly at the time of verification;  • Numbers of installed equipment pieces and their corresponding model numbers in the  applications had to match the database; and   • Units must have been ENERGY STAR‐qualified at the time of the program offering.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 77 of 296   38  Clothes Washers, Refrigerators, and Freezers  Energy‐saving calculations drew upon a 2009 Cadmus study,16 which metered more than 100 clothes  washers in California homes for three weeks—the largest in situ metering study on residential clothes  washers and dryers conducted in the last decade. Cadmus has updated the analysis since the 2012  Avista TRM was completed to improve the accuracy of the savings estimated.  Dryers produced the majority of energy consumption and savings, as high‐efficiency washing machines  removed more moisture from clothes, allowing for shorter drying times.  Determining adjusted gross savings required using the following, additional input assumptions:  • Based on recent independent evaluation surveys from the RBSA17 and on PY 2012 Avista  participant surveys, Cadmus estimated 262 washing cycles per year. We adjusted the UES values  accordingly, which is reflected in this measure’s realization rate.  • Cadmus used data from the California metering study to estimate consumption per wash and  dry cycle for the base and efficient equipment.  Results and Findings  Table 31 shows total reported and qualified counts, savings, and realization rates for electric ENERGY  STAR Products Program measures in Idaho.  Table 31. PY 2013 ENERGY STAR Products Program Results in Idaho  Program  Name  Reported  Measure  Count  Reported  Savings  (kWh)  Adjusted  Savings  (kWh)  Quali‐ fication  Rate  Verification  Rate  Adjusted  Gross  (kWh)  Realization  Rate  Electric  Clothes  Washer  160 74,240 21,479 100% 100% 21,479 29%  Electric  Freezer 7 294 326 100% 100% 326 111%  Electric  Refrigerator 110 4,840 7,207 100% 100% 7,207 149%  Program  Total 277 79,374 29,011 100% 100% 29,011 37%  Program Total savings may be different that the sum of the values shown due to rounding.                                                                   16  The Cadmus Group, Inc. “Do the Savings Come Out in the Wash? A Large Scale Study of In‐Situ Residential  Laundry Systems.” 2010. Available online:  http://www.aceee.org/files/proceedings/2010/data/papers/2223.pdf  17 Ecotope Inc. 2011 Residential Building Stock Assessment: Single‐Family Characteristics and Energy Use. Seattle,  WA: Northwest Energy Efficiency Alliance. 2012.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 78 of 296   39  The program achieved a 37% realization rate. Our review of program applications determined that 42%  of the applications with water heater fuel originally marked as “Natural Gas” had been processed as  “Electric.” Cadmus reviewed gas consumption data from the associated premises to determine if these  customers have electric service only or if they have both electric and natural gas service. The adjusted  savings for this measure accounts for the existence of gas hot water heaters for 42% of the units  rebated. These units still deliver electricity savings since the majority of homes are assumed to use  electric dryers.  1.3.5. Heating and Cooling Efficiency  Program Description  The Heating and Cooling Efficiency Program included the following electric equipment:  • Ductless Heat Pump (DHP)  • Air‐Source Heat Pumps (ASHP)  • Variable Speed Furnace Fan  Analysis  The PY 2010 and PY 2011 electric impact evaluation report18 documented the analysis Cadmus  performed to determine the change in energy consumption resulting from the installation of electric  heating and cooling measures. As that analysis continues to provide the best information on these  measures, Cadmus retained those results for PY 2013.   Results and Findings  Table 32 shows total tracked and qualified counts, savings, and realization rates for electric Heating and  Cooling Efficiency Program measures in Idaho. The program achieved a 94% realized adjusted gross  savings rate. The reduction in savings is due to differences between the values used to track savings for  the program and the savings shown in the 2012 Avista TRM.                                                               18  Cadmus. Avista 2010–2011 Multi‐Sector Electric Impact Evaluation Report. May 2012.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 79 of 296   40  Table 32. Heating and Cooling Efficiency Program Results*  Program  Name  Reported  Measure  Count  Reported  Savings  (kWh)  Adjusted  Savings  (kWh)  Qualification  Rate  Verification  Rate  Adjusted  Gross  (kWh)  Realization  Rate  Electric  ASHP 101 39,221 33,989 100% 100% 33,989 87%  Electric  DHP 7 5,628 1,292 100% 100% 1,292 23%  Electric  Variable  Speed  Motor  249 109,311 109,199 100% 100% 109,199 100%  Program  Total 357 154,160 144,480 100% 100% 144,480 94%  *Table values may not sum due to rounding.   1.3.6. Space and Water Conversions  Program Description  Through the Space and Water Conversions Program, Avista incents three measures for residential  electric customers who currently use electricity to heat the space and water in their homes, but have  the opportunity to use natural gas or switch to an alternative, more efficient technology that uses the  same fuel source. The equipment conversions during PY 2010 through PY 2013 included the following  measures:   • Electric Forced Air Furnace to Air Source Heat Pumps (ASHP)   • Electric Forced Air Furnace to Natural Gas Forced Air Furnace (NGF)  • Electric Water Heater to Natural Gas Water Heater (NGWH)  By offering conversion rebates, Avista seeks to achieve energy efficiency by changing the fuel mix used  by customers, which leads to savings from the lower‐priced fuel (in case of a conversion from an electric  furnace to a NGF and electric water heater to a NGWH) and to higher efficiency in overall cooling and  heating usage.  With the residential energy‐efficiency programs, Avista targets single‐family homes and units in  multifamily buildings. Avista customers started participating in the conversion rebates in PY 2010. Table  33 shows participation by conversion measure and year, in both Idaho and Washington. Avista phased  out conversion rebates in Idaho in PY 2013 for conversion from an electric water heater to a NGWH.  Table 33 shows the number of participant that installed any of the conversion measures, grouped by  year of installation.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 80 of 296   41  Table 33. Participation in Fuel Conversion Program by Year and State  Conversion  Measure  Application  Year  Participants in  Idaho  Participants in  Washington  Total Participants  by Year  Total  Participants*  ASHP  PY 2010 123 129 252  624 PY 2011 61 74 135  PY 2012 60 64 124  PY 2013 48 65 113  NGF  PY 2010 51 82 133  429 PY 2011 27 65 92  PY 2012 24 74 98  PY 2013 28 78 106  NGWH  PY 2010 22 95 117  362 PY 2011 16 79 95  PY 2012 15 75 90  PY 2013 5 55 60  * This column double‐counts participants who installed multiple measures.   Table 34. Number of Homes That Participated From PY 2010 Through PY 2013     Air‐Source  Heat Pump  Natural Gas  Furnace  Natural Gas  Water Heater  Multiple Conversion  Measures* All Homes  Total Participants 623 375 309 54 1,361 * This primarily consists of all customers who installed a NGF and NGWH.   Impact Evaluation Methodology  With the impact evaluation, Cadmus sought to estimate the change in energy use after installing these  conversion measures. More specifically, Cadmus’ evaluation of the Space and Water Conversions  Program consisted of the following three tasks:  1. Data collection, review, and preparation.  2. Billing analysis.  3. Energy‐savings estimations.  Data Collection, Review, and Preparation  To perform the billing and uplift analysis, Cadmus collected the data outlined below.  Monthly Customer Bills   Cadmus collected data about monthly gas and electricity bills between January 2010 and December  2013. The data included approximately 10 to 12 months of bills prior to the measures installations and  the same number of months of bills after the installations. These billing data included: account numbers,  energy use during the monthly billing cycle, and the last day of the billing cycle. Avista supplied these  data to Cadmus.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 81 of 296   42  Program Information   Cadmus obtained measures data from Avista. These data included: program tracking data for the PY  2011‐PY 2013 participants, account numbers and site IDs for linking to billing data, all the measures  installed, rebated amounts of therms and kWh saved, and application dates for the rebates.  Weather   Cadmus collected National Climatic Data Center daily average temperature data from 2010 through  January 2014 for eight weather stations: two in Idaho (Lewiston and Coeur D’Alene) and six in  Washington (Moses Lake Grant Co., Walla Walla, Spokane, Fairchild, Felts, and Pullman Moscow). These  were the stations nearest to all the program homes in the Avista territory.  Data Preparation  Cadmus prepared billing data for analysis using the following steps:  • Reformatting and merging the raw billing data for all customers.   • Separating the gas and electricity datasets and identifying customers that had dual usage  (electricity and gas) versus customers using only electricity.  • Renaming the market measure description, such as the following the same conversion measure  naming convention for all program years.  • Identifying homes that had multiple conversions and assigning them to a separate group.  • Specifying the pre‐ and post‐periods for each customer account:  ƒ The Customer‐Specific Measure Install Date: For each customer’s unique installation date,  this specification compares the year ending just before the install date with the year  beginning on the installation month.  ƒ The Full Year: In this specification, the install year is taken as the current year and the  energy consumption of the full year before the current year is compared to the full year  after the current year.  Table 35 shows an example of the specification of the pre‐ and post‐installation periods under the two  specifications. In this analysis, Cadmus has used a combination of the two specifications. While the  Customer‐ Specific Measure Install Date specification allows the data from a more compressed  timeframe to be used, it relies heavily on the exact installation date. The Full Year specification excludes  this uncertainty by assuming that the conversion installations occurred any time during the rebate  application year. The Full Year specification requires at least three years of data. In cases where this  requirement was not met, Cadmus used the Customer‐Specific Measure Install Date specification.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 82 of 296   43  Table 35. Example of Pre‐ and Post‐Installation Period Under the Two Specifications  Specification Installation  Date Pre‐Analysis Period Post‐Analysis Period  Customer Specific Measure Install Date   June 2010  June 2009 to May 2010 June 2010 to April 2011 Full Year  January 2009 to  December 2009  January 2011 to December  2011    Cadmus used daily average temperature and billing cycle information to estimate cooling degree days  (CDDs) and heating degree days (HDDs) for each home during the billing cycle. This required using a base  temperature of 65 degrees and billing cycle end dates to calculate HDDs and CDDs that exactly matched  days in the customer’s bill.  Based on the conversion group (electric furnace to NGF only, electric water heater to NGWH only, both  electric furnace to NGF and electric water heater to NGWH, and ASHP) and the fuel usage type (electric  only and dual fuel: electric and gas), Cadmus estimated six separate models. The next section outlines  the selected sample sizes in these six groups.   Data Attrition  Cadmus performed billing analysis on the population of program homes, except for homes from the  estimation sample that satisfied one or more of the following criteria:  • The home had fewer than 11 pre‐ or post‐program monthly energy bills.   The home did not pass PRISM modeling screens, which are based on the weather‐normalized pre‐ and  post‐installation annual usage. These are discussed in more detail in the   • Billing Analysis section.  Table 36 shows the total customer accounts that had a conversion measure and the final sample  Cadmus used in the PRISM and the regression analyses. Each row in the table indicates the accounts  remaining after attrition.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 83 of 296   44  Table 36. Sample Size Selection for PRISM Analysis  Accounts Remaining After  Attrition  Air‐Source Heat  Pump  Natural  Gas  Furnace  Natural  Gas Water  Heater  Multiple  Conversion  Measures  All  Conversion  Homes Electric  Only Dual All Dual Dual Dual  Total accounts with fuel conversion  measures 561 62 623 375 309 54 1,361  Low usage (less than 1,000 kWh) in  pre‐ or post‐installation period 550 62 612 346 301 50 1,309  Total accounts with sufficient  billing data for PRISM analysis 372 47 419 193 203 25 840  PRISM screens* 363 46 409 192 199 25 825 Accounts deleted due to vacancies,  seasonal usage, outliers, and  inoperable heating systems**  288 33 321 164 159 23 667  Percentage of accounts retained  for analysis 51% 53% 52% 44% 51% 43% 49%  * These PRISM screens led to Cadmus dropping accounts with: 1) negative heating or cooling slopes in the pre‐or the  post‐installation period and/or 2) usage that increased by more than 83% between the pre‐ and post‐installation period.   ** The numbers in bold are the final sample size Cadmus used for the per‐home savings estimation.    Billing Analysis  To estimate program electricity savings, Cadmus used two approaches: PRISM and fixed‐effects  regression. Cadmus first estimated the PRISM model to obtain weather‐normalized annual consumption  (NAC) and identify outliers. Cadmus then estimated a regression model to control for the installation of  other weatherization measures or efficient equipment. Details on the model specifications can be found  in Appendix A.  Program Impact Evaluation Findings  Per Home Savings Impacts (PRISM)  Table 37 summarizes the PRISM results for conversion measures across the six groups. The results show  the annual savings, relative precision on these savings, the pre‐NAC for each group, and the savings as a  percentage of the pre‐NAC. Table 37 also reports savings as a percentage of the pre‐conversion period  heating load.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 84 of 296   45  Table 37. Electric Savings per Home (PRISM Results)   Conversio n  Measure  Home  Type  Number  of Homes  Annual  Savings  (kWh)  Relative  Precision  on the  Savings  Pre‐NAC  (kWh)  Savings as  Percent of  Pre‐NAC  Pre‐ Heating  Usage  Savings as  Percent of  Pre‐Heating  Usage  NGF Dual 164 9,563 8% 24,349 39% 13,433 71% NGWH Dual 159 4,367 13% 16,305 27% 4,506 97% Multiple Dual 23 12,350 19% 25,646 48% 13,558 91% ASHP  Electric  Only 288 4,419 10% 24,955 18% 15,181 29%  Dual 33 4,994 38% 24,566 20% 12,944 39% All Homes 321 4,478 10% 24,915 18% 14,951 30%   The evaluated savings for electric furnace to NGF conversion resulted in annual savings of 9,563 kWh  per home (39% of pre‐conversion usage and 71% of pre‐conversion heating usage) with a relative  precision of ±8%. For electric water heater to NGWH conversions, the annual savings are 4,367 kWh per  home (27% of pre‐conversion usage and 97% of pre‐conversion heating usage) with a relative precision  of ±13%. The homes with both furnace and water heater conversions had on average 12,350 kWh of  savings (48% of pre‐conversion usage and 91% of pre‐conversion heating usage) with a relative precision  of ±19%.  The following figures are based on PRISM model results. Figure 11 shows the distribution of percentage  changes in the predicted electricity use between the pre‐ and post‐conversion periods.   Figure 11. Distribution of Percentage Changes in Annual Electricity Savings by Conversion Group      These results show an approximate normal distribution centered around a 30% reduction in electric use  for ASHP conversions, 50% reduction for NGF conversions, and 35% for NGWH conversions.  Figure 12 shows the distribution of percentage changes in the predicted electricity use for heating  between the pre‐ and post‐conversion periods. The percentage changes are based on the pre‐period  heating load.  0 20 40 60 80 100 ‐0.3 ‐0.2 ‐0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Nu m b e r  of  Pa r t i c i p a n t s ASHP NGF NGWH Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 85 of 296   46  Figure 12. Distribution of Percentage Changes in Annual Electricity Use for Heating       The figure shows a more than 80% drop in the heating load for approximately 70% of electric furnace to  NGF conversion homes. For the electric water heater to NGWH conversion homes, there is varying  amounts of heat load savings across all homes. Almost 50% of savings were achieved for most ASHP  conversion homes.  Figure 13 shows the distribution of percentage changes in the predicted electricity use for cooling  between the pre‐ and post‐conversion periods. The percentage changes are based on the pre‐period  cooling load.  Figure 13. Distribution of Percentage Changes in Annual Electricity Use for Cooling      The figure shows that customers achieved cooling efficiency, especially with ASHP conversions, followed  by NGF conversions, then NGWH conversions.  Per Home Savings Impacts (Pooled Regression Model)  Cadmus ran several specification of the panel regression model. We found that the overall savings  results were fairly consistent across the PRISM and pooled regression model. In the final model, Cadmus  controlled for all additional non‐program measures installed by the conversion participants (except for  0 10 20 30 40 50 60 ‐0.3 ‐0.2 ‐0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Nu m b e r  of  Pa r t i c i p a n t s ASHP NGF NGWH 0 5 10 15 20 25 30 35 ‐0.3 ‐0.2 ‐0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Nu m b e r  of  Pa r t i c i p a n t s ASHP NGF NGWH Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 86 of 296   47  high‐efficiency variable speed motors). The results for this model are shown in Table 38. Cadmus used  the coefficient estimates and standard errors from this table to calculate the savings and relative  precision.  Table 38. Electric Savings per Home (Fixed‐Effects Model)  Conversion  Measure Home Type Number  of Homes  Savings  (kWh)  Relative  Precision on  the Savings  Pre‐NAC  (kWh)  Savings as Percent  of Pre‐Period  Consumption  NGF Dual 164 10,287 9% 24,349 42% NGWH Dual 159 4,370 16% 16,305 27% Multiple Dual 23 13,643 26% 25,646 53% ASHP  Electric Only 288 4,775 11% 24,955 19% Dual 33 5,309 30% 24,566 22% All 321 4,826 10% 24,915 19%   The results reveal that there are higher savings for each conversion group after controlling for the  installation of other measures.   Table 39 provides the percentage of conversion participants in each group who had additional/non‐ program  measures installed. The regression savings analysis controls for all additional measures except  high‐efficiency variable speed motors.  Table 39. Percentage of Additional Measures Installed by the Conversion Participants  Conversion  Measure  Percentage of Homes  With Other Measures  Percentage of Homes  Receiving High‐Efficiency  ASHP Rebate  Percentage of Homes  Receiving Variable Speed  Motor Rebate  NGF 27%9%45% NGWH 26%6%33% ASHP  27%20%52%   Results and Findings  Table 40 shows the total tracked and qualified counts, savings, and realization rates for electric Space  and Water Conversions Program measures in Idaho.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 87 of 296   48  Table 40. Space and Water Conversions Measures and Reported and Adjusted Savings  Conversion  Measure  Reported  Measure  Count  Reported  Savings  (kWh)  Adjusted  Savings  (kWh)  Qualification  Rate  Verification  Rate  Adjusted  Gross  (kWh)  Realization  Rate  E Electric to  NGF 28 334,536 267,764 100% 100% 267,764 80%  E Electric to  NGWH 6 21,636 26,202 100% 100% 26,202 121%  E Electric to  ASHP 48 312,492 212,112 100% 100% 212,112 68%  Program  Total 82 668,664 506,078 100% 100% 506,078 76%    1.3.7. Weatherization/Shell  Program Description  Avista offered the Weatherization/Shell Program, for which it incented three measures available to  residential customers who heat their homes with fuel provided by Avista:  • Insulation—Ceiling/Attic   • Insulation—Floor   • Insulation—Wall   Avista incented qualifying ceiling and attic insulation (both fitted/batt and blown‐in) that increased the  R‐value by 10 or more at $0.15 per square foot. Homes qualified if they had existing attic insulation of R‐ 19 or less.   Avista incented floor and wall insulation (both fitted/batt and blown‐in) that increased the R‐value by 10  or more at $0.20 per square foot. Homes were eligible if they had existing floor and/or wall insulation of  R‐5 or less.   Analysis  Cadmus conducted a statistical billing analysis to determine adjusted gross savings and realization rates  for installed electric weatherization in PY 2011, PY 2012, and PY 2013. The previous years’ billing  analyses primarily included PY 2010 customers, although we extrapolated the realization rates to PY  2011. We included PY 2011 customers in the PY 2013 billing analysis since they now have complete post‐ period billing data. This increased the sample sizes and improved the precision of the weatherization  savings estimates.   We also present results that only include PY 2012 and PY 2013. To increase the accuracy of our analysis,  we only included participants with at least 10 months of pre‐ and post‐installation billing data.  Consequently, the PY 2013 billing analysis includes PY 2011, PY 2012, and early PY 2013 participants.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 88 of 296   49  To estimate weatherization energy savings resulting from the Idaho program, Cadmus used a pre‐ and  post‐installation combined CSA and PRISM approach. We calculated overall electric model savings  estimates for each measure bundle. We also attempted to estimate the detailed measure‐specific  savings impacts.  Billing Analysis Methodology  Avista provided Cadmus with monthly electric billing data for all Idaho participants, from January 2009  through January 2014. Avista also provided a measure detail file containing participation and measure  data. Participant information included:   • Customer details,  • Account numbers,  • Types of measures installed,  • Rebate amounts,  • Measure installation costs,  • Measure installation dates, and   • Deemed savings per measure.  Cadmus first matched weatherization measure information with the electricity billing data. We obtained  daily average temperature weather data from January 2009 through January 2014 for National Oceanic  and Atmospheric Administration (NOAA) weather stations, representing all ZIP codes in Avista’s service  territory. From daily temperatures, we determined base 65 HDDs and CDDs for each station. Using ZIP  code mapping for all U.S. weather stations, we determined the nearest station for each ZIP code. We  then matched billing data periods with the HDDs and CDDs from the associated stations.  Cadmus specified the pre‐ and post‐installation periods for each customer account using two  specifications:  1. The Customer‐Specific Measure Install Date: For each customer’s unique installation date, this  specification compares the year ending just before the install date with the year beginning on  the installation month.  2. The Fixed Dates: For this specification, the earliest and latest dates of available billing data are  selected. In effect, we used the period of January 2010 through December 2010 as the pre‐ installation period, before any installations occurred. We defined the post‐installation period as  the latest period with complete billing data: February 2013 through January 2014.  Table 41 shows an example of the specification of the pre‐ and post‐installation periods under the two  specifications. In this analysis, Cadmus used a combination of the two pre‐post specifications. While the  Customer‐Specific Measure Install Date specification allows for data from a more‐compressed  timeframe to be used, it relies heavily on the exact installation date. The Fixed Dates specification  removes this uncertainty by keeping only the earliest and latest periods of data, which are well outside  the installation period. The drawback with using Fixed Dates is that it requires a longer billing data  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 89 of 296   50  history; however, Cadmus relied on this method by default. To minimize the attrition, we used the  Customer Specific Measure Install Date specification when there was insufficient billing data to use  Fixed Dates.  Table 41. Example of Pre‐ and Post‐Installation Period Under the Two Specifications  Specification of Pre‐ and Post‐ Installation Period  Installation  Date Pre‐Analysis Period Post‐Analysis Period  Customer‐Specific Measure Install Date  November 2012  November 2011 ‐ October 2012  November 2012 ‐ October 2013  Fixed Dates January 2010 ‐ December 2010  February 2013 ‐ January 2014    Data Screening  General Screens  Cadmus removed accounts with fewer than 10 paired months (300 days) of billing data in the pre‐ or  post‐installation period, which could have skewed the weatherization savings estimates.  PRISM Modeling Screens  As a second step of the data screening process, Cadmus ran PRISM models for pre‐ and post‐installation  billing data. These models provided weather‐normalized pre‐ and post‐installation annual usage for each  account, and provided an alternate check of the savings obtained from the CSA model. Details on the  model specifications can be found in Appendix A.  After running the three models, we dropped models with a negative heating and/or cooling slope. The  best of the remaining models for each customer in either the pre‐ or post‐installation period had the  highest R‐square with positive heating and cooling slopes.  Next we applied the following screens to the PRISM model output, removing outlier participants from  the billing analysis:  • Accounts where the post‐installation weather‐normalized usage was 70% higher or lower than  the pre‐ NAC usage. Such large changes could indicate property vacancies or adding or  removing other electric equipment that is unrelated to weatherization (such as pools or spas).  • Accounts with negative intercepts (base load). These negative intercepts indicate a negative  base load, such as for lighting, refrigerators, or plug loads. In electric homes, the base load is  never expected to be negative.  • Accounts where the pre‐ and post‐installation billing data had anomalies, including vacancies,  seasonal usage, outliers, and/or equipment changes.  The Idaho weatherization population included 169 participants. Once we screened the data, 66 Idaho  weatherization participants (39%) remained for use in the CSA model, outlined below, to determine  overall savings.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 90 of 296   51  Table 42 summarizes the attrition from each of the screening steps listed above. Each row in the table  indicates the accounts remaining after attrition. Approximately 44% of the participant accounts were  dropped because they did not have sufficient pre‐ and post‐period billing data in the analysis. Another  17% were dropped from PRISM screening, and from the presence of vacancies, seasonal usage, outliers,  or equipment changes in the billing data.  Table 42. Weatherization Account Attrition  Screen Number  Remaining  Percent  Remaining  Number  Dropped  Percent  Dropped  Total Idaho weatherization accounts 169 100%0 0% Matched to billing data provided 169 100%0 0% Less than 10 months of pre‐ or post‐ billing data 94 56% 75 44% PRISM screening* 84 50% 10 6% Vacancies, seasonal usage, outliers, and/or  equipment changes 66 39% 18 11%  Final analysis group 66 39%103 61% * Using PRISM screens, Cadmus dropped accounts with: 1) negative heating slopes in the pre‐ or the post‐period or  2) post‐period usage that changed by more than 70% from pre‐period usage.    CSA Modeling Approach  To estimate weatherization energy savings from this program, we used a pre/post CSA, fixed‐effects  modeling method, using pooled monthly time‐series (panel) billing data. This fixed‐effects modeling  approach corrected for differences between pre‐ and post‐installation weather conditions, as well as for  differences in usage between participants, through the inclusion of a separate intercept for each  participant. This modeling approach ensured that model savings estimates would not be skewed by  unusually high‐usage or low‐usage participants. Details on the model specifications can be found in  Appendix A.  Program Impact Evaluation Findings  Overall Savings Impacts  Table 43 summarizes the usage and savings associated with the weatherization measures installed in  electrically heated homes in Idaho and Washington.19 The results show the annual savings, relative  precision on these savings, the pre‐installation heating usage NAC for each level, and the savings as a  percentage of the pre‐heating usage NAC. The table also shows ex ante savings estimates and the  achieved realization rates for the weatherization measures.                                                                19  Cadmus also estimated measure‐level models for PY 2012 and PY 2013 that contain the most recent ex ante  estimates. These estimates revealed that the attic insulation model savings were generally higher than the  current ex ante values. The wall insulation model savings were similar to the ex ante savings, and the floor  insulation model savings were lower than the ex ante savings.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 91 of 296   52  Table 43. Idaho and Washington Combined Weatherization Electric Savings per Home   (Fixed‐Effects Model)  Program Years  Number  of  Homes  Model  Savings  (kWh)  Relative  Precision  on the  Savings  Pre‐NAC  (kWh)  Heating  Pre‐NAC  (kWh)  Savings as  Percent  of   Pre‐NAC  Idaho Only Sample  PY 2011‐PY 2013 66 2,020 35% 20,813 11,125 9.7% PY 2012‐PY 2013* 14 1,640 96% 21,727 10,377 7.5% PY 2011 52 2,368 31% 20,567 11,326 11.5% Combined Washington & Idaho Sample PY 2011‐PY 2013 225 2,315 17% 19,975 11,206 11.6% PY 2012‐PY 2013** 53 2,569 30%22,669 13,107 11.3% PY 2011 172 2,241 20% 19,145 10,620 11.7% Overall, the Idaho PY 2011‐PY 2013 weatherization measures achieved savings of 2,020 kWh, or 9.7%  relative to the pre‐installation period NAC. With an average weatherization measure ex ante savings  estimate of 2,757 kWh, the weatherization measures realized 73% of the expected savings across the  three year period.  PY 2011 represents the predominant sample of the billing analysis; however, the ex  ante estimates are considerably higher than in other years.20   If the billing analysis is limited to only PY 2012 and PY 2013 participants, the sample size drops  considerably. Only fourteen 2012 ‐ 2013 participant homes in Idaho passed screening for analysis. The  fixed effects model was unable to estimate savings for this sample. Cadmus therefore presents the  results of our PRISM analysis. Due to the high relative precision of this estimate, Cadmus used the  combined Washington and Idaho sample results for PY 2012 and PY 2013 as the evaluated result for PY  2013 in Idaho. This result is the best estimate of current program performance in Idaho. The combined  PY 2012 and PY 2013 weatherization participants achieved savings of 2,569 kWh, or 11.3% savings  relative to the pre‐installation period NAC. With an average weatherization measure ex ante savings  estimate of 1,927 kWh, the weatherization measures realized 133% of the expected savings.  Table 44 shows the realization rates for the three combined sample analysis groups. The realization rate  of 133% shown for PY 2012 – PY 2013 is used to calculate adjusted gross savings for this program.                                                               20 The previous analysis relied primarily on PY 2010 participants and resulted in a weatherization savings estimate  of 953 kWh with a combined Washington and Idaho realization rate of 35%. PY 2011 savings and realization rate  are higher than the PY 2010 estimates.  The ex‐ante values for PY 2011 participants were developed before our  previous analysis was completed.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 92 of 296   53  Table 44. Idaho and Washington Weatherization Electric Savings Realization Rates   (Fixed‐Effects Model)  Sample  Group Program Years Model Savings  (kWh)  Relative  Precision on the  Savings  Annual Ex Ante  Savings (kWh)  Realization   Rate  WA & ID PY 2011‐PY 2013 2,315 17%2,604 89% WA & ID PY 2012‐PY 2013* 2,569 30%1,927 133% WA & ID PY 2011 2,241 20%2,812 80% * Values shown in this row are used as the evaluation results for PY 2013 in Idaho.   Figure 14 shows a comparison of the weatherization percentage savings to similar electric  weatherization evaluations. Avista’s PY 2011, PY 2012 and PY 2013 percent savings have improved  significantly since the PY 2010 program year.   Figure 14. Electric Weatherization Percent Savings Benchmarking      Table 45 shows the total reported and qualified counts, savings, and realization rates of electric  weatherization program measures.  9.1% 10.2% 6.9% 4.0% 7.0% 7.5% 12.5% 11.5% 11.8% 5.6% 0% 2% 4% 6% 8% 10% 12% 14% Puget Sound Energy Pacificorp (ID 2013) Pacificorp (WA 2013) Pacificorp (ID 2011) Pacificorp (WA 2011) Avista PY 2012‐2013 ID Avista PY 2012‐2013 WA Avista PY 2011 ID Avista PY 2011 WA Avista PY 2010 (Previous) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 93 of 296   54  Table 45. Weatherization Program Results  Measure  Reported  Measure  Count  Reported  Savings  (kWh)  Adjusted Savings  (kWh)  Qualification  Rate  Verification  Rate  Adjusted  Gross  (kWh)  Realization  Rate  E Attic Insulation  with Electric Heat 20 18,667 24,891 100% 100% 24,891 133% E Floor Insulation  with Electric Heat 7 13,121 17,496 100% 100% 17,496 133% E Wall Insulation  with Electric Heat 10 36,061 48,084 100% 100% 48,084 133% Program Total 37 67,849 90,471 100%100% 90,471 133%   1.3.8. Water Heater Efficiency  Program Description  The Water Heater Efficiency Program represented one measure: electric high‐efficiency water heaters.  Through this program, Avista offered a $50 incentive to residential electric customers who installed an  eligible high‐efficiency water heater. Electric water heaters with a tank had to have a 0.93 EF or greater  to qualify for the program.  Analysis  The PY 2010‐PY 2011 electric impact evaluation report21 documented Cadmus’ analysis for determining  the change in energy consumption resulting from installing electric high‐efficiency water heaters. As  that analysis continues to provide the best information on this measure, we used those results for PY  2013.   Results and Findings  Table 46 shows the total tracked and qualified counts, savings, and realization rate.  Table 46. Water Heater Efficiency Measure and Reported and Adjusted Savings  Reported  Measure  Count  Reported  Savings  (kWh)  Adjusted  Savings  (kWh)  Qualification  Rate  Verification  Rate  Adjusted  Gross  (kWh)  Realization  Rate  38 4,496 5,487 100% 100%5,487 122%                                                                21  Cadmus. Avista 2010–2011 Multi‐Sector Electric Impact Evaluation Report. May 2012.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 94 of 296   55  1.3.9. ENERGY STAR Homes  Program Description  Avista offered incentives through the ENERYG STAR Homes Program for builders constructing single‐ family or multifamily homes complying with ENERGY STAR criteria and certified as ENERGY STAR Homes.  Avista provided a $900 incentive for homes using electricity from Avista for space and water heating.  Analysis  In the PY 2010‐PY 2011 electric impact evaluation report, Cadmus documented the simulation modeling  we performed to determine energy savings achieved by ENERGY STAR Homes. As those simulation  results continue to provide accurate estimates of savings, we used those results for PY 2013.  Results and Findings  Table 47 shows the total tracked and adjusted counts, savings, and realization rates for measures  offered through the ENERGY STAR Homes Program. Avista funded electric measures for participating  Avista homes.   Table 47. ENERGY STAR Home Program Results  Program  Name  Reported  Measure  Count  Reported  Savings  (kWh)  Adjusted  Savings  (kWh)  Qualification  Rate  Verification  Rate  Adjusted  Gross  (kWh)  Realization  Rate  Home‐ Electric Only 5 17,521 12,550 100% 100% 12,550 72%    1.3.10. Geographic CFL Giveaway   Avista gives CFLs to customers at events throughout the year. Avista tracks the number of bulbs  distributed outside of their database and separate from the other programs with CFL offerings. Avista  estimates the energy savings as 15 kWh per bulb. This value is conservative compared to estimates  currently in use by the RTF. Cadmus accepts the energy savings estimated using 15 kWh per bulb, and  completed no further evaluation activities.  Table 48. Geographic CFL Giveaway Events, Evaluated Savings  Reported Measure Count Evaluated Savings (kWh)  Residential Giveaways 248 3,720 Low Income and Senior Citizen Giveaways 1,528 22,920 Program Total 1,776 26,640   1.4. Residential Conclusions   For PY 2013, Avista’s residential electric programs produced 5,933,197 kWh in gross savings, yielding an  overall realization rate of 116%. Table 49 shows reported and evaluated gross savings and realization  rates per program.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 95 of 296   56  Table 49. Total Program Reported and Evaluated Gross Savings and Realization Rates  Program Reported   Savings (kWh)  Adjusted Gross  Savings (kWh)  Realization  Rate  Simple Steps, Smart Savings 3,892,227 4,750,306 122% Second Refrigerator and Freezer  Recycling 219,576 368,174 168%  ENERGY STAR Products 79,374 29,011 37% Heating and Cooling Efficiency 154,160 144,480 94% Space and Water Conversions 668,664 506,078 76% Weatherization/Shell 67,849 90,471 133% Water Heater Efficiency 4,496 5,487 122% ENERGY STAR Homes 17,521 12,550 72% Geographic CFL Giveaway 26,640 26,640 100% Program Total 5,130,507 5,933,197 116%   1.5. Residential Recommendations  Cadmus recommends the following changes to Avista’s residential electric programs:  • Avista should consider updating its per‐unit assumptions of recycled equipment to reflect this  evaluation in order to ensure that planning estimates of program savings align with evaluated  savings.  • If Avista chooses to reinstate clothes washer rebates, it should continue to track them all within  the electric program unless there is a large penetration of gas dryers.  • Avista should increase the measure‐level details captured on applications and included in the  database. Specific additional information should include energy factors and/or model numbers  for appliances, baseline information for insulation, and home square footage, particularly for the  ENERGY STAR Homes Program.  • Avista should consider offering tiered incentives by SEER rating, as higher SEER systems  generally require ECM fan motors to achieve the high SEER rating.   Future Research Areas  The following are recommended future research areas for this program. Cadmus based these research  recommendations on the results of this impact evaluation and on known future changes to program  requirements.  • Avista should consider completing a lighting logger study within its territory if the results of the  forthcoming RBSA study do not accurately represent usage in their territory.  • Avista should consider researching the percentage of Simple Steps, Smart Savings bulb  purchases that are installed in commercial settings. This could reflect an increase in the average  installed HOU and increase program savings.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 96 of 296   57  • Avista should perform a billing analysis of ENERGY STAR Homes using a nonparticipant  comparison group once enough homes have participated under the new requirements to justify  performing the work. This research could be used to demonstrate the savings achieved through  energy‐efficiency construction practices.  • Avista should consider researching the current variable speed motor market activity to  determine if this measure should continue as a stand‐alone rebate or be packaged with other  equipment purchases.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 97 of 296   58  2. Residential Behavior Program  2.1. Program Description  For its Residential Behavioral Program, Avista sends home energy reports to residential customers to  educate them about their electricity use and suggest opportunities for saving electricity. Each report  contains:   • An analysis of the home’s current and past electricity use;  • A comparison of the home’s electricity use to the electricity use of its similar neighbors (known  as the neighbor comparison); and   • Electricity savings tips, including promotions of other Avista energy‐efficiency programs.   Avista seeks to achieve program electricity savings by increasing awareness of energy efficiency and by  encouraging lasting changes in energy‐use behaviors and in the adoption of energy‐efficiency measures.  Opower implements the program. Avista expected the program to save about 1% of energy use in PY  2013.   The program was targeted to single‐family homes and units in multifamily buildings with above‐average  electricity use.22 Although the program is focused on saving electricity, homes that receive electricity  and natural gas service from Avista are eligible to participate. Each home receives six reports during the  first 12 months of the program.   2.1.1. Program Details  The program began in June 2013, when Opower sent the first energy reports to homes in Avista’s Idaho  service territory by U.S. mail. Approximately 24,500 Avista Idaho residential electric customers received  one or more reports in 2013. Most program homes received their first report in June or July 2013,  although a small number received their first report in a later month.   To be eligible, homes had to meet the following criteria:  • Have above‐average electricity use;  • Have an adequate electricity billing history (12 or more months of continuous bills at the same  premise);  • Have a sufficient number of similar neighboring homes (for the neighbor comparison);  • Have home occupants who are responsible for paying electricity bills;  • Be a primary residence;                                                                22  The average annual electricity use per program home was 16,712 kWh in PY 2012. The median annual energy  use was 15,122 kWh and the 25th and 75th percentiles were 12,395 kWh and 19,429 kWh, respectively.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 98 of 296   59  • Not be master‐metered; and  • Have a valid mailing address.  By contacting Avista, a homeowner could stop delivery of the reports at any time; these customers are  referred to as opt‐outs. During PY 2013, there were 297 opt‐out customers in Idaho, for a rate of 1.21%,  which is a very small share of customers that received reports.  Opower implemented the program as a randomized control trial (RCT), in which Opower identified  homes in Avista’s service territory eligible to receive the reports and Cadmus independently and  randomly assigned each home to the program treatment or control group.23 Homes in the treatment  group received the home energy reports while homes in the control group did not receive reports and  were not informed of the program.24 With random assignment, the treatment and control groups are  expected to be equivalent except for the treatment group receiving energy reports, so it is therefore  possible to attribute any difference in average energy use during the program between the groups to  the receipt of the reports. RCT is the gold standard in program evaluation, because it yields unbiased  and robust estimates of the program treatment effects. RCT is recommended in the DOE’s forthcoming  UMP for Evaluating Behavior‐Based Programs (2014) and by State and Local Energy Efficiency Action  Network guidelines for evaluating residential behavior‐based programs (2012).25 This approach was also  employed for evaluations of large‐scale, home energy reports programs for Washington investor‐owned  utilities.26  Table 50 shows the number of Avista residential customers in Idaho assigned to the treatment group  and the number receiving one or more energy reports in PY 2013. Not every treatment customer  received energy reports because after Cadmus created the random assignments, Opower determined  that some customers did not have a valid mailing address or were missing information required to  generate a report. The table also shows the total number of customers in the control group and the                                                               23  Using standard statistical tests, Cadmus verified that the treatment and control groups were balanced in terms  of their annual, summer, and winter ADCs.  24  Opower could not deliver reports to a small number of homes assigned to the treatment group, as discussed  later in this report. Opower also identified control homes for which it would have been impossible to send a  home energy report.   25  See: State and Local Energy Efficiency Action Network. Evaluation, Measurement, and Verification (EM&V) of  Residential Behavior‐Based Energy Efficiency Programs: Issues and Recommendations. Prepared by A. Todd, E.  Stuart, S. Schiller, and C. Goldman, Lawrence Berkeley National Laboratory. 2012. Available online:  http://behavioranalytics.lbl.gov. Also see the draft DOE UMP protocols for evaluating behavior‐based  programs: http://energy.gov/eere/about‐us/initiatives‐and‐projects/uniform‐methods‐project‐determining‐ energy‐efficiency‐program   26  See: Puget Sound Energy’s Home Energy Reports Program. Prepared by DNV KEMA Energy & Sustainability.  2012. Available online: https://conduitnw.org/_layouts/Conduit/FileHandler.ashx?RID=849  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 99 of 296   60  number of customers in the control group who would have received reports if they had instead been  assigned to the treatment group.   Table 50. Number of Treatment and Control Homes in PY 2013    Idaho  Treatment Control Total  Randomly assigned 25,200 13,000 38,200 Randomly assigned and received a report (treatment) or  could have received a report (control)* 24,501 12,630 37,131  * This row excludes treatment homes that did not receive a report and control homes that could not have  received a report due to an invalid mailing address or unavailable information required to generate a report.    2.2. Residential Behavior Program Impact Evaluation Methodology  For the impact evaluation, Cadmus estimated the program energy savings in PY 2013 and quantified the  program impact on participation in Avista’s other residential efficiency programs. Cadmus used a panel  regression analysis of customer monthly bills to estimate the program’s electricity savings between  mailing of the first reports in June 2013 and December 2013. Cadmus analyzed Avista efficiency program  participation and measure savings data to estimate the program’s effects on participation in other  Avista efficiency programs, as well as to estimate savings that were counted towards other efficiency  programs.   More specifically, Cadmus’ evaluation of the Residential Behavior Program savings and efficiency  program uplift consisted of the following four tasks:  1. Data collection, review, and preparation.  2. Equivalency analysis (checks on treatment and control groups).  3. Billing analysis.  4. Energy‐efficiency program uplift and savings analysis.  2.2.1. Data Collection, Review, and Preparation  To perform the billing and uplift analyses, Cadmus collected the data outlined below.  Monthly Customer Bills   Avista supplied Cadmus with monthly electricity and gas bills (for dual‐fuel customers) between June  2012 and January 2014. The data included approximately 12 months of bills prior to and six months of  bills after the program began for homes in the treatment and control groups. These billing data  included: account numbers, energy use during the monthly billing cycle, number of days in the billing  cycle, and the first and last days of the billing cycle.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 100 of 296   61  Program Information   Cadmus obtained program enrollment information from Opower. These data included the following  fields for each home in the treatment and control groups:   • Address of residence;  • Assignment to treatment or control group;  • Date first report was generated ;27   • Opt‐out date for homes in the treatment group choosing not to participate in the program;   • Inactive date for homes that closed their gas or electric account; and  • Account numbers (for linking to billing data).  Weather   Cadmus collected daily average temperature data for weather stations in the program region from the  National Climate Data Center (NCDC). For a small number of stations where the NCDC data were  incomplete, Cadmus was able to interpolate the daily average temperature as an average of the  preceding and following day. In cases where a string of days were missing data, Cadmus used  temperature data from the next‐nearest weather station. Then we used temperatures to calculate the  number of HDDs and CDDs for each customer billing cycle.  Residential Energy‐Efficiency Program Tracking Data  Avista provided Cadmus with participant and measure savings data for any PY 2013 residential energy‐ efficiency programs in which participation could have been influenced by the behavior program. These  programs included those offering appliance recycling and residential rebates for HVAC equipment,  conversions to natural gas, and insulation.   For each program and measure, the data included: the account number; the number and description of  measures installed; measure installation dates; and verified gross savings. Cadmus used this information  to estimate the Residential Behavior Program’s participation and savings effects on other efficiency  programs.  Data Cleaning  Cadmus conducted a number of steps to inspect and clean the data provided by Opower. The steps are  described in Appendix B: Residential Behavior Program Data Cleaning Procedures. Cadmus did not  identify any significant issues with the Opower data.   Cadmus requested monthly billing data from Avista for Idaho customers from June 2012 through  February 2014. Avista provided bills for all but a few customers in the program treatment and control                                                               27  Opower assigned a pseudo first report date to control homes, representing the date the first energy report  would have been mailed.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 101 of 296   62  groups.28 Cadmus then followed a number of steps to clean the billing data. These steps are also  described in Appendix B: Residential Behavior Program Data Cleaning Procedures.   Data Preparation  Using the number of days in the billing cycle, Cadmus expressed each month’s energy use and weather  in average daily terms, then merged the billing, weather, and program information data, including  information about the approximate delivery date of the first home energy report.   Cadmus performed billing analysis on the population of program homes, except for homes from the  estimation sample that satisfied one or more of the following criteria:  • The home was in the treatment group but did not receive a home energy report or was in the  control group but would not have received a home energy report (indicated by the customer  information data missing the first report date).29   • Opower flagged the home as receiving a home energy report, but the home had not been  randomly assigned to the treatment group.30   • The home did not have a complete or near‐complete billing history for the 12 months before the  start of the program. Cadmus dropped homes from the analysis that had fewer than 11 bills  between June 2012 and May 2013.  Applying these filters resulted in a group containing 34,382 customers: 11,730 in the control group and  22,652 in the treatment group. Although the billing analysis excluded homes with fewer than 11 bills in  the year before the program, the savings estimate includes savings from these homes.31  2.2.2. Equivalency Analysis   Per an agreement between Avista, Cadmus, and Opower, Cadmus randomly assigned eligible residential  customers to the program treatment and control groups. At that time, Cadmus verified that the random  assignment resulted in treatment and control groups that were balanced in terms of their annual,  winter, and summer electricity use. Cadmus provided these random assignments to Opower, who                                                               28  Avista provided billing data for all but 868 customers (315 in Idaho). While we did not use these customers’  bills in the savings analysis, we did count the savings from these customers in our estimated PY 2013 total  program savings.   29  A home in the treatment group may have been missing a first report date because either the account became  inactive before the first report was generated, or Opower did not have a valid mailing address. An  approximately equal number of control homes were not assigned a first report date and were left out of the  analysis for the same reasons.  30  For example, this group included utility employees who requested to participate in the program.   31  Cadmus followed guidelines in the State and Local Energy Efficiency Action Network report, EM&V of  Residential Behavior‐Based Energy Efficiency Programs (2012), to drop homes with less than 10 months of  billing data from the analysis.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 102 of 296   63  additionally analyzed them using proprietary home and demographic characteristic data and verified  that the groups were balanced.   Cadmus also performed an equivalency check of homes in the treatment and control groups after  applying the filters described in the preceding section. As Table 51 shows, the difference between the  two groups’ annual consumption is small and not statistically significant.  Table 51. Equivalency of Analysis Sample Treatment and Control Group Homes  Average Annual Consumption  Treatment 16,710  Control 16,714  t value 0.05  P value 0.96    As described below, any time‐invariant differences in energy use between the treatment and control  groups after filtering are absorbed with customer fixed effects.32   2.2.3. Billing Analysis  To estimate Residential Behavioral Program electricity savings, Cadmus used difference‐in‐differences  (D‐in‐D) regression. D‐in‐D regression uses the energy use of treatment and control group homes before  and after the first energy reports to account for any naturally occurring efficiency that might have been  correlated with Residential Behavior Program activity.   The D‐in‐D approach requires monthly energy use from before and during the program in the treatment  and control group homes. Using Avista billing data, Cadmus conducted panel regression analysis of the  electricity consumption in Idaho to estimate the average program savings per home per day in PY 2013.   Model Specification  The average daily consumption (ADC) of electricity in home ‘i’ in month ‘t’ is given by:  ADCit = β1 POSTit + β2 PARTi x POSTit + W’γ + αi + τt + εit                                                               32  A home fixed effect represents the portion of a home’s energy use that does not vary over time. This energy  use is captured in the regression analysis by the inclusion of a separate intercept for each customer or by  equivalently transforming all the variables by subtracting home‐specific means.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 103 of 296   64  Where:  β1 = Coefficient representing the impact of non‐program factors on  consumption between pre‐program and program months.33  POST = An indicator variable for whether the month is pre‐ or post‐treatment.  This variable equals 1 in months following the first report date and 0  otherwise. The variable is defined with a short lag to allow for time  between the report’s generation and delivery to the home.34   β2 = Coefficient representing the conditional average treatment effect (ATE)  of the program on electricity use (kWh per home per day).  PART =  An indicator variable for program participation (which equals 1 if the  home was in the treatment group, and 0 otherwise).  W =  A vector using both HDD and CDD variables to control for the impacts of  weather on energy use.   γ =  Vector of coefficients representing the average impact of weather  variables on energy use.  αi = Average energy use in home ‘i’ that is not sensitive to weather or time.  Analysis controlled for non‐weather‐sensitive and time‐invariant energy  use with home fixed effects.  τt = Average energy use in month ‘t’ reflecting unobservable factors specific  to the month. The analysis controls for these effects with month‐by‐ year fixed effects.35   εit = Error term for home ‘i’ in month ‘t.’  Program Energy Savings   Cadmus estimated the total Residential Behavioral Program energy savings in PY 2013 by multiplying the  total number of program days across treated homes by the average savings per home per day, β2. To  illustrate, let i=1, 2, …, N index the number of homes receiving a home energy report; and D(x) return  the number of the days in 2013 from January 1 for a given date x (e.g., D(February 1)=32).                                                                33  In addition to naturally occurring efficiency, this coefficient captures differences in average consumption  between pre‐program and program months due to having 12 months of pre‐program bills and only seven  months of program bills.  34  Specifically, we defined the first report date as 14 days after the report was generated to allow time for report  delivery.  35  Cadmus included month‐by‐year fixed effects and POST in the same model because there was variation  between customers in the month of the first report date.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 104 of 296   65  The net program savings then equaled:  Net Savings = ‐β2*(∑i=1N ProgDaysi)  Where:  i =  1, 2, …, N; indexes the number of homes in the treatment group.  ProgDaysi  = 365 – D(first report datei), if the billing account for home ‘i' was still  active on December 31, 2013; and,    = D(inactive datei) ‐ D(first report datei), if the billing account for home ‘i'  became inactive before December 31, 2013.  As the definition of ProgDaysi shows, Cadmus counted savings from treated homes whose accounts  became inactive up until the accounts closed.   2.2.4. Energy‐Efficiency Program Uplift and Savings Analysis  The Residential Behavioral Program could have increased participation in Avista’s other efficiency  programs in two ways:   • First, energy reports directly educated customers about some of Avista’s efficiency programs  and encouraged them to take advantage of program offerings and incentives.   • Second, the reports could have raised customer awareness and knowledge of energy efficiency,  which may cause some to participate in Avista’s efficiency programs.   Analysis of efficiency program uplift is important for two reasons:   • First, Avista sought to learn whether and to what extent the Residential Behavior Program  caused participation in its other efficiency programs.   • Second, to the extent the Residential Behavioral Program caused participation in other  efficiency programs, energy savings resulting from this participation will have be counted twice:  in the regression estimate of Residential Behavior Program savings, and in the other programs’  savings. (Thus, Avista will want to subtract the double‐counted savings from its portfolio  savings.)  The uplift analysis described here yields estimates of the effect of the Residential Behavioral Program on  other efficiency program participation and the amount of double‐counted savings. The analysis was  limited, however, to program measures that Avista tracked at the customer level, and thus did not  include residential upstream programs promoting CFLs through store discounts. However, analysis of  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 105 of 296   66  Opower home energy report programs in other service territories suggests that CFLs account for only a  small percentage of total program savings.36   Methodology  As with the energy‐savings analysis, for the uplift analysis Cadmus followed the logic of the program’s  experimental design. Cadmus collected Avista electric efficiency program participation and savings data  for PY 2013, matched the data to the program treatment and control homes, and estimated uplift as a  simple difference in participation rates and savings between treatment and control groups. As  customers in the treatment and control groups are expected to be similar, except for having participated  in the behavior program, the difference between treatment and control groups in other efficiency  program participation is expected to equal the true Residential Behavior Program uplift. In matching  treatment and control homes to the PY 2013 efficiency program data, Cadmus excluded measures  installed after an account became inactive or before the first energy report date.   Let ρm be the participation rate (defined as the number of efficiency program participants to the number  of potential participants) in a PY 2013 program for group m (as before, m=1 for treated homes, and m=0  for control homes). Then:   Participation uplift = ρ1−ρ0  Expressing participation uplift relative to the participation rate of control homes in PY 2013 yields an  estimate of the percentage of uplift:  % of participation uplift = program uplift/ρ0  Residential Behavior Program savings from participation in other efficiency programs can be estimated  the same way, by replacing the program participation rate with the program net savings per home:  Net savings per home from participation uplift = σ1‐σ0.37  Multiplying net savings per home from participation uplift by the number of program homes yielded an  estimate of the total Residential Behavioral Program net savings counted in Avista’s other efficiency  programs.                                                                36  See the impact evaluation of Pacific Gas & Electric’s Home Energy Reports Program, 2010‐2012, which is  available online: http://www.calmac.org/publications/2012_PGE_OPOWER_Home_Energy_Reports__4‐25‐ 2013_CALMAC_ID_PGE0329.01.pdf  37  Cadmus obtained net savings by multiplying measure‐verified gross savings by the estimated measure net‐to‐ gross (NTG) ratio.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 106 of 296   67  Cadmus performed participation and savings uplift analyses for the following Avista residential efficiency  programs:  • Second Refrigerator and Freezer Recycling  • Residential rebate programs, including:  ƒ Space and Water Conversions (conversion from electric furnace to NGF or electric water  heater to NGWH)  ƒ Heating and Cooling Efficiency (ASHPs (including conversions), variable speed motors, and  electric water heaters)  ƒ Weatherization/Shell (floor and attic insulation)  Cadmus did not perform uplift analyses for the following residential electricity efficiency programs:   • Geographic CFL Giveaway. Though the Residential Behavior Program may have influenced CFL  and other high‐efficiency lighting purchases, such purchases were tracked at the store level.  • ENERGY STAR Homes. This program targeted builders of new homes, which the Residential  Behavior Program did not target.  2.3. Program Results and Findings  2.3.1. Electricity Savings per Home Estimates  Table 52 shows the average daily energy savings per home or, equivalently, the conditional ATE per  home of Avista’s Residential Behavioral Program. The savings are represented by the coefficient on the  interaction variable PARTit x POSTit. On average, homes saved 0.674 kWh (1.57%) per day.38 This savings  estimate was statistically significant at the 1% level.   For perspective, these savings could be achieved by turning off a 65‐watt incandescent lamp for 10  hours per day or by replacing nine 100‐watt incandescent lamps used for one hour each day with nine  25‐watt CFLs.                                                                38  Average savings of 1.57% during the first seven months is slightly greater than the average savings over the  same period estimated for other utility home energy reports programs. See: Allcott, Hunt. (2011). Social  Norms and Energy Conservation. Journal of Public Economics, 95(2), 1,082‐1,095. Also see: Rosenberg,  Mitchell, G. K. Agnew, and K. Gaffney. Causality, Sustainability, and Scalability – What We Still Do and Do Not  Know about the Impacts of Comparative Feedback Programs. Paper prepared for 2013 International Energy  Program Evaluation Conference, Chicago, Illinois, August 13‐15, 2013.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 107 of 296   68  Table 52. Conditional Average Treatment Effect*   kWh/day  PARTit x POSTit – Year 1 (Year 1 savings per day per home) 0.674 (0.095) Customer fixed effects Yes Month‐by‐year fixed effects Yes Weather polynomials Yes N (homes) 36,862 * The dependent variable is average daily electricity use in the month for a treatment or control group home. The  model estimated this by ordinary least squares using monthly bills between June 2012 and January 2014. Huber‐ White estimated standard errors (shown in parentheses) are clustered on homes.     Cadmus ran several other model specifications to verify the robustness of the savings estimates with the  inclusion or omission of different variables. For example, we estimated models with and without  different combinations of home‐fixed effects, time‐fixed effects, and the weather variables. Appendix C:  Residential Behavior Program Regression Model Estimates includes complete results from these other  regression specifications. Little or no difference occurred in the estimated savings between  specifications—an expected result, as estimates of treatment effects in large RCTs typically prove robust  to changes in model specifications.   Table 53 shows the average savings per Residential Behavior Program home in PY 2013. Cadmus  obtained this estimate by multiplying the estimated savings per home per day in Table 52 by the average  number of program days for treated homes in PY 2013. We defined the program days for a home as the  number of days between the first report date and December 31, 2013.   Table 53. Average Savings (kWh) Per Home for PY 2013*  Savings (kWh) 90% Confidence Interval   Lower Bound  90% Confidence Interval   Upper Bound  119 92 147 * Cadmus estimated these savings per home based on Table 52 and on the average number of program days per  home in PY 2013.    Figure 15 shows estimates of average savings per month from June 2012 to January 2014. Cadmus  obtained savings via a regression that estimated the difference in energy use between treatment and  control group homes, conditional on home fixed effects. The ATE is shown as a percentage of the ADC of  control group homes.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 108 of 296 * Cadmus  year fixed  treatment  effect.    As expec control g interval i that we c report w Treated h savings w ramping o energy re 2.3.2. P Table 54 r by multip treated h obtained the s effects, and m group. As the  ted, there we oup homes b ncludes zero i annot reject t as random an omes starte ere below 1 f savings in t port progra rogram Sav reports the t lying the esti mes.   Fi savings estima onth‐by‐year f model also in re not signifi efore Opow n each mont he identifyi d uncorrelat  saving ener  but still su he first six m s.   ings Estima otal program  mate of aver gure 15. Aver tes in this figu ixed effects i ludes home fi ant differen r sent the fi h. The appro g assumptio d with expe y after recei stantial. Per onths of the  tes  savings for A age daily sav 69  age Savings P re from a regr teracted with  xed effects, it w ces in averag st energy re imate equal  of the savi ted energy u ving the first  cent savings i program is e vista’s Idaho  ings per hom Per Month* ession of ADC o an indicator o as necessar  energy use  ports in June  ity of energy  ngs analysis: t se.   reports. In J creased in s ident in Fig service terri e by the tota n home fixed  f whether tha  to omit one m between tre 2013. The 9 use before t hat receivin ly and Augu ubsequent m ure 15, which  tory. Cadmus  l number of p effects, mont  home was in t month‐by‐year  atment and  0% confidenc eatment me  a home ene t, percentag onths. The  is typical of h estimated s rogram day     h‐by‐ the  fixed  e  ans  rgy  e  home  avings  s for  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 109 of 296   70  Table 54. Residential Behavioral Program Energy Savings in PY 2013  Service  Area  Ex Ante  Percent Net  Electricity  Savings*  Evaluated  Percent Net  Electricity  Savings  Evaluated  Annual Net  Electricity  Savings (kWh)  90% CI  Lower  Bound  90% CI  Upper  Bound  Realization  Rate  Idaho 1.20% 1.57%2,925,860 2,224,203 3,607,516 131% * Cadmus obtained ex ante percentage electricity savings from the 2013 Avista Business Plan. Avista expected  1.4% electric savings from the program in the first year, and assumed that 40% of the first‐year energy savings  would occur in the first six months of the program in 2013. Given the 2013 consumption data for the control  group, it follows that the savings expected for the first six months of the program are 1.2%. Evaluated annual net  electricity savings are based on the savings estimate shown in Table 53.     Avista expected net savings of 1.2% from the Residential Behavioral Program in PY 2013. Based on the  regression analysis of monthly energy use, Cadmus determined that the program achieved net savings  of 1.57%. Cadmus estimated net savings of 2,925,860 kWh in PY 2013, with a 90% confidence interval   [2,224,203 kWh, 3,607,516 kWh], or relative precision of ±23%. The program realized 131% of the  expected savings.   2.3.3. Uplift Analysis  This section reports estimates of the Residential Behavioral Program’s effect on participation in Avista’s  other efficiency programs (the uplift), as well as savings resulting from additional participation. To avoid  double‐counting savings, behavior program savings from participation in other efficiency programs must  be subtracted from the residential portfolio savings. In estimating participation uplift and savings from  uplift, Cadmus considered only those measures installed after the first reports were received.   Table 55 shows the percentage uplift estimates for each program. As noted in the methodology, uplift  equals the absolute effect on the participation rate, and the percentage uplift equals the participation  rate effect divided by the participation rate of control homes in PY 2013.   Table 55. Residential Behavioral Program Participation Uplift*   Program Participation Uplift % Participation Uplift  Second Refrigerator and Freezer  Recycling 0.14% 41%  Residential Rebate Programs  Space and Water Conversions 0.01%16% Heating and Cooling Efficiency 0.21%100% Weatherization/Shell 0.01%158% * Participation uplift is an estimate of change in the rate of program participation attributable to the Residential  Behavior Program. The percentage of participation uplift is the change in the participation rate relative to the  program participation rate of customers in control homes in PY 2013. The text below provides estimation details  and data sources.     Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 110 of 296   71  The Residential Behavioral Program increased the rate of participation of customers in the Second  Refrigerator and Freezer Recycling, Space and Water Conversions, Heating and Cooling Efficiency, and  Weatherization/Shell programs. While this increase was less than 1%, the baseline rate of participation  was relatively low, so the percentage uplift effect was higher, especially for the Weatherization/Shell  Program.   The Second Refrigerator and Freezer Recycling Program experienced 41% uplift, the Space and Water  Conversions Program experienced 16% uplift, the Heating and Cooling Efficiency Program experienced  100% uplift, and the Weatherization/Shell Program experienced 158% uplift.39 This means, for example,  that treatment homes were 41% more likely to participate in the Second Refrigerator and Freezer  Recycling Program than control homes.   Savings Analysis  Table 56 shows electricity savings from uplift in participation in the Second Refrigerator and Freezer  Recycling Program and the residential rebate programs in PY 2013. The savings reflect the behavior  program’s effects on both participation rates and on the numbers and/or kinds of measures installed.40  The savings from program uplift reported in Table 56 should be subtracted from the PY 2013 residential  portfolio savings.  Table 56. Residential Behavior Program Electricity Savings from Program Uplift  Program Idaho PY 2013  Home (kWh) Total Savings (kWh)  Second Refrigerator and Freezer  Recycling 0.78 19,060  Residential Rebate Programs  Space and Water Conversions 0.13 3,238 Heating and Cooling Efficiency 1.25 30,700 Weatherization/Shell 0.08 1,957 Total 2.24 54,955   Participation in the Residential Behavior Program resulted in Avista efficiency program savings of 54,955  kWh, equal to 1.9% of the behavior program savings. The majority of uplift savings derived from                                                               39  The percentage uplift for the Weatherization/Shell Program was large because the increase in the conversion  rate was large relative to the baseline rate.   40  The methodology called for using net savings of efficiency measures in calculating Residential Behavioral  Program savings from efficiency program uplift; however, except for the Second Refrigerator and Freezer  Recycling Program, Cadmus did not derive NTG values for program measures. Instead, we used adjusted gross  savings estimates based on field estimates of utilization and installation rates to calculate uplift savings. For  consistency across programs, we used the adjusted gross savings for the Second Refrigerator and Freezer  Recycling Program.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 111 of 296   72  residential conversions of electricity to gas. To avoid double counting, the savings from uplift must be  subtracted from evaluated savings for the electricity efficiency portfolio, from the Residential Behavior  Program, or from other efficiency PY 2013 programs.   2.3.4. Evaluated Net Savings Adjustment  Table 57 shows the Residential Behavioral Program adjusted net savings for PY 2013. The adjusted  savings are the difference between the program‐evaluated net savings and estimated savings from  program uplift. The adjusted net program savings in PY 2013 were 2,870,905 kWh.  Table 57. Residential Behavioral Program Adjusted Net Savings in PY 2013  Service Area Evaluated Net Electricity  Savings (kWh/year)  Adjusted Net Electricity  Savings (kWh/year)  Idaho 2,925,860 2,870,905    2.4. Residential Behavior Program Conclusions   Analysis of the monthly electric bills of treatment and control homes during the first seven months of  the Residential Behavior Program led to the following PY 2013 findings:  • Homes in Idaho saved an average 0.674 kWh (1.57%) per day. The percentage savings were  higher than expected (1.2%).   • The program achieved total electricity savings of 2,925,860 kWh. The relative precision of the  electricity savings estimate was ±23% with 90% confidence.   • The program generated percentage savings at a slightly higher rate than the normal range for  energy reports programs.   Analysis of Avista’s energy‐efficiency program data resulted in the following findings about the  Residential Behavior Program effects on other efficiency program participation and savings:  • The Residential Behavior Program lifted the rate of participation in the Second Refrigerator and  Freezer Recycling, Space and Water Conversions, and Weatherization/Shell programs. The  percentage uplift for the Space and Water Conversions Program was large because of the low  baseline rate of conversions.  • The total Residential Behavior Program electricity savings from efficiency program uplift was  54,955 kWh, or 1.9%.   • Savings from efficiency program uplift are counted in the Residential Behavior Program  regression‐based estimate of savings and in other programs’ savings. To avoid double counting,  the uplift savings must be subtracted from the evaluated savings for the electric portfolio or for  the Residential Behavior Program.  • After adjusting net electricity savings for program uplift, the program saved 2,870,095 kWh.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 112 of 296   73  2.5. Residential Behavior Program Recommendations  Based on the analysis, Cadmus makes the following recommendations:  • Avista should continue to promote its efficiency programs in the energy reports, as the reports  increased both the rate of efficiency program participation and savings.   • Avista should consider performing additional research about the peak‐coincident demand  savings from the Residential Behavior Program to determine whether it is cost‐effective relative  to existing residential load control programs.41                                                                41  Research would require analysis of high frequency (15 minute or one hour interval) energy use data for a large  number of treatment and control group homes. For an example of such an analysis, see: Stewart, James. Peak‐ Coincident Demand Savings from Residential Behavior‐Based Programs: Evidence from PPL Electric’s Behavior  and Education Program. 2013. Available at http://escholarship.org/uc/item/3cc9b30t.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 113 of 296   74  3. Nonresidential Impact Evaluation  3.1. Introduction  Through its nonresidential portfolio of programs, Avista promotes the purchase of high‐efficiency  equipment for commercial utility customers. Avista provides rebates to partially offset the difference in  cost between high‐efficiency equipment and standard equipment.   The nonresidential electric portfolio has 11 programs in three major categories: prescriptive programs,  the Energy Smart Grocer Program, and the Site‐Specific Program (for custom projects). These programs  are described below.  Prescriptive Commercial Clothes Washer  To encourage customers to select high‐efficiency clothes washers, this program is targeted to  nonresidential electric and natural gas customers in multifamily or commercial Laundromat facilities.  Avista streamlined the program approach to reach customers quickly and effectively and to promote  ENERGY STAR or Consortium for Energy Efficiency (CEE)‐listed units.  Prescriptive Commercial Windows and Insulation  Beginning in January 2011, Avista has processed the installation of commercial insulation through this  prescriptive program in addition to the Site‐Specific Program. Projects are eligible for the Prescriptive  Commercial Windows and Insulation Program when they have:  • Wall insulation of less than R‐4 that is improved to R‐11 or better  • Attic insulation of less than R‐11 that is improved to R‐30 or better  • Roof insulation of less than R‐11 that is improved to R‐30 or better  Prescriptive Food Service   Applicable to nonresidential electric and gas customers with commercial kitchens, Avista provides direct  incentives to customers who choose high‐efficiency kitchen equipment though this program. The  equipment must meet either ENERGY STAR or CEE tier levels (depending on the unit) to qualify for an  incentive.  Prescriptive Green Motors Initiative  Operated in partnership with The Green Motors Practices Group42, Avista provides education through  this program to foster the organization and promotion of member motor service centers’ commitment  to energy‐saving shop rewind practices for motors ranging from 15 HP to 500 HP.                                                                42  http://www.greenmotors.org/  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 114 of 296   75  Prescriptive Lighting  Since there is a significant opportunity for lighting improvements in commercial facilities, Avista offers  direct financial incentives to customers who increase the efficiency of their lighting equipment through  this program. The rebate is available to existing commercial and industrial electric customers whose  facilities are on rate schedules 11 or above. Avista provides pre‐determined incentive amounts for 38  measures, including:   • T12 fluorescent to T8 fluorescent lighting  • High bay, high‐intensity discharge lighting to T5 fluorescent or T8 fluorescent  • High bay, high‐intensity discharge lighting to induction fluorescent  • Incandescent to CFL or cold cathode fluorescent  • Incandescent to LED  • Incandescent exit signs to LED exit signs   Prescriptive Motor Controls HVAC  The use of single‐speed motors to drive fans or pumps often provides the opportunity to save energy  through the use of a variable frequency drive (VFD). A VFD can convert a single‐speed motor to a  variable speed motor with no modification to the motor itself. This can be an efficient way to convert  constant volume air systems into variable volume systems, for example. VFDs are readily available for  motors from 1 HP to 300 HP and are easily installed directly into the power line leading to the motor,  replacing the existing motor starter. Avista provides incentives for the installation of VFDs.  Many fan and pump systems have a cost‐effective application for VFDs. Quite often these systems have  a variable flow rate through the use of throttling devices, such as valves and dampers that vary the flow.  Throttling devices essentially waste excess energy to maintain a given pressure or flow, and the use of a  VFD can be very cost‐effective in these situations. Typical examples of systems using throttling devices  are: booster pumps for domestic water, process chilled or condenser water systems, and fan discharge  dampers.  Other variable flow systems use mechanical or electrical methods such as inlet vanes, outlet dampers,  eddy current clutches, hydraulic couplings, or variable pitch pulleys to vary the speed of the fan or  pump. These are more efficient than throttling devices, but not as efficient as VFDs. Some fan and pump  systems that currently have a constant flow may be converted to variable flow through system  modifications.  Prescriptive PC Network Controls  Computers that remain in a full‐power state when idle can waste significant energy, especially for  customers with numerous PCs. Through this program, available to nonresidential electric customers,  Avista provides an incentive for the installation of a network‐based power management software  solution that manages the power of networked PCs.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 115 of 296   76  Prescriptive Standby Generator Block Heater  Most block heating technology employs natural convection within the engine block system to drive  circulation—more commonly known as thermosiphon. Avista promotes the replacement of  thermosiphon‐style engine block heaters with pump‐driven circulation units, which reduces the overall  block temperature. Because this replacement also decreases the heat transfer rate from the block to the  environment, it can reduce overall block heater energy consumption, which is tied to the circulation  method.  Because thermosiphon heaters require temperature variation to drive circulation, warmer coolant rises  to the top of the block and colder coolant descends to the lower sections of the block. The coolant in the  lower portions of the block must meet the minimum block temperature requirements, which means the  coolant in the upper parts of the block will exceed the minimum temperature requirements. A pump‐ driven heater does not require a temperature difference to drive flow, leading to a more uniform  coolant temperature throughout the block. This reduces the overall average block temperature and  minimizes the driving force affecting heat transfer.  Renewables   Avista provides prescriptive incentives for residential and nonresidential projects installing photovoltaic  (solar electric) systems and/or wind turbines.  Energy Smart Grocer  Refrigeration has high potential for energy savings, but is often overlooked because of the technical  aspects of the equipment. Through the Energy Smart Grocer Program, Avista assists grocery store  customers with technical aspects of their refrigeration systems, while also providing guidance as to the  amount of savings they can achieve. A field energy analyst offers technical assistance to customers,  produces a detailed report of the potential energy savings at their facility, and guides them through the  program process from inception through the payment of incentives for qualifying equipment.  Site Specific  The Site‐Specific Program is for nonresidential measures that are not addressed by any of the  prescriptive applications, but must be considered based on their project‐specific information. For a  measure to be considered, it must demonstrate kWh and/or therm savings. These measures are  available to all commercial, industrial, or pumping customers that receive electric or natural gas service  from Avista.   Electric and saving measures included in the program are:  • Site‐Specific HVAC   ƒ HVAC Combined (heating and cooling)  ƒ HVAC Cooling  ƒ HVAC Heating  ƒ Multifamily Measures  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 116 of 296   77  • Site‐Specific Lighting  ƒ Lighting Exterior  ƒ Lighting Interior  • Site‐Specific Other  ƒ Appliances  ƒ Compressed Air  ƒ Green Motors Rewind  ƒ Industrial Process  ƒ Motor Controls Industrial  ƒ Standby Generator Block Heater  • Site‐Specific Shell   Avista implements the Site‐Specific Program and prescriptive programs, while PECI implements the  Energy Smart Grocer Program. As implementers, both Avista and PECI are responsible for designing and  managing program details. Both implementers developed algorithms for use in calculating measure  savings and determining measure and customer eligibility.   Avista staff fields inquiries from potential participants and contractors and maintains a project tracking  database. Throughout the program, Avista manages projects by reviewing and approving applications at  all stages of the process, calculating project savings, and populating the database with relevant  information.   3.2. Methodology  Cadmus designed the impact evaluation to verify reported program participation and estimate energy  savings. For the impact evaluation, we determined gross savings through engineering calculations,  verification site visits, metering, and some project‐level billing analysis.  We reviewed Avista’s reported gross energy savings and available documentation, such as audit reports  and savings calculation work papers, for a sample of sites, giving particular attention to the calculation  procedures and documentation for savings estimates. We also verified the appropriateness of Avista’s  analyses to calculate savings, as well as the operating and structural parameters of the analyses. We  then determined gross evaluated energy savings through site visits and engineering calculations for a  sample of projects.   Cadmus collected baseline, tracking, and program implementation data through on‐site interviews with  facility staff. During on‐site visits, we verified measure installations and determined any changes to the  operating parameters since the measures were first installed. We also interviewed facility staff about  their experiences and any additional benefits or shortcomings of the installed system. We used the  savings realization rates from site visits to estimate savings and develop recommendations for future  studies.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 117 of 296   78  3.2.1. Sampling  Cadmus developed a sampling calculation tool to estimate the number of on‐site visits required to  achieve the rigor precision target shown in Table 58. We used preliminary program population data  provided by Avista, and determined we needed to conduct measurement and verification at 107 sites.  We anticipated achieving 90/10 precision for the overall nonresidential portfolio level through the  targets for each stratum.  Table 58. Proposed PY 2012‐PY 2013 Nonresidential Evaluation Activities  Stratum Precision Target Proposed Site Visits  Prescriptive 90/20 26  Energy Smart Grocer 90/20 13  Site‐Specific HVAC 90/20 25  Site‐Specific Lighting 90/20 21  Site‐Specific Other 90/20 15  Site‐Specific Shell 90/20 7  Total 90/10 107    Cadmus selected both a census and random sample from each stratum. The census projects represented  a small number of participants in the stratum with large savings impacts. The cutoff for the census  savings for each stratum is shown in Table 59. We visited all census project sites. Within each stratum,  we also randomly selected additional site visits from the remaining population of projects.  Table 59. Census‐Level Cutoff by Stratum  Stratum Reported Savings (kWh)  Prescriptive 300,000  Energy Smart Grocer 300,000  Site‐Specific HVAC 500,000  Site‐Specific Lighting 500,000  Site‐Specific Other 500,000  Site‐Specific Shell N/A    Table 60 shows the precision achieved for the actual number of evaluation activities for electric  measures. In subsequent sections of this report, we explain the differences between our initial proposed  and actual sampling plan for the evaluation activities. For example, in our initial sampling plan we  categorized ENERGY STAR appliances in the ‘Site‐Specific Other’ category, but as the impact evaluation  progressed, we determined these measures were more appropriate for the ‘Prescriptive’ category.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 118 of 296   79  Table 60. Final PY 2012‐PY 2013 Electric Evaluation Activity Sample  Stratum Achieved Precision Metering Projects  Completed Site Visits Completed  Prescriptive 90/17 7 25 Energy Smart Grocer 90/5 2 23 Site‐Specific HVAC 90/6 1 29 Site‐Specific Lighting 90/11 5 20 Site‐Specific Other 90/3 7 13 Site‐Specific Shell 90/11 0 10 Total 90/9 22 120   In selecting the random sample from each stratum, we found that the extract from Avista’s database did  not include addresses that would enable us to identify whether projects performed for the same  company were at different sites, nor did it include information on the specific measures installed.  Therefore, our sampling process was iterative. From the extract, we determined the final primary and  backup samples by selecting projects of interest and asking Avista for additional data, which we received  and used to determine the number and types of projects at various locations.   Also, the database extract provided program‐level data, but not measure‐level information. Therefore,  we attempted to verify savings for every incented measure at each site, regardless of whether it  achieved gas or electric savings. We were unable to determine whether we evaluated an accurate  distribution of measure types within each program, which would have required an exhaustive review of  project files and it was not within the scope of the evaluation.  3.2.2. Data Collection  Cadmus collected metering data from 22 sites and conducted verifications at 120 sites. For each, we first  conducted a document review to determine measure type, quantity, operational parameters, and  calculation methodology.  Document Review  Avista provided Cadmus with documentation of the energy‐efficiency projects undertaken at the sample  sites. We reviewed program forms, the tracking database, audit reports, and savings calculation work  papers for each rebated measure. In reviewing calculation spreadsheets and energy simulation models  relevant to the evaluation effort, we paid particular attention to calculation procedures and  documentation for savings estimates.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 119 of 296   80  Cadmus reviewed each application for the following information:   • Equipment being replaced: descriptions, schematics, performance data, and other supporting  information.  • New equipment installed: descriptions, schematics, performance data, and other supporting  information.  • Savings calculation methodology: methodology used, specifications of assumptions and sources  for these specifications, and correctness of calculations.  Short‐Term Metering  Cadmus performed short‐term (two weeks) metering for projects within the nonresidential electric  portfolio. We installed power meters and light loggers to obtain operational data to inform energy‐ savings estimates. The metering and analysis requirements were specific to the measure category.  Site Visits  Cadmus performed on‐site visits to verify measure installations, collect primary data to calculate savings  impacts, and interview facility staff.  We accomplished three primary tasks during the on‐site visits:   1. We verified the implementation status of all measures for which customers received incentives.  We verified that the energy‐efficiency measures were installed correctly and still functioned  properly, and also verified the operational characteristics of the installed equipment, such as  temperature setpoints and operating hours.  2. We collected the physical data, such as cooling capacity or horsepower, and analyzed the energy  savings realized from the installed improvements and measures.   3. We interviewed facility personnel to obtain additional information on the installed system to  supplement data from other sources.  3.2.3. Engineering Analysis  The prescriptive programs and the Site‐Specific Program required significantly different methods of  analysis.   Overview  Our procedures for verifying savings through an engineering analysis depended on the type of measure  being analyzed. The following analytical methods were included in this evaluation and are described in  the following sections:  • Prescriptive deemed savings  • Short‐term metering  • Billing analysis  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 120 of 296   81  • Calculation spreadsheets  • Energy simulation modeling  Prescriptive Deemed Savings  For most prescriptive measures, Cadmus verified the deemed savings estimates Avista used. We focused  our verification activities on the installed quantity, equipment nameplate data, and operating hours, as  well as on the proper installation of equipment. Where appropriate, we used data from site verification  visits to re‐analyze prescriptive measure savings using Avista’s Microsoft Excel® calculation tools,  ENERGY STAR calculation tools, RTF deemed savings, and other secondary sources.   Metering  Depending on the site and measure, Cadmus determined whether short‐term metering (over a period of  two weeks) would be most appropriate for achieving precision in that particular project’s energy‐saving  calculations. Specific metering details for each measure category are discussed in the Results and  Findings section. The installed metering equipment encompassed:  • HOBO light loggers for 12 lighting projects.  • Energy Logger Pros for metering two Energy Smart Grocer projects: anti‐sweat heater controls  and refrigeration compressors.  • Energy Logger Pro for metering fan usage for one site‐specific HVAC cooling project.  • Energy Logger Pros for metering energy use for seven compressed air and industrial process  motor projects.  Our analysis for each project varied by the measure and metering data obtained.  Billing Analysis  Cadmus analyzed Avista’s metered billing data for several site‐specific HVAC projects. Using a pre‐ and  post‐modeling approach, we developed retrofit savings estimates for each site. This modeling approach  accounted for differences in HDDs between years. It also determined savings based on normalized  weather conditions, since the actual weather conditions may have been milder or more extreme than  the TMY3 15‐year normal weather averages from 1991‐2005 obtained from the NOAA.  We also obtained daily weather data from NOAA for each weather station associated with the  participant projects, then calculated the base 65 reference temperature HDDs. We matched the  participant billing data to the nearest weather station by ZIP code, then matched each monthly billing  period to the associated base 65 HDDs.   We followed a modified PRISM approach for developing the analysis models, which normalized all  dependent and independent variables for the days in each billing period and allowed for model  coefficients to be interpreted as average daily values. We used this methodology to account for  differences in the length of billing periods. For each project, we modeled the ADC in kWh as a function  of some combination of average standing base load, HDDs, and (where appropriate) daily consumption.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 121 of 296   82  For each site, Cadmus estimated two demand models: one for the pre‐period and one for the post‐ period. We chose this methodology over a single standard treatment effects model to account for  structural changes in demand that might have occurred due to retrofits.   Cadmus calculated three scenarios after estimating model coefficients for each site. First, we estimated  a reference load for the previous 12 billing cycles using the pre‐installation period model. This scenario  extrapolated the counterfactual consumption, which is what the consumption would have been in  absent the program. We calculated the energy savings as the difference between the counterfactual  scenario and the actual consumption.  Cadmus then estimated two normalized scenarios: one using the pre‐model, and one using the post‐ model. We used 15‐year TMY3 data in both scenarios as the annual HDD and mean annual values for the  usage data. The difference between these two scenarios represents the long‐term expected annual  savings.  Calculation Spreadsheets  Avista developed calculation spreadsheets to analyze energy savings for a variety of measures, including  building envelope measures such as ceiling and wall insulation. These calculation spreadsheets require  the input of relevant parameters such as square footage, efficiency value, HVAC system details, and  location details, from which Avista‐programmed algorithms estimate energy savings. For each  spreadsheet, we reviewed the input requirements and output estimates and determined if the approach  was reasonable.  Energy Simulation Modeling  Avista determined savings for many site‐specific HVAC and site‐specific shell projects with energy  simulation modeling, choosing eQuest software because of the complex interactions between heating  and cooling loads and the building envelope. Avista provided the original energy simulation models,  which we reviewed to determine the relevant parameters and operating details (such as temperature  setpoints) for the applicable measure. We updated the models as necessary based on our site  verification data.  3.3. Results and Findings  3.3.1. Overview  Cadmus adjusted gross savings estimates based on our evaluated findings. Further details by program  are discussed in the following sections.  For most projects, the documentation was readily available and the measures performed close to  expectations. However, some project files contained excessive documentation. In certain cases, projects  evolved over time based on participant capital availability and interest level. These project files often  included the different iterations of project development, but did not clearly identify the final reported  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 122 of 296   83  project energy savings and analysis documentation. Cadmus contacted the participants regarding these  measures, but the lack of clarity sometimes caused them to be confused and dismayed.  3.3.2. Prescriptive  Cadmus evaluated savings for a sample of sites across eight prescriptive programs and the Renewables  Program. Table 61 and Table 62 show our evaluated results by program.   Table 61. Evaluated Results for PY 2012‐PY 2013 Nonresidential Prescriptive Sample ‐ Combined States  Program  Number of  Measure  Installations  Evaluated  Sample  Gross Savings (kWh) Realization  Rate Reported Evaluated  Prescriptive Commercial Clothes  Washer 2 0 N/A N/A N/A  Prescriptive Commercial Windows  and Insulation 97 3 1,866 1,168 63%  Prescriptive Food Service 154 3 11,136 16,470 148% Prescriptive Green Motors Rewind 35 1 2,254 1,376 61% Prescriptive Lighting 4,784 19 3,150,101 2,582,336 82% Prescriptive Motor Controls HVAC 24 3 1,069,027 1,035,447 97% Prescriptive PC Network Controls 3 1 21,000 0 0% Prescriptive Standby Generator  Block Heater 42 1 1,849 1,849 100%  Renewables 11 0 N/A N/A N/A Total 5,152 31 4,257,233 3,638,646 85%   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 123 of 296   84  Table 62. Evaluated Results for PY 2013 Nonresidential Prescriptive Sample – Idaho Only43  Program  Number of  Measure  Installations  Evaluated  Sample  Gross Savings (kWh) Realization  Rate Reported Evaluated  Prescriptive Commercial Windows  and Insulation 4 0 N/A N/A N/A  Prescriptive Food Service 17 0 N/A N/A N/A Prescriptive Green Motors  Initiative 15 1 2,254 2,208 98%  Prescriptive Lighting 593 4 1,158,327 666,631 58% Prescriptive Motor Controls HVAC 4 0 N/A N/A N/A Prescriptive Standby Generator  Block Heater 1 0 N/A N/A N/A  Renewables 1 0 N/A N/A N/A Total 635 5 1,160,581 668,839 58%   Overall, the prescriptive programs’ analysis achieved a level of 90/17 confidence and precision. Cadmus  identified several necessary adjustments to the reported savings for the prescriptive programs. These  calculations often rely on reported equipment and operations data, which may vary from the  parameters identified during on‐site verification visits and metering.   Our adjustments decreased savings by 10%. The typical adjustments were to correct equipment  efficiency, fuel type, operating schedules, and/or operating parameters as described below:  • Cadmus used lighting logging and verification data to confirm or adjust operating hours for  lighting projects. These adjustments, in addition to those made based on verified fixture counts,  reduced or increased energy savings by varying amounts.  • Avista implementation staff made a data entry error on one census lighting project. The  calculation workbook listed 646 baseline fixtures listed instead of 64. This data entry error  significantly overestimated baseline consumption, and the resulting realization rate was 3%.  However, Avista paid the correct incentive for the project.  • For one motor controls HVAC project, Avista provided incentives for two pump VFDs. One of the  pumps was redundant, as only one is operating at any given time. The realization rate for this  project was 50%.   • One food service equipment refrigerator had a larger volume than reported, which increased  savings. The resulting realization rate was 157%.  • Cadmus evaluated one PC network controls project. The participant installed the system in 2009  and applied for an incentive in December 2009. The project files show that Avista was still                                                               43 Avista did not install any measures in either the Prescriptive Clothes Washer or PC Network Control programs in  Idaho in 2013. Therefore, we omitted those two programs from the table.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 124 of 296   85  attempting to obtain output reports from the control system to verify savings during 2011 and  2012. The incentive was approved in early 2012. Cadmus contacted the facility in October 2012,  but learned the participant had deactivated the PC network control system. As a result, we did  not assign any savings for this project (a realization rate of 0%).  3.3.3. Energy Smart Grocer  Cadmus performed on‐site or metering visits at 26 Energy Smart Grocer Program projects, which  represented a mixture of refrigeration case lighting and refrigeration equipment measures. We  calculated an overall realization rate for all PY 2012 and PY 2013 projects in Idaho and Washington, then  applied the resulting realization rate to the savings for each state. Table 63 lists the number of projects  and reported savings for the two measure types we evaluated. Table 64 shows our evaluated results for  the program by state.  Table 63. Energy Smart Grocer Program Measure Types and Projects Evaluated  Measure Type  Idaho Washington Total  Evaluated  Projects  Reported  Savings  (kWh)  Evaluated  Projects  Reported  Savings  (kWh)  Evaluated  Projects  Reported  Savings  (kWh)  Case Lighting 2 88,535 9 24,012 11 112,547 Industrial Process 6 477,441 8 972,020 14 1,449,461 Total 8 565,976 17 996,032 25 1,562,008   Table 64. Evaluated Results for Nonresidential Energy Smart Grocer Program Sample  State  Total PY 2012‐  PY 2013  Measure  Installations  Evaluated  Sample  Gross Reported  Sample Savings  (kWh)  Gross Evaluated  Sample Savings  (kWh)  Sample  Realization  Rate  Idaho 191 8 565,976 503,604 89% Washington 485 17 996,032 1,012,166 102% Total 676 25 1,562,008 1,515,770 97%   Overall, the Energy Smart Grocer analysis achieved a level of 90/5 confidence and precision. Cadmus  identified several necessary adjustments to the reported savings for the Energy Smart Grocer Program.  These calculations often rely on reported equipment and operations data, which may vary from the  parameters identified during on‐site verification visits and metering.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 125 of 296   86  Our adjustments decreased savings by 5%. The typical adjustments were to correct equipment  efficiency, operating schedules, and/or operating parameters as described below:  • At one large site, we found that floating head pressure controls were not enabled on the  medium temperature rack. Energy management system (EMS) data showed that the controls  had not been in operation for at least three weeks, but it could easily have been longer as three  weeks is the limit of the EMS trending history. The reduction in energy savings resulted in a 51%  realization rate.  • Cadmus applied a PECI benchmarking work paper44 to evaluate savings for several doors added  to medium temperature walk‐in cases. The adjustment resulted in a decrease in electricity  savings, for a realization rate of 50%.  • Cadmus found variation in actual installed LED case lighting quantities during site visits at two  retail chain stores. The stores installed fewer low output LED case lights and more high output  LED case lights than reported. This increased savings, and the resulting realization rate was  112%.  3.3.4. Site Specific  Cadmus performed site visits at 85 site‐specific projects, which represent a variety of measure types.  Cadmus calculated an overall realization rate for all projects in Idaho and Washington, then applied the  resulting realization rate to the savings for each state. Table 65 lists the number of projects and reported  savings for the different measure types we evaluated. Table 66 shows our evaluated results for the  program by state.  Table 65. Site‐Specific Measure Types and Projects Evaluated  Measure Type  Idaho Washington Total  Evaluated  Projects  Reported  Savings  (kWh)  Evaluated  Projects  Reported  Savings  (kWh)  Evaluated  Projects  Reported  Savings  (kWh)  Site‐Specific HVAC 10 1,345,068 20 4,708,338 30 6,053,406 Site‐Specific Lighting 8 1,990,605 17 6,766,338 25 8,756,943 Site‐Specific Other 4 3,460,866 16 2,864,862 20 6,325,728 Site‐Specific Shell 5 149,317 5 359,772 10 509,089 Total 27 6,945,856 58 14,699,310 85 21,645,166                                                                44  http://rtf.nwcouncil.org/meetings/2011/0830/WP_PECIREF_CA%20DRAFT.pdf  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 126 of 296   87  Table 66. Evaluated Results for Nonresidential Site‐Specific Sample  State  Total PY 2012‐  PY 2013  Measure  Installations  Evaluated  Sample  Gross Reported  Sample Savings  (kWh)  Gross Evaluated  Sample Savings  (kWh)  Sample  Realization  Rate  Idaho 214 27 6,945,856 7,401,914 107% Washington 434 58 14,699,310 14,024,358 95% Total 648 85 21,645,166 21,426,272 99%   Overall, the Site‐Specific Program achieved a level of 90/10 confidence and precision. Cadmus identified  many adjustments to Site‐Specific Program project reported savings. Site‐specific projects tend to be  more complex, with energy‐savings parameters and impacts that are more difficult to estimate. In  addition, the calculations often rely on participant‐supplied building, equipment, and operations data,  which may vary from parameters identified during an on‐site verification visit.   In aggregate, the adjustments noted by Cadmus increased savings by 1.5%, driven primarily by the high  realization rate for lighting projects.   Typical adjustments made to the savings values included corrections to equipment efficiency, operating  schedules, temperature setpoints, and building parameters. Cadmus also identified errors in simulation  models and calculation estimates, which resulted in adjustments. Specific adjustments are identified by  major measure category below.  Site‐Specific HVAC Adjustments  • Cadmus determined that Avista overestimated cooling savings for one project. We applied an  equivalent full load hours algorithm supported by RTF analysis. This resulted in lower savings,  for a realization rate of 41%.  • Avista adjusted the furnace calculator on one project to calculate heat pump savings, and the  resulting values were too high. The result appears to account for the per‐unit consumption  instead of energy savings. Cadmus benchmarked the results against ENERGY STAR, and used the  more conservative value. This led to a 14% realization rate.  • Cadmus conducted a utility billing analysis on one small heat pump project, which revealed no  electricity savings resulting from the project and resulted in a realization rate of 0%.   • The heating load appeared to have been overestimated on two large, partially‐occupied,  multifamily new construction projects. The utility billing data showed an average 65% of  expected consumption when normalized to full occupancy.  • Cadmus engineers found issues with simulation modeling by one contractor on four projects.  The models had an excessive portion of simulation hours outside of the throttling range. The  unmet load hours outside the throttling range indicate zones in the model, which do not receive  sufficient heating or cooling. This value should be less than 5% (as recommended by the U.S.  Green Building Council's Leadership in Energy and Environmental Design). Larger values call the  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 127 of 296   88  integrity of the model into question. These four evaluated projects had unmet load hour issues  ranging from 10.36% to 99.9% for any system zone outside throttling range. However, the  contractor had calibrated the models to the utility billing data. Overall, the energy savings and  model energy consumption appeared to be within a reasonable range. An example of the issue  from an eQuest simulation output file is shown in Figure 16.   Figure 16. eQuest Output File Showing Throttling Range Issue      Site‐Specific Lighting Adjustments  Cadmus evaluated a non‐census sample of site‐specific lighting projects using a combination of light  logging and verification data. On average, the results indicated reasonable reported values, and the  measure category had a realization rate of 98%.  • Cadmus evaluated the largest project (with 2,857,210 kWh of reported savings) through  extensive verification and light logging. The evaluated results were nearly identical to Avista's  reported values, resulting in a 100.5% realization rate.   • On one hotel project, Avista assumed 25 operating hours per week for wall sconces. Light  logging revealed that the fixtures were never turned off. This increased the baseline and retrofit  energy consumption. Therefore, it also increased energy savings, resulting in a 306% realization  rate.  • On one small new construction project, the installed lighting power density exceeded code  requirements; therefore, no savings could be achieved and the realization rate was 0%.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 128 of 296   89  Site‐Specific Other Adjustments  • Cadmus found that Avista applied an incorrect baseline for a refrigerated dryer on a compressed  air application. The baseline listed a desiccant dryer, which would actually consume far more  energy than Avista estimated. The refrigerated dryer is the industry standard, and typically  represents the baseline. Thus, no savings were achieved for this project.  • Cadmus metered two industrial process motor projects and one compressed air project, and  accepted Avista's metering data for baseline energy consumption. Our metering data indicated  lower retrofit energy consumption than Avista's retrofit data. This would increase energy  savings. We compared the production data for both periods, and could not reconcile the  difference in energy consumption based on that data. We therefore combined the Avista and  Cadmus retrofit metering data to establish the normalized retrofit energy consumption. The  realization rate for these three projects was 86%.  • Cadmus adjusted savings for a small refrigeration circulation pump project to match actual  operating hours. This resulted in a reduction in energy savings, with a realization rate of 33%.   • Cadmus evaluated the remaining site‐specific other projects using a combination of utility billing  and verification data. On average, the results indicated that the achieved energy savings were  slightly less than the reported values.  Site‐Specific Shell Adjustments  • One site‐specific shell project had low evaluated savings based on the initial calculation  methods. Avista funded the switch from electric resistance to natural gas heating, but did not  update the shell calculator with new fuel, and calculated shell savings in terms of electricity. The  resulting realization rate was 35%.  • Cadmus performed a site visit at one school with two site‐specific shell projects. We found that  the site turned off their HVAC system completely during the summer months when school was  not in session. Avista based its energy‐savings estimate on the assumption that air conditioning  would operate during the summer months. This required an adjustment to reduced energy  savings, with a resulting realization rate of 34% for both projects combined.  Cadmus evaluated the remaining site‐specific shell projects using verification data with the applicable  Avista savings calculators. In general, Cadmus found that the reported shell quantities and properties  did not vary much from verified values, and the savings calculators produced reasonable results. The  remaining results indicated that the achieved energy savings were equal to the reported values.  3.3.5. Extrapolation to Program Population  For our evaluation of the nonresidential electric programs, we selected sites that could provide the most  impactful information. We designed the site visits to achieve a statistically valid sample for the major  strata, as discussed previously. For measures in the random (non‐census) sample, we calculated  realization rates (the ratio of claimed‐to‐verified savings) and applied these to the remaining non‐ sampled sites. We did not apply measure‐level realization rates to the census population. These  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 129 of 296   90  realization rates are weighted averages, based on the random verification sample and using the  following four equations.  We calculated realization rates for each individual site in the sample based on measure type:  isiteatjmeasureforClaimed VerifiedRR ij ij ij ;=   Where:  RR = Realization rate  i = Sample site   j = Measure type   Then we calculated the realization rates for the measure types using the ratio of the sum of verified  savings to the sum of claimed savings from the randomly selected sample for each measure type:  sitessampleallacrossjmeasureforClaimed Verified RR i i i i j ;∑ ∑=   We calculated the population‐verified savings for non‐census projects by multiplying the measure type  realization rate from the random sample by the claimed savings for the non‐census population of each  measure type:  populatiomeasureinsitesallacrossjmeasureforClaimedxRRVerified k kj k k ;∑∑=   Where:  k = Total population for measure type j  Finally we added the claimed and verified savings from census stratum measures to calculate the total  reported and verified savings for each program. The program realization rate is the ratio of all verified to  all claimed savings:  )(;measuresandsitesallpopulationtheforClaimed Verified RR k k k k l ∑ ∑ =   Where:  l = Total program population  Cadmus summed these values to determine the total adjusted evaluated savings and program‐level  realization rates for the programs as a whole and for Idaho and Washington, as shown in Table 67 and  Table 68. The overall portfolio gross realization rate was 97%.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 130 of 296   91  Table 67. PY 2012‐PY 2013 Electric Gross Program Realization Rates – Combined States  Program Gross Sample Savings (kWh) Realization  Rate*  Gross Program Savings (kWh)  Reported Evaluated Reported Evaluated  Prescriptive 4,257,233 3,638,646 95%6,791,118 6,448,089 Energy Smart Grocer 1,562,008 1,515,770 92% 22,560,559 20,652,917 Site‐Specific HVAC 6,053,406 5,229,048 91%3,367,537 3,053,079 Site‐Specific Lighting 8,756,943 9,141,338 110%9,596,933 10,589,164 Site‐Specific Other 6,325,728 6,659,011 100%4,693,462 4,696,253 Site‐Specific Shell 509,089 396,875 78% 82,037 63,954 Total 27,464,407 26,580,688 97%47,091,646 45,503,456 * Realization rates vary from the ratio of evaluated to reported savings due to the impact of census‐level projects.   Table 68. PY 2013 Electric Gross Program Realization Rates – Idaho Only  Program Gross Sample Savings (kWh) Realization  Rate*  Gross Program Savings (kWh)  Reported Evaluated Reported Evaluated  Prescriptive 1,160,581 668,839 86%8,079,107 6,978,966 Energy Smart Grocer 449,443 397,978 95%1,753,808 1,672,139 Site‐Specific HVAC 759,054 666,597 89%1,104,062 977,838 Site‐Specific Lighting 1,842,534 2,280,518 113%3,483,430 3,919,299 Site‐Specific Other 2,381,238 2,175,691 96%3,111,738 2,992,445 Site‐Specific Shell 113,857 67,833 78% 70,108 54,655 Total 6,706,707 6,257,456 94%17,602,253 16,595,342 * Realization rates vary from the ratio of evaluated to reported savings due to the impact of census‐level projects.   3.4. Nonresidential Conclusions  Cadmus evaluated 142 of 6,476 measures installed through the nonresidential programs, representing  16% of reported savings.  In general, Cadmus determined that Avista implemented the programs well. The overall portfolio  achieved a 97% realization rate when comparing gross evaluated savings to gross reported savings. In  Idaho, the PY 2013 nonresidential portfolio achieved a 94% realization rate.  Cadmus identified the following key issues that led to adjusted energy savings:  • Metering on post‐installation power consumption for several industrial process measures  indicated that the evaluated savings varied from the reported value.  • Some participants did not operate the incented equipment correctly or did not complete the  improvements expected for the measure.  • Some participant post‐installation heating or cooling loads did not achieve the level of projected  consumption, which reduced energy savings.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 131 of 296   92  • Simulation models sometimes did not accurately represent the actual as‐built building or system  operation.  • There were instances where thorough analysis of energy‐savings calculations provided by  participants or third‐party contractors was lacking.  • Some projects had data entry errors in characterizing building or measure performance.  3.5.  Nonresidential Recommendations  Cadmus recommends that Avista continue to offer incentives for measure installation through the  evaluated programs. We have the following recommendations for improving program energy‐savings  impacts and evaluation effectiveness:  • Create a quality control system to double‐check all projects with savings over 300,000 kWh.   • Avista may want to consider tracking and reporting demand reduction to better understand  measure load profiles and peak demand reduction opportunities.  • Update prescriptive measure assumptions and sources on a regular basis.  • Streamline its file structure to enable reviewers to more easily identify the latest  documentation.  • Continue to perform follow‐up measure confirmation and/or site visits on a random sample of  projects (at least 10%).  • Consider flagging sites for additional scrutiny when the paid invoice does not include installation  labor as it may indicate that the work was not yet performed.  • Avista may consider adding a flag to their tracking database to automatically calculate the unit  of energy savings per dollar (kWh/$ or therm/$) to provide a quick check to identify extreme  outliers.   • In the case of redundant equipment, Avista may want to consider incenting pump projects  through the Site‐Specific Program to more accurately characterize the equipment operating  hours.  • Avista may want to set minimum standards for modeling design guidelines. The Energy Trust of  Oregon provides an example on their website:  http://energytrust.org/commercial/incentives/construction‐renovation‐ improvements/custom/modeled‐savings.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 132 of 296   93  4. Low Income Impact Evaluation  4.1. Introduction  Cadmus conducted a statistical billing analysis to determine adjusted gross savings and realization rates  for energy‐efficient measures installed through the low income weatherization program in PY 2013.  Cadmus examined energy savings at the household or participant level, rather than at the measure level.  We performed a billing analysis of PY 2012 participants who had a full year of energy consumption data  both before (2011) and after (2013) the weatherization period. Then Cadmus applied PY 2012 billing  analysis results to PY 2013 participants.   To estimate energy savings resulting from the program, Cadmus used a pre‐ and post‐installation,  combined CSA and PRISM approach, using monthly billing data. We analyzed energy‐savings estimates  for program participants and ran a series of diagnostic tests on the data. These tests included reviewing  savings by pre‐consumption usage quartile, checking to ensure households have a sufficient amount of  billing data, and creating a graphical outlier analysis. Below is a detailed discussion of the regression  model used for this billing analysis along with resulting savings.  4.1.1. Program Description  Five components, listed in Table 69, are included in the low income weatherization program. Local  Community Action Partners (CAPs) within Avista’s Idaho service territory implement the projects. CAPs  holistically evaluate homes for energy‐efficiency measure applicability, combining funding from different  utility and state/federal programs to apply appropriate measures to a home, based on the results of a  home energy audit.   Table 69. Low Income Weatherization: PY 2013 Electric‐Efficiency Installations by Component*  Low Income Program  Component Measure Description Measure  Installations  Shell/Weatherization Insulation, window/door, air infiltration, programmable thermostat 270 Fuel Conversion* Electric furnace, heat pump,or water heater replacement 36 Hot Water Efficiency High‐efficiency water heater replacement 0 ENERGY STAR Appliance High‐efficiency refrigerator replacement 0 HVAC Efficiency High‐efficiency heat pump replacement, variable speed motor 2 * Avista considers (and reports) fuel conversion measures in its portfolio as electric‐saving measures.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 133 of 296   94  4.2. Data Collection and Methodology  Cadmus obtained impact evaluation data from multiple sources, including:  • Program participant database: Avista provided information regarding program participants and  installed measures. Specifically, these data included a list of measures installed per home and  the reported savings from each completed installation. The data did not, however, include the  quantity of measures installed (such as the total square feet of installed insulation) or per‐unit  savings estimates.   • Billing records: Avista provided participant meter records from January 2011 through December  2013.  • Weather data: Cadmus collected Idaho weather data from NOAA for three representative  stations, drawn for the corresponding time period.  4.2.1. Sampling  Cadmus began the analysis with a census of PY 2012 participants. We then screened the PY 2012  participant data for specific criteria (e.g., ensuring that it had sufficient monthly billing data, was not  classified as an outlier) for use in the final analysis. In all, we included 65 Idaho participants in the billing  analysis: 50 non‐conversion and 15 conversion participants. Cadmus defined a conversion customer as  any participant who received a new gas furnace or water heater.   4.2.2. Billing Analysis  Avista provided monthly billing data for all participants from January 2011 through December 2013.  Avista also provided the participant database, which contained participation and measure data for the  PY 2012 and PY 2013, detailing all gas and electric measures installed per home by CAPs.   Cadmus obtained daily average temperature weather data from 2011 to 2013 for the three NOAA  weather stations, representing all PY 2012 electric participant ZIP codes in Avista’s Idaho territory. From  daily temperatures, we determined base 65‐degree HDDs and CDDs for each station, then matched  billing data periods with the HDDs and CDDs from the station closest to each participant.  As we received billing data through December 2013, we could only perform the billing analysis for the  2012 program year. We defined the analysis pre‐period as 2011, before all participation installations  occurred, and defined the analysis post‐period as 2013, following all installations occurring in 2012. We  then applied the analysis results for PY 2012 participants to the PY 2013 participant population, thus  reporting overall impacts for PY 2013. Given consistency in delivery infrastructure, measure offerings,  and program design, using billing analysis and extrapolating evaluated impacts from the previous year to  2013 seems appropriate. Furthermore, performing billing analysis for whole‐house programs is  considered an industry best‐practice, cited in several evaluation protocols (IPMVP, UMP), allowing for  the utility to account for measure interaction, participant take‐back, and the effects of energy‐education  on participant usage behavior.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 134 of 296   95  To estimate energy savings from this program, Cadmus used a pre/post CSA fixed‐effects modeling  method using pooled monthly time‐series (panel) billing data. This modeling approach corrected for  differences between pre‐ and post‐installation weather conditions, as well as for differences in usage  consumption between participants (as the model included a separate intercept for each participant).  The modeling approach ensured that model savings estimates would not be skewed by unusually high‐ usage or low‐usage participants.   4.3. Data Screening and Modeling Approach  Cadmus conducted a series of steps to screen participant usage data, ensuring a clean, reliable dataset  for analysis.   4.3.1. General Screens  Cadmus used the following screens to remove accounts that could have skewed the savings estimation:  • Accounts with fewer than three months (90 days) of billing data, in either the pre‐ or post‐ period.  • Accounts with annual usage outside of reasonable bounds in either the pre‐ or post‐period (less  than 1,000 kWh or more than 50,000 kWh).  • Accounts that change electric usage between the pre‐ or post‐period by more than 90% (unless  for a conversion project).45  4.3.2. Weather Normalization Screens  To screen the data, Cadmus used PRISM‐like models to weather‐normalize pre‐ and post‐billing data for  each account, and to provide an alternate check on measure savings obtained from the CSA model. For  more detail on the model specification, see Appendix E.  Table 70 and Table 71 summarize non‐conversion and conversion account attrition, respectively, from  the screens listed above.                                                               45  Changes in usage of this magnitude are probably due to vacancies, home remodeling or addition, seasonal  occupation, or fuel switching. Changes of usage over a certain threshold are not expected to be attributed to  program effects and can confound the analysis of consumption.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 135 of 296   96  Table 70. Low Income Weatherization: Non‐Conversion Account Attrition  Screen Participants  Remaining  Percent  Remaining  Number  Dropped  Percent  Dropped  Original Electric Accounts  63 100%0 0% Participation in Pre/Post Period 61 97%2 3% Dropped in Merge with Billing Data 61 97%0 0% Insufficient Pre‐ and Post‐Period Months 60 95%1 2% Insufficient Pre‐ and Post‐Days 60 95%0 0% Low or High Usage in Pre‐ or Post‐Period 60 95%0 0% Changed Usage Between Pre and Post (>  90%) 59 94% 1 2%  PRISM Screen: Low R‐Squared, Low Heating  Usage 59 94% 0 0%  Account‐level inspection of pre/post 12‐ month usage (e.g., vacancies, anomalies) 50 79% 9 14%  Final Analysis Group 50 79%13 21%   Table 71. Low Income Weatherization: Conversion Account Attrition  Screen Participants  Remaining  Percent  Remaining  Number  Dropped  Percent  Dropped  Original Electric Accounts  18 100%0 0% Dropped in Merge with Billing Data 18 100%0 0% Insufficient Pre‐ and Post‐Period Months 18 100%0 0% Insufficient Pre‐ and Post‐Days 18 100%0 0% Low or High Usage in Pre‐ or Post‐Period 18 100%0 0% Changed Usage Between Pre and Post (>  90%) 18 100% 0 0%  PRISM Screen: Low R‐Squared, Low Heating  Usage 18 100% 0 0%  Account‐level inspection of pre/post 12‐ month usage (e.g., vacancies, anomalies) 15 83% 3 17%  Final Analysis Group 15 83% 3 17%    4.3.3. Conditional Savings Analysis Modeling Approach  To estimate energy savings from this program, Cadmus used a pre/post CSA fixed‐effects modeling  method, which uses pooled monthly time‐series (panel) billing data. The fixed‐effects modeling  approach corrects for differences between pre‐ and post‐installation weather conditions, as well as for  differences in usage consumption between participants with a separate intercept for each participant.  This modeling approach ensured that model savings estimates are not skewed by unusually high‐usage  or low‐usage participants. For more detail on the model specification, see Appendix E.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 136 of 296   97  4.4. Results and Findings  This section presents the evaluated savings for the program derived from the billing analysis. Several  detailed tables are presented to contextualize the billing analysis impacts, including measure  distributions and some benchmarking comparisons.  4.4.1. Billing Analysis Results  Table 72 summarizes model savings results for electric non‐conversion and conversion participants of  the low income weatherization program.   Table 72. Electric Model Savings Summary  Participant  Type n PRENAC  Change in  Consumption  (kWh)  Savings as  Percent of  Pre‐Usage  Relative  Precision  at 90%  Savings  Lower 90%  (kWh)  Savings  Upper 90%  (kWh)  Non‐Conversion 50 19,098 2,776 15%±30%1,943 3,609 Conversion 15 16,859 10,980 65%±19%8,890 13,071   The model savings averaged 2,776 kWh for each non‐conversion participant and 10,980 kWh for each  conversion participant. In this analysis, Cadmus determined an overall conversion estimate instead of  equipment‐specific estimates due to the small sample size of furnace‐only and water heater‐only  participants at the state level.   Table 73 provides a distribution of the electric measures in the final model that Avista funded for  participants. This distribution reveals a different mix of measures for the two participant groups.  Specifically, non‐conversion participants had higher installation percentages of shell measures (e.g.,  doors, windows, wall insulation).   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 137 of 296   98  Table 73. Measure Distribution of Final Model Sample by Participant Type  Measures Non‐Conversion Conversion  Count Percent Count Percent  Air infiltration controls 23 46%1 7% Windows 11 22%1 7% Doors 18 36%1 7% Floor insulation 14 28%0 0% Attic insulation 3 6%0 0% Duct insulation 11 22%1 7% Water heater replacement 13 26%0 0% Wall Insulation 1 2%0 0% T‐stat (no air conditioning) 0 0%7 47% Refrigerator replacement 0 0%0 0% Furnace replacement 0 0% 14 93% Furnace conversion 0 0% 14 93% Water heater conversion 0 0% 13 87% Sample (n) 50 100%15 100%   Statistical billing analysis results encompass all measure installations made at participant households,  including those not paid for through Avista’s program. Since local CAP agencies use a variety of funding  sources to implement this program, it is possible that participant homes received measures paid for by  federal, state, and/or other utility dollars. Specifically, Avista does not fund CFLs offered through the  program, which likely had a significant impact on the electric savings in participant homes.   4.4.2. Overall Program Results  Table 74 shows the realization rates for Idaho low income weatherization program participants.   Table 74. Low Income Weatherization: Electric Model Realization Rate Summary  Participant  Type n PRENAC  Model  Savings  (kWh)  Per  Participant  Reported  Savings (kWh)  Realization  Rate  Model  Savings as  Percent of  Pre‐Usage  Expected  Savings as  Percent of  Pre‐Usage  Non‐Conversion 50 19,098 2,776 3,059 91%15% 16% Conversion 15 16,859 10,980 2,994 367%65% 18%   Non‐conversion participants had a realization rate of 91%. There were two PY 2013 participants who  received electric resistance to electric heat pump conversions, which were not represented in the billing  analysis sample.  Cadmus used Avista’s listed database savings for the heat pump conversion measures and additional  non‐conversion measures for this customer. Table 75 presents the PY 2013 population savings separated  by participant type.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 138 of 296   99  Table 75. Low Income Weatherization: Total PY 2013 Evaluated Savings  Participant Type Total  Participants  Model  Savings per  Participant  Total  Evaluated  Savings (kWh)  Total  Expected  Savings (kWh)  Realization  Rate  Non‐Conversion 100 2,776 179,628 197,945 91% Conversion 23 10,980 309,964 84,513 367% Heat Pump Replacement* 2 N/A 10,309 10,309 N/A Overall 125 N/A 499,901 292,767 171% * Avista funded high‐efficiency electric heat pump replacements that were not included in the billing analysis  participant sample. For these measures, Cadmus used the claimed savings values listed in the Avista database.    Cadmus calculated the total program savings by multiplying the modeled realization rates by the  claimed ex ante savings.   4.5. Comparison to Previous Billing Analysis  The results from the PY 2012 billing analysis indicate greater energy savings than had resulted from the  PY 2010 billing analysis. Table 76 compares the model results from Cadmus’ PY 2010 and PY 2012 billing  analyses.46   Table 76. Low Income Weatherization: Comparison of Model Results by Participant Group and Year  Participant  Type  Program  Year n PRENAC  Model  Savings  (kWh)*  Average Reported  Savings Per  Participant (kWh)  Realization  Rate  Model  Savings as  Percent of  Pre‐Usage  Reported  Savings as  Percent of  Pre‐Usage  Non‐ Conversion  2010 73 15,773 1,602 3,626 44% 10% 23% 2012 50 19,098 2,776 3,059 91% 15% 16% * The model results are not statistically different at the 0.05 level of significance.   One factor contributing to increased modeled energy savings between PY 2010 and PY 2012 is a change  in the distribution of electric‐saving measures that Avista funded. Avista funded a greater number of  high energy‐saving measures in PY 2012 than in PY 2010 for non‐conversion participants, including air  infiltration controls, floor and duct insulation, and doors. Additionally, Avista began funding wall  insulation and water heater replacements in Idaho. Figure 17 shows the percentage of Avista‐funded  measures for non‐conversion participants for both program years.                                                                46  No comparison is provided for fuel conversion measures, as Avista added these measures to the Idaho  program after the previous evaluation.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 139 of 296   100  Figure 17. Percent of Installed Measures for Non‐Conversion Model Participants by Program Year      The realization rates are also substantially higher in PY 2012 than in previous years. As explained above,  there was an increase in the installation of building shell measures during PY 2012. The difference in  realization rates is also partially due to the reported measure‐level savings. Table 77 presents a  comparison of the average kWh savings between PY 2011 and PY 2012‐PY 2013 for both non‐conversion  and conversion customers.  Table 77. Comparison of Average Reported Measure‐Level Savings Between Program Years*  Measures PY 2011 (kWh) PY 2012‐PY 2013 (kWh)  Air infiltration controls 1,871 458 ASHP replacement (conversion) N/A 3,932 Attic insulation 1,478 589 Doors 287 313 Duct insulation 5,485 1,457 Floor insulation 4,408 1,874 Furnace replacement (conversion) N/A 2,555 High‐efficiency water heater replacement 299 117 Wall insulation 3,466 1,075 Water heater replacement (conversion) N/A 1,148 Windows 2,432 1,255 * These savings values reflect full program years, not the analysis sample.   All but one measure (doors) experienced a decrease in average reported savings between PY 2011 and  PY 2012‐PY 2013. The measures with the largest change in reported savings were air infiltration, attic  insulation, wall insulation, duct insulation, and floor insulation.   55% 0% 0% 32% 3% 38% 53% 62% 52% 6% 6% 56% 8% 44% 36% 90% 0% 20% 40% 60% 80% 100% Windows Water heater replacement Wall insulation Floor insulation Duct insulation Doors Attic insulation Air infiltration controls PY 2012 PY 2010 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 140 of 296   101  An additional factor may account for changes in modeled savings: non‐Avista funded measures installed  by agencies through the program.  4.6. Benchmarking  To place Avista program savings estimates in context, we compared billing analysis results from other  low income program efforts across the country.47 This section provides two metrics for comparing  Avista’s program savings to other similar programs. First, Figure 18 compares the percentage of energy  savings, relative to PRENAC, of Avista’s program and a number of other low income weatherization  programs, based on electric billing analyses. This metric allows for comparing programs given variation  in weather, costs, program delivery, and measure offerings.   Figure 18. Savings Percentage of Pre‐Period Consumption*    * This figure reflects savings for non‐conversion participants.    Figure 19 presents the absolute energy savings from low income programs; this is a second metric for  comparing Avista’s non‐conversion results to other programs. Absolute estimates do not use PRENAC,  but rather show savings that are directly attributable to the program.                                                                47  The comparable studies include Oak Ridge National Laboratory’s (ORNL) Meta‐evaluation of Low Income  Weatherization Programs, the People Working Cooperatively Low Income Weatherization Program in Ohio  (MW), the Pacific Power (PP) Low Income Weatherization Program in Washington, the Rocky Mountain Power  (RMP) Low Income Weatherization Program in Idaho, the Energy Smart low income program in Oregon (OR).  12% 11% 11% 9% 11% 10% 15% 0% 2% 4% 6% 8% 10% 12% 14% 16% PP WA (09‐11) RMP ID (07‐09) OR Energy Smart  (2007) MW Utility (2009) ORNL (metaeval.) Avista ‐ID (PY10‐11) Avista  ‐ID (PY12‐13) Percent kWh of PRENAC Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 141 of 296   102  Figure 19. Average Per‐Participant Savings for Non‐Conversion Participants      The realization for Idaho conversion participants appeared high, at 367%. When comparing PY 2013  average savings for furnace and water heater conversions in Avista’s tracking data, average savings for  Idaho were 50% of the Washington estimates for these measures. By comparison, billing analysis results  for Washington conversion participants over the last two studies are consistent with the modeled  savings here for Idaho, coming in at 8,394 kWh and 10,397 kWh, respectively.  4.7. Low Income Conclusions  Compared to PY 2010, Avista’s PY 2012 low income program demonstrated an increase in average  electric savings per participant, in addition to an increase in non‐conversion program realization rate  (from 44% to 91%). Several factors may have contributed to the increase in non‐conversion participant  savings, including: (1) an increased frequency of installing high‐saving measures (e.g., shell) in the  evaluation period, (2) changes in agency delivery protocols or energy‐saving installations made with  non‐utility funding, and (3) exogenous effect (e.g., economic, rate changes) that may have occurred  simultaneous to program activity. One factor contributing to higher realization rates are lower average  reported savings occurring in the evaluation period compared to previous years.   While we cannot compare the results of the conversion customer impacts to previous evaluations in  Idaho, average savings are comparable to those observed in the Washington low income program  through past billing analyses.  2,432 1,972 1,254 987 2,153 1,602 2,776 0 500 1,000 1,500 2,000 2,500 3,000 PP WA (09‐11) RMP ID (07‐09) OR Energy Smart  (2007) MW Utility (2009) ORNL (metaeval.) Avista ‐ID (PY10‐11) Avista  ‐ID (PY12‐13) kWh Savings per Participant Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 142 of 296   103  4.8. Low Income Recommendations  Cadmus recommends the following enhancements in order to improve program impact results:   • Avista should use a control or comparison group in future billing analyses for use in analyzing  the treatment group of program participants. This would allow controlling for exogenous factors  (e.g., macroeconomic, rate changes, technological trends) that could result in trends that affect  consumption. Controlling for these trends using a control/comparison group is a robust and  defensible method for estimating accurate energy‐savings impacts.  • Avista should consider options for increasing analysis sample sizes (such as using combined  models with participants in either state program). Smaller sample sizes in state‐specific models  attributed to decreased precision in the PY 2012 model estimates. Increasing the sample sizes  by using a combined state model in future evaluations will mitigate this cause of decreased  precision.   • Avista should obtain a full list of weatherization measures from agencies. The billing analysis  results do not allow Cadmus to disaggregate energy savings specific to Avista‐funded measures.  In addition, a complete list of participants’ installed measures would allow Cadmus to conduct a  measure‐level billing analysis specific to measure types. This granularity could help Avista  improve future program offerings and help fully characterize the energy savings modeled  through billing analysis.  • Avista should include high‐use customers in program targeting. While prioritization guidelines  for targeting low income weatherization participants are set at the federal level, some utilities,  for targeting purposes, actively track customer usage and provide agencies with lists of  customers that have particularly high energy consumption.   Notably, DOE protocols list high‐energy consumption as a factor allowed in participant  prioritization. In such cases, along with other targeting criteria (e.g., families with children,  senior citizens), agencies may incorporate energy‐consumption characteristics into their  program participant prioritization. Not only would weatherizing high‐use customers likely result  in higher energy savings, but could provide these customers with some financial relief from their  higher energy bills caused by their housing characteristics.   Avista should identify high‐usage customers while controlling for factors that contribute to  consumption (e.g., square footage, income, numbers of people per household).  Given reductions in federal funding for weatherization and associated reduced agency capacities  resulting in more limited leveraging opportunities, Avista can lead new efforts for the continued  delivery of energy‐savings resources to low income residential customers. Potential exists to  secure cost‐effective energy savings through high‐usage targeting, while continuing to support  weatherization for income‐qualified customers. Efficient targeting balances efforts to provide  whole‐house weatherization, and allows for leveraging the agency network as a resource for  outreach and delivery.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 143 of 296   104  • Avista should track and compile additional data from agency audits. These data include  information on primary and secondary heating and cooling, and on the size of a home. As an  inexpensive alternative to gas heat, gas customers may turn to electric room heaters and wood  stoves, reducing the impacts of installed weather‐sensitive measures (e.g., insulation). Collecting  information on customers’ primary heating usage during weatherization would lead to more  reasonable savings estimates.   Cadmus recommends that Avista work with CAP agencies to develop explicit, on‐site tracking  protocols for collecting information on participant heating sources. The CAPs should collect the  following information to better inform heating and cooling sources:  ƒ Visual inspections of all heating equipment found on site;  ƒ Participant‐reported primary and supplemental heating sources used;  ƒ Quantities of secondary heating, if applicable (e.g., numbers of electric room heaters); and  ƒ Any indicators suggesting discrepancies between actual and reported primary heating.  • Avista should consider performing quantitative, non‐energy benefit analyses. Cadmus  recommends that Avista consider pursuing additional analyses aimed at quantifying non‐energy  benefits associated with low income weatherization, applicable to the Total Resource Cost (TRC)  test. Specifically, analyses of economic impacts and payment pattern improvements (including  reduced arrearages and collections costs) can provide program stakeholders with the monetized  value of energy‐efficiency measures. Other Northwest utilities have used such analyses to report  low income weatherization cost‐effectiveness (in Idaho and Washington). Standard cost‐ effectiveness TRC testing accounts for all program costs and only includes energy savings as a  program benefit. The TRC test omits some non‐energy benefits genuinely experienced by  participants, such as decreased mortality and morbidity, as well as environmental benefits such  as reduced emissions of carbon dioxide and other pollutants listed in the Clean Air Act.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 144 of 296   105  5. Portfolio Savings and Goals  5.1. Gross Portfolio Savings  The PY 2013 Idaho electric portfolio consisted of several sectors and many program delivery streams. In  total, the programs achieved a 102.7% gross realization rate and total evaluated savings of  25,899,345 kWh (Table 78).  Table 78. PY 2013 Idaho Gross Savings  Segment* Reported Savings  (kWh)  Gross Evaluated Savings  (kWh) Realization Rate  Residential 5,130,507 5,933,197 115.6% Nonresidential 17,602,253 16,595,342 94.3% Low Income 292,767 499,901 170.8% Residential Behavior 2,194,322 2,870,905 130.8% Total  25,219,849 25,899,345 102.7% * Note that Residential Behavior Program savings are inherently calculated as net, not gross.    5.2. NTG Adjustment  Cadmus evaluated NTG through customer self‐reports, using different methodologies and data sources  for the different programs, as detailed below.  5.2.1. No NTG Adjustment  The programs outlined below did not require a NTG adjustment, as the original savings analysis  methodology accurately reflected net market characteristics.   Low Income Weatherization  Traditionally, low income programs receive a 100% NTG as the participants are assumed unlikely to have  installed the incented measures on their own.   Simple Steps, Smart Savings and Geographic CFL Giveaway  The savings analysis methodology Cadmus used for Avista’s upstream and giveaway lighting programs  follows the RTF, which does not differentiate between gross and net savings but instead uses an  adjusted market baseline approach. For the various inputs to the savings calculation, Cadmus used  either direct RTF values or RTF methods with Avista‐specific data. To assign an additional NTG value to  these programs would, in effect, be double counting.  Residential Behavior  Cadmus analyzed the Residential Behavior Program using a randomly selected control group such that  the differences between groups net out any natural effect of what people would have done in absence  of the program, or because of the existence of the other Avista programs. The savings produced by this  method of analysis are inherently net and need no further adjustment.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 145 of 296   106  5.2.2. Residential NTG  Cadmus updated NTG values for the PY 2013 residential population. We determined freeridership and  participant spillover from 210 participating customers’ self‐reports during phone surveys performed in  Q1 2014. The methodology is consistent with that described in detail in Cadmus’ 2012 NTG report.48   We calculated nonparticipant spillover from 1,109 completed multi‐method General Population surveys  (395 of which were Idaho residents). We mailed 3,000 paper surveys to randomly selected residential  customers in both Idaho and Washington. These mailings included a website to complete the survey  online. Cadmus also called a subset of the sample with a traditional phone survey. This multi‐media  method helps reduce survey bias.   Cadmus followed a specific NTG methodology for the Second Refrigerator and Freezer Recycling  Program, as outlined in the program section above. Table 79 outlines the NTG components and resulting  program‐level NTG from our most recent round of analyses.  Table 79. Residential NTG   Program  Freeridership Participant  Spillover  Nonparticipant  Spillover NTG  ENERGY STAR Products 79%1.3%0.7% 23% Heating and Cooling Efficiency 72%0.0%0.7% 29% Weatherization/Shell 55%0.0%0.7% 46% Water Heater Efficiency 55%0.0%0.7% 46% Space and Water Conversions 62%0.0%0.7% 39%   Table 80 shows the NTG values and resulting net savings for Avista’s residential downstream programs  (36%), and a NTG for the residential sector overall (92%).                                                               48  Cadmus. Net‐to‐Gross Evaluation of Avista’s Demand‐Side Management Programs. June 2012.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 146 of 296   107  Table 80. Residential NTG and Net Savings  Program  Evaluated Gross  Savings (kWh) NTG Evaluated Net  Savings (kWh)  Second Refrigerator and Freezer Recycling 368,174 32% 117,699 ENERGY STAR Products 29,011 23% 6,760 Heating and Cooling Efficiency 144,480 29% 42,188 Weatherization/Shell 90,471 46% 41,436 Water Heater Efficiency 5,487 46% 2,513 Space and Water Conversions 506,078 39% 195,346 ENERGY STAR Homes* 12,550 74% 9,287 Subtotal 1,156,251 36% 415,229 Simple Steps, Smart Savings 4,750,306 100% 4,750,306 Geographic CFL Giveaway 26,640 100% 26,640 Residential Behavior 2,870,905 100% 2,870,905 Total 8,804,102 92% 8,063,080 *ENERGY STAR Homes NTG was not evaluated in 2013 due to small participation.  Value is from previous evaluation.  5.2.3. Nonresidential NTG  Cadmus surveyed PY 2013 participants in Q1 2014, following the methodology described in Cadmus’  2012 NTG report. Table 81 outlines the NTG components and resulting program‐level NTG.  Table 81. Nonresidential NTG   Program  Freeridership Participant  Spillover  Nonparticipant  Spillover NTG  Site‐Specific 30.4%0.1%0.8% 70.4% Prescriptive 9.1%0.0%0.8% 91.7% EnergySmart Grocer 14.3%0.0%0.8% 86.5%   Table 82 shows the resulting net savings for each program component. The nonresidential sector  exhibited a weighted nonresidential NTG of 81%.  Table 82. Nonresidential NTG and Net Savings  Program  Evaluated Gross  Savings (kWh) NTG Evaluated Net Savings  (kWh)  Site‐Specific 7,944,237 70.4%5,594,332 Prescriptive 6,978,966 91.7%6,396,222 EnergySmart Grocer 1,672,139 86.5%1,445,564 Total 16,595,342 81%13,436,118   5.3 Net Portfolio Savings  The portfolio achieved an overall NTG ratio of 85% and 21,999,099 kWh of net savings. Table 83 shows  evaluated gross and resulting net savings for Idaho’s PY 2013 DSM programs.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 147 of 296   108  Table 83. 2013 Idaho Net Savings  Sector Gross Evaluated  Savings (kWh) NTG Net Verified Savings  (kWh)  Residential 8,804,102 92%8,063,080 Nonresidential 16,595,342 81%13,436,118 Low Income 499,901 100%499,901 Total  25,899,345 85%21,999,099   5.4 IRP Goals Achievement  Table 84 shows net evaluated savings, compared to the IRP goal of 19,009,200 kWh. The IRP goals are  set at the portfolio‐level. In order to conduct sector‐level comparisons, Cadmus adopted the Avista  Business Plan goals by sector and applied those proportions to the IRP targets. PY 2013 achieved 115.7%  of the IRP target in Idaho with 21,999,099 kWh. Excluding the Residential Behavior Program savings,  Idaho still met the IRP goal, at 100.6% with 19,128,194 kWh. Table 85 shows Avista’s internal Business  Plan goal achievements.   Table 84. PY 2013 IRP Goal and Net Achieved Savings  Sector Savings Goal (kWh) Net Achieved (kWh) Achievement  Rate  Residential 7,697,009 8,063,080 104.8% Nonresidential 10,849,696 13,436,118 123.8% Low Income 462,495 499,901 108.1% Total  19,009,200 21,999,099 115.7%    Excluding Residential Behavior 19,009,200 19,128,194 100.6%   Table 85. PY 2013 Avista Business Plan Goal and Net Achieved Savings  Sector Savings Goal (kWh) Net Achieved (kWh) Achievement  Rate  Residential 8,547,340 8,063,080 94.3% Nonresidential 12,048,322 13,436,118 111.5% Low Income 513,589 499,901 97.3% Total  21,109,251 21,999,099 104.2%          Excluding Residential Behavior 21,109,251 19,128,194 90.6%   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 148 of 296   109  Appendix A: Residential Billing Analysis Model Specifications   Overview of the PRISM Approach  A site‐level modeling approach was originally developed for the PRISM software.49 In this model, the  NAC is estimated separately for each customer account, for both the pre‐ and post‐installation periods.  The weather normalization for each account and period relies on a longitudinal regression analysis. The  difference between the pre‐ and post‐program NAC represents the program‐related change in  consumption plus exogenous changes in consumption. Without a nonparticipant group this exogenous  change is not eliminated, but it is expected to be small for consumption over the three‐year evaluation  period, especially with respect to the larger change in consumption from conversion.   Model Specification  Cadmus fitted each account with specific degree‐day regression models, separately for the pre‐ and  post‐installation periods. We first normalized the monthly bills by the number of days in each billing  period to obtain the average daily consumption (ADC). Then we calculated the average temperature  during each utility billing period.   This degree‐day regression for each account is modeled as:  ADCHH αH βHAVGHDDHH γHAVGCDDHH SHH   Where:  ADCit = Average daily kWh or therm consumption for each customer ‘i’ during  billing month ‘t’  αι =  Participant intercept; represents the average daily kWh or therm base  load or the energy use for non‐space heating or cooling purposes  βι =  Participant slope; represents the change in energy use for a unit change  in the HDDs  AVGHDDit =  Base 65 average daily HDDs for customer ‘i’ in period ‘t’  γι =  Participant slope; represents the change in energy use for a unit change  in the CDDs  AVGCDDit =  Base 65 average daily CDDs for customer ‘i’ in period ‘t’  Cadmus used the results from the above estimation to compute the NAC for electricity:  NACH αH 365 β HNORMHDDH γHNORMCDDH                                                                49  Fels et al. 1995  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 149 of 296   110  Where:  NACi =  Normalized annual kWh or therm consumption for each customer ‘i’  αH =  The participant intercept; estimated from the above model  βH =  The participant heating slope; estimated from the above model  NORMHDDi =  Annual normal‐year HDDs (base 65) for customer ‘i’ in period ‘t’  γH =  The participant cooling slope; estimated from the above model  NORMCDDi =  Annual normal‐year CDDs (base 65) for customer ‘i’ in period ‘t’  Overview of the Regression Approach  Cadmus specified a conditional savings regression model with paired pre‐ and post‐participation  months. This is a pooled regression approach that combines all participants and time intervals for a  single measure group into a single regression analysis. The observations vary across both time and  individual accounts. This pooled approach is recommended for cases like this, where there is no  separate comparison group and where other energy‐efficiency measures are installed in homes.   Model Specification  Cadmus estimated a separate regression model for each of the groups. The model determined the ADC  of electricity of home ‘i’ in month ‘t’ as:  ADCHH DH τH βHHDDHH βHCDDHH βHHDDHH D D D D D HH βHCDDHH D D D D D HH βHPOSTHH βHPOSTHH HDDHH βHPOSTHH CDDHH βHPOSTHH D D D D D HH DHH   Where:  αi = Average daily base load energy use in home ‘i’ that is not sensitive to  weather or time. This analysis controlled for non‐weather‐sensitive and  time‐invariant energy use with home fixed effects  τt = Average energy use in month ‘t’ reflecting unobservable factors specific  to the month. This analysis controlled for these effects with month‐by‐ year fixed effects  β1, β2 = Average daily usage per HDD and CDD (kWh or therm/degree day) in  the pre‐conversion period  HDD =  Average daily HDDs (heating load) during the billing cycle  CDD =  Average daily CDDs (cooling load) during the billing cycle  β3, β4 = Coefficients for HDD and CDD (kWh or therm/degree day) interacted  with the installation of other measures  Other  =  An indicator variable for whether the month is pre‐ or post‐installation  of other measure. This variable equals 1 in the months following the  maximum install date for all other measures, and equals 0 for months  prior to the minimum install date  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 150 of 296   111  β5 – β8 = Coefficients used to estimate the conversion program effect on  electricity usage (as shown in next equation)  POST = An indicator variable for whether the month is pre‐ or post‐conversion.  This variable equals 1 in the months and years following the conversion  date, and 0 otherwise. The variable is defined using a combination of  Customer‐Specific Measure Install Date and Full Year specifications  εit = Error term for home ‘i’ in month ‘t’  Cadmus used the mean differences approach to estimate the above model. This approach removes the  customer‐specific constant term, αi, and controls for the variation in electricity use between customers  and between months.   Cadmus estimated the fuel conversion program savings for each conversion group using estimated  coefficients on all the post‐installation period dummy variable components in the above fixed‐effects  regression model. For a home in conversion group ‘j,’ the gross savings are given by:  SavingsH βH 365 β HAnnualHDDH βHAnnualHDDH βH 365   Where:  AnnualHDDj  = Average annual HDDs for all customers in conversion group ‘j’   AnnualCDDj  =  Average annual CDDs for all customers in conversion group ‘j’      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 151 of 296   112  Appendix B: Residential Behavior Program Data Cleaning Procedures  Cadmus conducted the following steps to inspect and clean the data provided by Opower:  1. Removal of one customer from the Opower data that appeared in both the control and  treatment groups.  2. Verification that customer assignments to treatment and control groups in the Opower data  corresponded to the assignments that Cadmus made. We found no discrepancies.  3. Removal of customers Opower flagged for exclusion from analysis because it was not possible to  generate an energy report or they received a report but were not randomly assigned.50  4. Checks for duplicate records. We found none.  One participant originally selected by Cadmus for the control group was missing from Opower’s list of  participants. The Opower data also included 12 extra participants in the treatment group that were not  present in Cadmus’ original sample, but Opower had flagged all of these to be excluded from the  analysis. After cleaning the data, there were 99,495 customers on Opower’s list.  Cadmus conducted the following steps to clean the billing data provided by Avista:  1. Verification that customer account numbers were unique to addresses.  2. Removal of billing data for customers not in the Opower control or treatment groups and for  billing records ending before June 1, 2012 or beginning after December 31, 2013.  3. Removal of gas bills.  4. Removal of customers whose maximum daily average consumption in any billing period was  greater than 1,000 kWh per day. There were less than 10 such customers, and Cadmus assumed  their large bills were likely due to meter misreads, billing errors, or significant commercial,  industrial, or agricultural activity which would make them ineligible for analysis. Cadmus also  noted that there were 185 customers who regularly consumed more than 240 kWh per day on  average, but Cadmus did not remove these customers from the analysis.  5. Removal of duplicate bills. One of the additional billing data files that Avista provided included  many duplicate records; Cadmus did not include these in the analysis.  6. Removal of $0.00 bills. Cadmus noticed that there were many duplicate bills of this type.  Cadmus only removed these bills when either:  a. The service amount was $0.00 and the usage quantity (kWh) was non‐zero, or  b. Both the service amount and the usage quantity were zero, but there was another non‐zero  bill in the same period.                                                               50  For example, some Avista staff requested to receive energy reports from Opower. There were 12 customers  who received reports but were not assigned to the treatment group.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 152 of 296   113  7. Removal of August 2012 bills that ended on August 27, only when there were multiple bills for  that month. Many customers had two partially‐overlapping bills in August 2012 that had the  same start dates. The first always ended on August 15 or 16, and the second always ended on  August 27. Cadmus noted that the next bill started on the 15 or 16 of August, not the 27, so we  removed the longer, partially‐overlapping bill to ensure we would not be double‐counting  energy usage.  8. Manual data cleaning of partially‐overlapping bills. In less than 20 instances, Cadmus manually  removed problematic partially‐overlapping bills, so that we would not be double‐counting  energy usage when summarizing the bills for analysis.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 153 of 296   114  Appendix C: Residential Behavior Program Regression Model Estimates   Table 86 shows results from different panel regressions of home average daily electricity use. Cadmus  used Model 4 to estimate savings as shown in the report. There were only small differences between  models 1‐4 in the estimated savings.   Table 86. Regression Estimates of Home Energy Report Effects on Energy Use    Conditional Average Treatment Effects  Model 1 Model 2 Model 3 Model 4  Post 3.0979 1.7691 ‐0.9085 0.741 (0.09)(0.18)(0.09) (0.18) Participant x post ‐0.6586 ‐0.7612 ‐0.7642  ‐0.7637 (0.10)(0.10)(0.10) (0.10) Customer fixed effects Yes Yes Yes Yes Month‐by‐year fixed effects No Yes No Yes Weather No No Yes Yes Number of homes 54,324 54,324 54,324 54,324 Number of observations 1,022,886 1,022,886 1,022,886 1,022,886 Notes: The dependent variable is the home’s average daily electricity use for a month. Cadmus based these  estimates on a D‐in‐D ordinary least squares regression of average daily consumption between June 2012 and  December 2013. The Huber‐White estimated standard errors shown in parentheses are clustered on homes.      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 154 of 296   115  Appendix D: Low Income Weatherization Participant Survey  In May 2013, Cadmus coordinated a phone survey of 150 residential low income weatherization  program participants. We developed the participant survey instrument and defined the sample, then  subcontracted survey administration to an implementation firm.   Table 87 provides details regarding the planned and achieved completes for the telephone survey.  Table 87. Participant Telephone Survey Sampling Plan   Quantity  Total participants 434 Screened out due to a change in occupancy or incorrect phone number 78 Eligible participants on call list 356 Completed surveys 150 Sample size goal 150   Cadmus selected a random sample of participants from the PY 2012 Q3 to PY 2013 Q1 participant  population as available in April 2013 (434 participants). Cadmus aimed for and achieved 150 completed  survey responses, which provided results with 90% confidence and ±5.1% precision at the program level.  The survey achieved a high fielding response rate, as we used only 75% the sample frame to accomplish  the targeted completes.  We asked participants about their experiences with the program, addressing the following topics:  • Their previous awareness of the program, and how long they waited for an appointment and  pick‐up.  • Functionality of equipment prior to repair or replacement  • Education they received through the program.  • Demographics and home characteristics  Program Awareness and Wait Time  Most survey respondents said they heard about the program through family or friends. Figure 20  presents all ways survey respondents heard about the program.   Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 155 of 296   Figure 21    Nearly ha indicatin between  Previo Table 88 s responde program Fi shows how l Figure 2 lf of the resp  they were o one and two  us and Ne shows the di nts who rece ed the ther gure 20. Ho ong respond 1. How Long R ondents said  n the wait lis years, and 2 w Equipm stribution of i ived progra ostat, educ w Responden ents were on  Respondents  they were o  for less tha % waited o ent  nstalled equi mable ther ted the par 116  ts Heard Abo the waiting l Were on th n the progra  six months.  ver two years  pment and t ostats, the t icipant abou ut the Progr ist for the pr e Program W m waiting list  Thirty perce for program  he condition  able also ind  how to inst am (n=125)  ogram.   aiting List (n one year or l t of the res services.  of the replac cates wheth ll it, or neith =142)    ess, with 26 ondents wai d equipme r the install er.       %  ted  nt. For  er  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 156 of 296   117  Table 88. Equipment Installation Rates and Equipment Condition  Equipment Installed % Installed Worked Fine Had Problems Did Not Work  Refrigerator (n=150) 16%54%38% 8% Furnace (n=146) 60%24%61% 15% Water Heater (n=148) 51%50%43% 7% Windows (n=148) 45%29%71% N/A Doors (n=149) 62%8%92% N/A Equipment Installed % Installed Programmed Just Education Neither  Thermostat (n=143) 50%87%7% 6%   For respondents who said their previous equipment had problems or did not work, Table 89 shows how  long the equipment was experiencing those issues.  Table 89. Equipment Problem Duration  Problem Equipment Months One Year > One Year  Refrigerator (n=10) 30%10% 60% Furnace (n=59) 15%24% 61% Water Heater (n=34) 26%32% 41%   Table 90 details the fuel type of old and replaced furnaces and water heaters for respondents who  received this new equipment to replace old equipment. The table does not include customers who did  not previously own a furnace or water heater before participating in the program  Table 90. Furnace and Water Heater Fuel  Equipment Type Fuel Previous New  Furnace (n=61)  Electric 42%10% Gas 53%90% Oil 5%0% Water Heater (n=67) Electric 76%25% Gas 24%75%   Program Education  Only 3% of respondents said they received little program information, while over two‐thirds said they  received a lot of information, as shown in Figure 22.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 157 of 296   As shown responde Yes  No    Home C Figure 23  Figure  in Table 91,  nts said they  Ta Character shows the di  22. Amount  89% of resp read them.  ble 91. How M istics  stribution of  Figure 23. Y of Much Inf ondents said t Many Respo Received  when respo Year Respon 118  ormation Re they received ndents Recei Pamphlet (n ndents’ hom dents’ Home pondents R  educational  ved and Rea =132)  89% 11% s were built. s Were Built ( eceived (n=1 pamphlets, a d Pamphlets  Read Pam n=141)  19)    and 97% of t phlet (n=11     hose  6)  97% 3% Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 158 of 296   Most res   Figure 25    Figure 26  said their  pondents live shows that m presents the primary hea  in a single‐f ost respond  distribution  ter is a natur mily home, m Figure 24. H ents heat th Figure 25. H of responde l gas furnac 119  mobile home Home Types ( eir home wit Heating Fuel ( nts’ primary h e, followed b  or trailer, a (n=147)  h natural gas,  (n=147)  heating equi  an electric f s shown in Fi followed by  pment. Most r furnace (22% ure 24.    electricity.    respondents  ).    (69%)  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 159 of 296   Most res turned d   Figure 28  electric r ondents sai wn the tem shows what  oom heater o Fi d that after t erature setti Figure 27. P respondents  r a wood bu gure 26. Prim he program e ng on their t Post‐Installat use as a sup ning device. 120  ary Heater T quipment w ermostat, a ion Thermos plemental he ype (n=147) as installed, t  shown in Fi tat Changes ( ating source. ey either di ure 27.  (n=135)   Most indica   d not change    ted using an    or  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 160 of 296   Respond program e   Figure 30  they wou affirmati nts who use  equipment w F presents the ld change th ely.  Figur a suppleme as installed, a Figure 29. Po  distribution  e way they c e 28. Supple ntal heating s s shown in F st‐Installatio of equipmen ol their hom 121  mental Heat ource said th igure 29.  n Suppleme t used to co  after partic er Types (n=5 ey used it les ntal Heater U ol responden ipating in th 8)  s or about th se (n=56)  t’s homes. W  program, o   e same after    hen we aske ly 8% respo   the  d if  nded  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 161 of 296   Figure 31    shows the t Figure 30 ype of supple Figure 31. S  Summer Co mental equi upplemental 122  oling Equip pment respo  Cooling Equ ent Types ( ndents use to  ipment Type =140)  cool their h s (n=64)    ome.       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 162 of 296   123  Appendix E: Low Income Weatherization – Billing Analysis Model  Specification  For each participant home, Cadmus estimated three models in both the pre‐ and post‐periods in order  to weather‐normalize raw billing data:   • Heating and cooling,   • Heating only, and   • Cooling only.   The heating and cooling PRISM model specification was:   ititAVGCDDitAVGHDDiitADCεββα+++=21   Where for each customer ‘i’ and calendar month ‘t’:  ADCit = The average daily kWh consumption in the pre‐ or post‐program period  αi = The participant intercept; represents the average daily kWh base load   β1 = The model space heating slope (used in the heating only and heating +  cooling models)  AVGHDDit = The base 65 average daily HDDs for the specific location (used in the  heating only and heating + cooling models)  β2 = The model space cooling slope (used in the cooling only and heating +  cooling models)  AVGCDDit = The base 65 average daily CDDs for the specific location (used in the  cooling only and heating + cooling models)  εit = The error term  From the model above, we computed the NAC as follows:  iiLRCDDiLRHDDiiNACεββα+++=21365* Where, for each customer ‘i’:  NACi = Normalized annual kWh consumption  αi = The intercept that is the average daily or base load for each  participant, representing the average daily base load from the model  αi * 365 = Annual base load kWh usage (non‐weather sensitive)  β1 = The heating slope; in effect, usage per heating degree from the model LRHDDi = The annual, long‐term HDDs of a TMY3 in the 1991–2005 series from  NOAA, based on home location  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 163 of 296   124  β1 * LRHDDi = Weather‐normalized annual weather sensitive (heating) usage, also  known as HEATNAC  β2 = The cooling slope; in effect, the usage per cooling degree from the  model  LRCDDi = The annual, long‐term CDDs of a TMY3 in the 1991–2005 series from  NOAA, based on home location  β2 * LRCDDi = The weather‐normalized annual weather sensitive (cooling) usage,  also known as COOLNAC  εi = The error term  Although we used the same specification for both electric (non‐conversion) and conversion participants,  Cadmus estimated separate fixed‐effects CSA models for each group to determine program‐level  savings:  DDDHH D H D HDDDDDDHH D HDDDDDDHH D HDDDDHH D H…HHD H D HH  Where, for customer ‘i’ and monthly billing period ‘t’:  ADCit  = Average daily kWh consumption during the pre‐ and post‐program  periods  αi  = The average daily kWh base load intercept for each participant (part of  the fixed‐effects specification)  β1  = The model space heating slope  AVGHDDit  = The average daily base‐65 HDDs, based on home location  β2  = The model space cooling slope  AVGCDDit  = The average daily base‐65 CDDs, based on home location  β3  = The kWh change in usage per day  POSTit  = An indicator variable that is 1 in the post‐period (after measure  installations) and 0 in the pre‐period  Mt  = An array of bill month dummy variables (Feb, Mar, …, Dec), 0  otherwise51  εit  = The modeling estimation error  Cadmus estimated the above model for Idaho non‐conversion and conversion participants separately.  The model coefficient, β3, is an estimate of the kWh savings per day in each model.                                                                51  We excluded the January dummy variable from the independent variables, otherwise the 12 monthly  indicators would form perfect co‐linearity with the intercepts; thus, the intercepts include the seasonality  from January.  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 164 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 165   Avista Utilities              Appendix 2    Avista 2013 Idaho Natural Gas Savings Memorandum  June 14, 2014  The Cadmus Group, Inc.    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 165 of 296   MEMORANDUM  To: David Thompson, Avista   From: Danielle Kolp, Cadmus    Subject: 2013 Idaho Natural Gas Savings   Date:  June 14, 2014   This memorandum is intended to document the natural gas savings achieved by Avista Utilities’ DSM  programs in Idaho for program year 2013. Though formal programs were suspended in Idaho for 2013,  there were several instances where gas savings were still achieved due to grandfathered projects or duel  fuel saving measures. The analysis methodologies for these savings are omitted from this memorandum,  but can be found in great detail in the Avista 2013 Washington Gas Portfolio Impact Evaluation report  submitted to Avista on May 15, 2014.    Total 2013 Idaho Natural Gas Savings  In 2013, Avista’s Idaho service territory exhibited natural gas savings of 51,772 therms across  nonresidential projects, residential measures, and the residential behavior program.   Table 1. 2013 Reported and Gross Evaluated Savings for Idaho  Sector Reported Savings  (therms)  Gross Evaluated  Savings (therms)  Realization  Rate  Nonresidential 18,192 18,580 102%  Residential 1,743 2,561 147%  Residential Behavior 29,498 30,631 104%  Total  49,433 51,772 105%    Nonresidential Savings  There were twelve natural gas projects in Idaho that were originated prior to 2013 but were physically  completed and paid incentives in 2013. These projects were subjected to the site visit and metering  sampling methodology along with the rest of Avista’s natural gas projects included in the evaluation.       Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 166 of 296        2      Table 2 shows the reported and gross evaluated savings for the 12 nonresidential projects in 2013,  resulting in evaluated savings of 18,580 therms yielding a 102% realization rate.    Table 2. PY 2013 Nonresidential Gross Gas Savings  Measure  Category  Project  Count  Gross Program  Reported Savings  (Therms)  Gross Program  Evaluated Savings  (Therms)  Realization  Rate  Prescriptive 3 2,447 2,135 87% Site Specific ‐ HVAC 6 12,641 13,355 106% Site Specific ‐ Other 1 27 26 96% Site Specific ‐ Shell 2 3,077 3,064 100% Total 12 18,192 18,580 102%   Residential Savings  Though the residential natural gas DSM programs were suspended for 2013, 214 measures were  processed at the beginning of the year. The 99 clothes washer measures were actually processed as  electric measures, but upon evaluation, found to have natural gas water heating, so there were  additional gas savings from the electric dryer savings. Table 3 gives details on these six measures and the  reported and evaluated gross savings, which achieved 2,561 therms.  Table 3. PY 2013 Residential Gross Gas Savings  Measure Category Measure Count  Gross Program  Reported  Savings  (Therms)  Gross Program  Evaluated  Savings  (Therms)  Realization  Rate  Attic Insulation with Gas Heat 4 279 279 100% Wall Insulation with Gas Heat 2 370 370 100% Natural Gas Boiler 1 141 141 100% Natural Gas Furnace 7 722 722 100% Clothes Washer With Natural Gas  Water Heater 99 0 420 N/A Simple Steps ‐ Showerheads 101 231 630 272% Total 214 1,743 2,561 147%      Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 167 of 296        3    Residential Behavior Savings  Avista began a residential behavior program in the summer of 2013 in both Idaho and Washington that  targeted electric savings, but Cadmus also evaluated gas savings achieved by the program. Cadmus  performed a billing analysis on the entire population of participating homes, and the evaluated savings  and confidence intervals can be seen in Table 4 below. Idaho homes participating in the program  reduced their gas usage by 1.04%. The gross reported savings are presumed to reflect the Avista  Business Plan assumption of 1.00% savings. The program achieved 30,631 therms in the second half of  2013 in Idaho.  Table 4. PY 2013 Residential Behavior Gross Gas Savings and Confidence Intervals  Service Area  Gross Program  Reported  Savings (Therms) Gross Evaluated  Savings (Therms)  90%  CI  Lower  Bound  90% CI  Upper  Bound  Idaho 29,452 30,631 2,999 58,262    Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 168 of 296    Demand‐Side Management  Avista Utilities  July 31, 2014  2013 Annual Report Idaho Page 169   Avista Utilities              Appendix 3    Avista 2012‐2013 Process Evaluation Report  May 15, 2014  The Cadmus Group, Inc.        Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 169 of 296 AVISTA 2012-2013 PROCESS EVALUATION REPORT May 15, 2014 Avista Corporation 1411 E Mission Ave Spokane, WA 99220 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 170 of 296 This page left blank. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 171 of 296 Prepared by: Danielle Côté-Schiff Kolp, MESM Kate Bushman Cameron Ramey Allison Asplin Hanna Lee Andrew Carollo M. Sami Khawaja, Ph.D. Cadmus Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 172 of 296 This page left blank. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 173 of 296 v Table of Contents Portfolio Executive Summary ....................................................................................................................... ix Evaluation Activities .............................................................................................................................. ix Key Residential Findings ........................................................................................................................ ix Residential Conclusions and Recommendations .................................................................................... x Program Participation ..................................................................................................................... xi Program Design ............................................................................................................................... xi Program Implementation .............................................................................................................. xii Marketing and Outreach ................................................................................................................ xii Key Nonresidential Findings ................................................................................................................. xii Nonresidential Conclusions and Recommendations ............................................................................ xiv Program Management and Implementation ................................................................................. xiv Customer Feedback ....................................................................................................................... xv Market Feedback ........................................................................................................................... xv Marketing and Outreach ................................................................................................................ xvi Quality Assurance and Verification ................................................................................................ xvi Residential Process Report ........................................................................................................................... 1 Introduction ............................................................................................................................................ 1 Program Overview ........................................................................................................................... 2 Evaluation Methodology and Information Sources ......................................................................... 5 Status of Evaluation Recommendations ........................................................................................ 13 Program Participation .......................................................................................................................... 14 Savings and Incentives ................................................................................................................... 14 Participation Trends ....................................................................................................................... 15 Program Design, Management, and Implementation.......................................................................... 22 Effectiveness of Implementers ............................................................................................................. 28 Opower .......................................................................................................................................... 28 Residential Behavior Program Description .................................................................................... 28 Residential Behavior Program Implementation ............................................................................ 29 Future of the Residential Behavior Program ................................................................................. 30 Data Tracking ........................................................................................................................................ 30 Data Tracking Summary ................................................................................................................. 31 Planned Changes in Avista Data Tracking ...................................................................................... 33 Marketing and Outreach ...................................................................................................................... 33 Marketing Approach ...................................................................................................................... 33 Marketing Objectives and Strategies ............................................................................................. 34 Planning and Processes .................................................................................................................. 34 Target Audience and Customer Motivators .................................................................................. 35 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 174 of 296 vi Outreach Channels ......................................................................................................................... 36 Every Little Bit and Efficiency Matters Campaigns ......................................................................... 36 Materials and Messaging ............................................................................................................... 37 Marketing Execution and Measurement ....................................................................................... 37 Sources of Participant Awareness ................................................................................................. 37 Avista Customer Awareness of Energy-Efficiency Rebates............................................................ 39 Participant Experience and Satisfaction ............................................................................................... 40 Overall Program Satisfaction ......................................................................................................... 41 Rebate Amount and Promptness Satisfaction ............................................................................... 42 Residential Program Freeridership and Spillover ................................................................................. 45 Freeridership .................................................................................................................................. 45 Spillover ......................................................................................................................................... 48 Residential Conclusions and Recommendations .................................................................................. 49 Program Participation .................................................................................................................... 49 Program Design .............................................................................................................................. 50 Program Implementation .............................................................................................................. 51 Marketing and Outreach ................................................................................................................ 51 Nonresidential Process Report ................................................................................................................... 52 Introduction .......................................................................................................................................... 52 Program Overview ......................................................................................................................... 52 Evaluation Methodology and Information Sources ....................................................................... 54 Status of Evaluation Recommendations ........................................................................................ 59 Program Participation .......................................................................................................................... 59 Savings and Incentives ................................................................................................................... 59 Program Design, Management, and Implementation.......................................................................... 60 Overview ........................................................................................................................................ 60 Program Logic ................................................................................................................................ 60 Internal Communication ................................................................................................................ 62 Effectiveness of Implementers ............................................................................................................. 63 Data Tracking, Verification, and Quality Assurance ............................................................................. 63 Participant Characteristics, Experience and Satisfaction ..................................................................... 64 Participant Characteristics ............................................................................................................. 65 Participant Satisfaction .................................................................................................................. 66 Program Barriers ............................................................................................................................ 68 Program Benefits ........................................................................................................................... 69 Market Feedback .................................................................................................................................. 70 Contractor Awareness ................................................................................................................... 70 Program Impact on Sales ............................................................................................................... 71 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 175 of 296 vii Market Transformation.................................................................................................................. 72 Marketing and Outreach ...................................................................................................................... 73 Program Marketing Approach ....................................................................................................... 73 Customer Awareness ..................................................................................................................... 75 Nonresidential Program Freeridership and Spillover ........................................................................... 77 Freeridership .................................................................................................................................. 77 Spillover ......................................................................................................................................... 80 Nonresidential Conclusions and Recommendations ............................................................................ 80 Program Management and Implementation ................................................................................. 80 Customer Feedback ....................................................................................................................... 81 Market Feedback ........................................................................................................................... 81 Marketing and Outreach ................................................................................................................ 81 Quality Assurance and Verification ................................................................................................ 82 Appendix A: Status of PY2010 and PY2011 Residential Evaluation Recommendations ............................. 83 Appendix B: Status of PY2010 and PY2011 Nonresidential Evaluation Recommendations ....................... 86 Appendix C: 2012 Nonresidential Process Evaluation Memorandum ........................................................ 90 Key Findings .......................................................................................................................................... 90 Interview Findings: Large Project Review Challenges and Changes .............................................. 90 Review Process Challenges Identified by Avista ............................................................................ 91 Issues Identified Through the Large Project Review...................................................................... 92 Planned Process Improvements .................................................................................................... 92 2011-2012 Database and Realization Rate Review .............................................................................. 93 Database Review ............................................................................................................................ 94 Realization Rate Review ................................................................................................................. 98 Conclusions and Recommendations .................................................................................................. 106 Large Project Review Process ...................................................................................................... 106 Database and Realization Rate Review ........................................................................................ 107 Memo Appendix A .............................................................................................................................. 109 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 176 of 296 viii This page left blank. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 177 of 296 ix Portfolio Executive Summary Avista Corporation contracted with The Cadmus Group, Inc., to perform a portfolio-wide evaluation for the 2012-2013 demand-side management programs. This report presents the process evaluation findings for the residential and nonresidential sectors. Evaluation Activities Table ES-1 summarizes the process evaluation activities conducted by sector. Table ES-1. PY 2012-2013 Process Evaluation Activities Avista Program Staff Interviews* 7 12 Third-Party Implementer Interviews 1 - Contractor Interviews - 20 Participant Surveys 1,005 210 Nonparticipant Surveys 2,160 140 Assessment of Tracking Databases  Review of Program Documentation  Review of Marketing Materials  Review of Stakeholder Reports  *Multiple representatives present for some interviews. Key Residential Findings The residential process evaluation resulted in the following key findings for the programs examined (listed in Table ES-2). Table ES-2. PY2012 - PY2013 Residential Programs Natural Gas and Electric Programs ENERGY STAR® Homes ENERGY STAR Products High-Efficiency Equipment Home Audit Manufactured Home Duct Sealing Residential Behavior Weatherization and Shell Electric-Only Programs Second Refrigerator and Freezer Recycling Simple Steps, Smart Savings Space and Water Conversions Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 178 of 296 x  Participation levels in many of Avista’s residential programs trended downward during PY2012 and PY2013. Many factors contributed to the downward trend, including reduced measure offerings and the 2013 discontinuation of natural gas incentives in Idaho. The trend experienced by Avista’s programs is similar to participation trends in other regional utility DSM programs.  The Simple Steps, Smart Savings program saw increased participation, partly due to new measure offerings. Energy-efficient showerheads were added in 2012 and LEDs were added in 2013.  Avista’s overall program design is effective, but there is room for improvement around internal communication between Avista staff.  Avista staff showed a strong commitment to customer satisfaction, achieving fast rebate processing despite increasing complexity of applications. Avista staff have also taken steps to improve data tracking, such as integrating additional program data into a central database. In addition, program marketing through mass media channels had to be tailored to avoid customer confusion about different incentive offerings in Idaho and Washington.  Key sources of program information for customers included contractors (17% in 2012; 28% in 2013), bill inserts (16%; 16%), and word of mouth (10%; 14%). Changes in information sources reflected changing program offerings such as the elimination of appliance rebates in 2013.  General population awareness of Avista’s rebates decreased from 63% in 2012 to 54% in 2013. Bill inserts are the most common way for the general population to learn about Avista’s rebates.  Participant satisfaction increased since the 2011 process evaluation, with 89% of 2013 participants being “very satisfied” with their program experience. Only a small number of customers expressed any level of dissatisfaction across the three years in which Cadmus conducted surveys.  Avista’s appliance rebates experienced a high level of freeridership, likely due to high market penetration of ENERGY STAR appliances and comparatively low incentive amounts—as a percent of incremental cost. Avista adjusted their program offerings to reflect this market, discontinuing appliance rebates in 2013.  Many of Avista’s customers – both participants and nonparticipants – reported installing additional energy-saving improvements without receiving any rebate because of Avista’s programs’ influence. These actions contribute to program spillover. Out of the 3,215 customers Cadmus surveyed in 2012 and 2013, 113 (or roughly one in every 28 customers) reported a spillover measure. Residential Conclusions and Recommendations This section describes the evaluation’s conclusions and recommendations for the residential programs. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 179 of 296 xi Program Participation Conclusion: Avista’s implementation of new and continued support for existing third-party implemented programs such as Simple Steps, Smart Savings and Residential Behavior effectively captures energy savings in the residential market segments.  Recommendation: Continue exploring new measures, program designs, and delivery mechanisms that leverage the national expertise of experienced third-party implementation firms. Possible programs may include additional partnership with ENERGY STAR in the form of the Home Performance with ENERGY STAR program. Conclusion: Avista’s continued investment in pilot programs provides a low-risk way test the effectiveness of new measure offerings, delivery channels, and implementation partners.  Recommendation: Continue testing new program designs and measure offerings through the use of pilots—even if secondary sources of funding or local partners are not available. Conclusion: While still early, evaluation findings indicate the Residential Behavior program is an effective way to capture savings in the residential market and Opower is a strong partner for program implementation.  Recommendation: If determined to be cost-effective, consider expanding the Residential Behavior program (for example, lowering the energy consumption threshold for participation) and implementing measures to track the methods these customers use to save energy. Given that Avista has already included all cost-effective customers in their target population for this program, future opportunities for expansion may be limited. Program Design Conclusion: Inconsistencies continue to exist in measure and program naming and organization across program planning, tracking and reporting activities which result in less transparency in program operations and limit effective program evaluation. • Recommendation: As part of the transition to the new data tracking system, consider aligning program and measure names with offerings articulated in annual business plans and other planning materials. Conclusion: Reduction in Avista natural gas rebates and elimination of appliance rebates give customers fewer ways to participate in Avista energy-efficiency rebate programs. • Recommendation: Consider ways to encourage repeat participation (such as marketing targeted at previous participants and online profiles that reduce application paperwork). Conclusion: Considering self-report customer freeridership scores and market baseline data from the RTF is an effective way to assess the appropriateness of measure offerings. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 180 of 296 xii • Recommendation: Continue use of customer freeridership and market assessments as a way to assess the appropriateness of measure offerings. Conclusion: Many ongoing changes in Avista’s program design and measure offerings are driven by the need to continue to meet cost-effectiveness requirements. Avista’s examination of measure and program-level cost-effectiveness will determine the character of its portfolio in future program years. • Recommendation: Develop a transparent process for assessing measure or program cost- effectiveness and communicating results internally. Consider ways to ensure high-quality cost- effectiveness analysis that aligns with industry best practices, such as obtaining an objective third-party review of current cost-effectiveness screening processes. Program Implementation Conclusion: Avista prioritization of customer satisfaction has been very successful and overall participant experience is very positive across all rebate programs. • Recommendation: Continue Avista’s commitment to customer satisfaction, but monitor: – Increased staffing costs; and – Impacts of the 90-day participation window on freeridership. Marketing and Outreach Conclusion: Avista implements a strong general awareness campaign around energy-efficiency, but some room exists in market segmentation and targeting specific customer groups. • Recommendation: Utilize survey results from this evaluation and other data collection activities to understand which audiences are more likely to participate in Avista programs. Key Nonresidential Findings The nonresidential process evaluation resulted in the following key findings for the programs examined (listed in Table ES-3). Table ES-3. PY2012 - PY2013 Nonresidential Programs Prescriptive Program Lighting PC Network Controls Clothes Washers Food Service Motors Variable Frequency Drives Windows/Insulation HVAC (natural gas only) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 181 of 296 xiii Standby Generator Block Heater Green Motors Program Site-Specific Program Custom Projects Meeting Program Criteria EnergySmart Grocer Program Compressors Controls Motors Night Covers for Refrigerated Cases Case Lighting Strip Curtains for Refrigerated Spaces Insulation for Suction Lines Hot Water Tanks  Program participants were more likely than nonparticipants to own their facilities: according to surveys (78% of participants owned their facilities, compared with 67% of nonparticipants).  Overall, participants reported high satisfaction ratings. The vast majority were “very satisfied”: 87% for Prescriptive, 75% for Site-Specific, and 88% for EnergySmart Grocer. Only a handful of customers (roughly 1%) reported any level of dissatisfaction.  All three nonresidential programs received the same satisfaction ratings or better than they did in 2011, with the EnergySmart Grocer program showing a 23% increase in “very satisfied” customers over 2011.  Though still showing high overall satisfaction, the Washington Site-Specific program had the lowest level of “very satisfied” participants at 69%. Among these participants, lower levels of satisfaction stemmed from inadequate information included in the program materials, and a lower-than-desired rebate amount. However, satisfaction with Avista’s staff remained high despite these minor issues: 90% or more of participants in every category were “very satisfied” with staff.  Contractors were the primary source of program information for nonresidential program participants (37%. Other common sources of information were word of mouth (23%) and direct contact with Avista (17%).  Among nonparticipants, awareness of Avista’s energy-efficiency rebates has remained fairly constant since 2010, with around 4 in 10 nonparticipants being aware of the programs (38% in 2013).  Avista’s management and implementation of DSM programs has had some persistent organizational challenges, which may have impacted the effectiveness of implementation processes. While not limited to any specific part of Avista’s DSM staff, many of the issues have primarily affected the nonresidential program processes.  Cadmus’ review of Avista’s implementation and QA/QC processes showed that the accuracy of project savings estimates has increased since 2011, there is still room for improvement. Figure Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 182 of 296 xiv ES-1 shows the percentage of electric realization rates for site-specific projects that fell within the range of 90% to 110%. This range indicates a good level of accuracy in reported savings. Figure ES-1. Nonresidential Site-Specific Project Electric Realization Rates 2011-2013  Cadmus’ interviews with lighting contractors – conducted as a supplement to the ongoing Panel Study research – revealed that Avista’s programs increase sales of energy-efficient lighting equipment for both participating and nonparticipating contractors: 16 out of 20 reported that their sales increased because of Avista’s programs.  The prescriptive program showed 9% freeridership in 2013, showing a large decrease in freeridership as compared to the 2011 result. The site-specific program showed 30% freeridership in 2013, showing an increase as compared to 2011. Nonresidential Conclusions and Recommendations This section describes the evaluation’s conclusions and recommendations for the nonresidential programs. Program Management and Implementation Conclusion: Several parties over several years, internal and external to Avista, have observed the need for greater data quality assurance, in both documentation and input tracking. Quantitative inputs to the savings and rebate calculations have repercussions for tariff compliance,1 incentive payments, and savings realization rates. 1 As noted in Idaho Public Utilities Commission Order Number 33009 on Avista Corporation’s Application for a Finding that it Prudently Incurred its 2010-2012 Electric and Natural Gas Energy Efficiency Expenditures. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 183 of 296 xv  Recommendation: Avista should continue efforts to improve program processes. Cadmus understands that a reorganization of the DSM group has occurred concurrent to the delivery of this report. This change may be an opportunity for fresh perspectives, clarified responsibilities, and improved coordination within and between teams. We believe unifying the organizational structure under central leadership is a step in the right direction and may help alleviate some previously documented issues with internal communications. In addition to the reorganization, Cadmus recommends that Avista develop standardized processes within the DSM group, including clear delineation of roles and precise description and assignment of all processes and responsibilities for both residential and nonresidential programs. All affected parties should be included in formalizing and standardizing the DSM group’s processes, roles, and responsibilities. Further, all parties must formally agree to clearly delineated responsibilities under the new organizational structure. While these activities need to be prescriptive and precise, we caution that the resulting structure should still allow some flexibility: increased clarity, transparency, and accountability should serve to enhance program delivery and customer satisfaction. Customer Feedback Conclusion: Customers were highly satisfied with the program overall and with individual components. Customer satisfaction has increased since 2011, which had in turn increased from 2010.  Recommendation: Continue to prioritize and monitor program satisfaction. Conclusion: Customers appeared to be slightly less satisfied with the Washington Site-Specific program than with other programs. The largest source of lower satisfaction was the participants’ reactions to program materials. Many customers said they received no program materials, and many participants learned about the program from their trade allies.  Recommendation: Consider taking action to strengthen the use of program materials. Consider providing trade allies with printed program information flyers or brochures to give to customers. Maintaining up-to-date information for trade allies is critical when they are the key party delivering the program’s message and participation details. Market Feedback Conclusion: According to commercial lighting contractor feedback, the nonresidential programs are successful in driving incremental energy-efficient equipment sales, and the market has not yet transformed to make energy efficiency standard practice.  Recommendation: Continue to monitor market transformation indicators to measure programs’ market impact over time. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 184 of 296 xvi Marketing and Outreach Conclusion: The characteristics of Cadmus’ survey respondents indicate that the office / professional services and local government sectors may be underserved by the programs relative to their incidence in the nonparticipant population. Further research is necessary to determine whether this is true.  Recommendation: Identify underserved industries, and seek opportunities to target outreach to specific underserved industries: – Investigate overall customer industry distribution – Compare to participant industry distribution – Develop targeted outreach strategies for any underserved sectors Quality Assurance and Verification Conclusion: Avista monitored its site-specific project review process and instituted refinements during the evaluation period in response to feedback from users. While this has led to improvements, including notably improved reliability of reported savings in 2012, quality assurance problems may persist.  Recommendation: Continue to monitor the effectiveness of the site-specific project review process and refine as needed. Cadmus recommends implementing the following to ensure continued improvement: – All large prescriptive or site-specific projects reporting savings over a threshold of 300,000 kWh or 10,000 therms should undergo a complete QA/QC review prior to incentive payment in addition to the standard Top Sheet review process. Typically, a QA/QC process reviews engineering calculations, verifies inputs, checks payback period and incentive payments for reasonableness, and ensures compliance with program requirements and tariff rules. In order to align with the above recommendation regarding program management and implementation, Cadmus recommends that Avista determine and document the specific requirements and steps in the QA/QC process through a collaborative process that will ensure accountability and balance needs for efficiency and customer satisfaction. – Conduct an external third-party review of Top Sheets, including reviewing a random sample of completed Top Sheets for completeness and accuracy. These were not reviewed as part of the current process evaluation, but should be included in the next process evaluation. Review should not only verify the presence of the Top Sheets, but also the quality and accuracy of the information provided. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 185 of 296 1 Residential Process Report Introduction This residential process evaluation focuses on ten Avista programs offered to Idaho and Washington natural gas and electric customers during program years 2012 and 2013 (PY2012 and PY2013).2 In this evaluation, Cadmus sought to address the following researchable questions:  What are the major trends in measure offerings and program uptake, and how do they compare to other utilities?  What barriers exist to increased customer participation, and how effectively do the programs address those barriers?  How satisfied were customers with the programs?  What changes to design and delivery would improve program performance? In assessing these topics, Cadmus relied on three main data collection efforts:  Review of program tracking data, documents, and invoice materials;  Interviews with Avista and third-party program implementation staff; and  Telephone surveys with participating and general population3 customers. In this effort, Cadmus sought to align evaluation resources with evaluation objectives and focus on areas of uncertainty and programs with higher reported gross savings. Therefore, as indicated in Table 1, evaluation activities generally centered on programs implemented directly by Avista (rather than a regional partner) and established programs rather than pilots. Table 3 provides additional detail on the scope of evaluation activities applied to each program. Table 1. PY2012 - PY2013 Process Evaluation Scope Natural Gas and Electric Programs ENERGY STAR® Homes Limited ENERGY STAR Products Full High-Efficiency Equipment Full Home Audit Limited Manufactured Home Duct Sealing Limited 2 Not all programs are offered to customers in both states. For example, the Home Audit program operated only in Spokane Washington. Avista’s programs operate on calendar years, with program years running from January through December. 3 In 2012 and 2013, Cadmus surveyed a random sample of Avista Washington and Idaho customers. Cadmus did not implement any screens for program participation when sampling, so it follows that some percentage of respondents have at one time participated in an Avista energy-efficiency program. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 186 of 296 2 Program Name Process Evaluation Scope Residential Behavior Limited Weatherization and Shell Full Electric-Only Programs Second Refrigerator and Freezer Recycling Full Simple Steps, Smart Savings Limited Space and Water Conversions Full In addition to the programs identified in Table 1, Avista offers energy-saving opportunities to residential customers through CFL Geographic Saturation events and Aclara® Software Applications. As energy savings from these activities are generally low (CFL Geographic Saturation events) or not tracked (Aclara), Cadmus did not review them as part of this evaluation. Program Overview The following section briefly describes the programs reviewed in this evaluation. ENERGY STAR® Homes The Northwest Energy Efficiency Alliance (NEEA) administers a regional ENERGY STAR Homes Program, which Avista supports. When a home in Avista’s territory makes it through the program and is certified as ENERGY STAR-compliant, Avista pays a rebate to the homebuilder. The amount of the rebate is based on Avista fuel-service(s) used in the home. ENERGY STAR Products This program offers direct financial incentives to motivate customers to purchase and install energy- efficient appliances. The program indirectly encourages market transformation by increasing demand for ENERGY STAR products—specifically, appliances such as refrigerators and clothes washers. High-Efficiency Equipment This program offers four incentive categories for electric and gas customers seeking to purchase:  High-efficiency water heaters;  High-efficiency natural gas furnaces or natural gas boilers;  High-efficiency air-source central heat pumps; and  Primary heating systems incorporating a variable-speed motor. Prior to 2011, these measures were offered under the Water Heating and Heating and Cooling Efficiency Programs. Home Audit The Home Audit Program, launched in May 2010 and implemented with support from municipal partners, sought to determine home energy audits’ cost-effectiveness for capturing electric and gas Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 187 of 296 3 savings. Eligible Avista customers must have resided in single-family homes, duplexes, or manufactured homes located in Spokane County. The program offered energy audits to customers, conducted by Building Performance Institute (BPI)-certified auditors, at no cost to eligible customers. An Energy- Efficiency Community Block Grant (EECBG), under the American Recovery and Reinvestment Act (ARRA), partially funded this program. The program operated through PY2012. Manufactured Home Duct Sealing This program, launched in October 2012, provides duct testing, sealing, and repair to Washington customers in electrically heated homes located in Adams, Asotin, Ferry, Franklin, Garfield, Lincoln, Spokane, Stevens, and Whitman counties. This program is offered free of charge to customers, with 60% of the funding coming from Avista’s DSM funds and 40% provided through the Washington State University (WSU) Community Energy Efficiency Program (CEEP). All work is performed by UCONS LLC (UCONS), a third-party contractor. Residential Behavior The Residential Behavior Program is a peer-comparison program that began in spring 2013 and is scheduled to continue through 2015. Through the program, residential customers receive regular reports on their energy usage and comparisons to the usage of other customers in their immediate vicinity. Avista expects the program to increase the participation in their residential rebate programs and encourage behavior changes that result in kWh and therm savings. The program is offered at no cost to a sample of customers preselected by Avista (with assistance from Cadmus and Opower) and is implemented by Opower. Weatherization and Shell This program offers incentives for attic, wall, and floor insulation measures, and is available to residential electric and gas customers with homes heated with an Avista fuel. Second Refrigerator and Freezer Recycling This program, available to Washington and Idaho electric customers, provides financial incentives to customers recycling refrigerators and freezers. The program seeks to reduce energy consumption by recycling up to two inefficient secondary refrigerators or freezers per home. JACO Environmental, Inc. (JACO), the implementation contractor, is responsible for scheduling, pick-up, recycling, rebate payment, and data tracking. Simple Steps, Smart Savings Avista sponsors an upstream, buy-down program, administered by the Bonneville Power Authority (BPA) and implemented by CLEAResult (formally Fluid Market Strategies). The program, available to customers in Washington and Idaho, offers discounted twist and specialty CFLs, LEDs, and energy efficient showerheads at many large retail locations. Space and Water Conversions This program offers incentives for three types of conversion: Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 188 of 296 4  Replacement of electric resistance heating equipment as a primary heat source (either electric forced-air furnaces or electric baseboard heat), with central, natural gas heating systems;  Replacement of electric resistance heating equipment with central heat pumps; and  Replacement of electric water heaters with new, natural gas water heaters. Table 2 lists the residential energy-efficiency programs offered in PY2012 and PY2013—along with their associated measures and incentives. Table 2. PY2012 - PY2013 Residential Programs and Incentives ENERGY STAR Homes ENERGY STAR Home with Electric-Only or Electric and Gas $900 $650 ENERGY STAR Home with Gas-Only $650 $650 ENERGY STAR Products ENERGY STAR Freezer $20 N/A ENERGY STAR Refrigerator $25 N/A ENERGY STAR Dishwasher $25 N/A ENERGY STAR Clothes Washer $25 N/A High-Efficiency Equipment High-Efficiency Natural Gas Boiler or Furnace $400 $400 High-Efficiency Air Source Heat Pump $400 $100 Ductless Heat Pump $200 N/A Variable Speed Motor $100 $100 High-Efficiency Electric Water Heater $50 $30 High-Efficiency Natural Gas Water Heater $50 $30 Home Energy Audit Home Audit No cost to customer N/A Manufactured Home Duct Sealing Duct Testing, Sealing, and Repair No cost to customer Residential Behavior Participating Customer No cost to customer Weatherization and Shell Attic Insulation $0.25 per sq. ft. $0.25 per sq. ft. Wall Insulation $0.50 per sq. ft. $0.50 per sq. ft. Floor Insulation $0.50 per sq. ft. $0.50 per sq. ft. Fireplace Damper $100 N/A Space and Water Conversions Electric to Natural Gas Furnace $750 $750 Electric to Air Source Heat Pump $750 $750 Electric to Natural Gas Water Heater $200 $200 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 189 of 296 5 Second Refrigerator and Freezer Recycling Appliance Recycled $30 $30 Simple Steps, Smart Savings Showerhead Variable upstream buy-down Light-Emitting Diode (LED) Compact Fluorescent Bulb (CFL) “N/A” indicates measure offering was eliminated. However, some rebates may have been paid in the early months of the year, as Avista offers customers a 90-day grace period between project completion and when rebate materials must be submitted. Evaluation Methodology and Information Sources Cadmus’ approach to this residential portfolio-wide process evaluation relied on three main reviews and data-collection efforts. Table 3 indicates which data-collection activities we applied to each program. Table 3. Data Collection Activities Applied to Each Program Natural Gas and Electric Programs ENERGY STAR Homes  ENERGY STAR Products    High-Efficiency Equipment    Home Audit  Manufactured Home Duct Sealing  Opower   Weatherization and Shell    Electric-Only Programs Second Refrigerator and Freezer Recycling   Simple Steps, Smart Savings  Space and Water Conversions    *Customer surveys asking specifically about program participation. All residential customers groups targeted in general population studies. A description of each activity follows below. Materials and Database Review Cadmus’ document review focused gaining an up-to-date understanding of PY2012 - PY2013 program offerings, planning assumptions, participation, and marketing methods. Our review centered on the following materials:  Avista’s in-house tracking database; Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 190 of 296 6  UCONS’ duct sealing tracking data;  JACO’s appliance recycling tracking database;  CLEAResult invoice summaries;  Avista’s PY2012 and PY2013 DSM Business Plans;  An internal Avista program implementation manual;  Avista marketing collateral;  The Everylittlebit.com website; and  The Avistautilities.com website. Program Staff and Market Actor Interviews Interviews with program staff and market actors provided first-hand insights into program design and delivery processes, and helped evaluation staff interpret the information collected. We conducted program staff interviews in two rounds, one in January 2013 and another in January and February 2014. Table 4 provides a summary of interview data collection. Table 4. PY2012 - 2013 Program Staff Interviews Avista Program Implementation Staff 2* 2 Avista Policy, Planning, and Analysis Staff 1* 1* Avista Marketing Staff 1* Residential Behavior Implementation (Opower) Staff 1 * Multiple non-Cadmus staff participated in interview. Cadmus interviewed six members of Avista’s Washington and Idaho program staff, including:  Demand-side management (DSM) program managers;  Planning, Policy, and Analysis (PPA) team members; and  Marketing staff. Cadmus conducted these interviews in person in 2012 and by phone in 2013, using prepared interview guides. When necessary, Cadmus requested clarifying information via phone or e-mail. Staff interviews addressed the following topics:  Changes in measure offerings;  Goals;  Program design; Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 191 of 296 7  Implementation:  Marketing  Target markets  Tracking; and  Quality assurance and control (QA/QC) procedures. Cadmus conducted only one interview with staff representing third-party implementation companies. We determined that this was appropriate for the following reasons:  Cadmus interviewed representatives from Opower, the Residential Behavior Change program implementer, as this is a new program with high levels of participation.  Staff from JACO and CLEAResult participated in in-depth interviews in 2012 (to inform the PY2011 evaluation effort) and interviews with Avista staff identified few program changes and limited issues.  Cadmus did not interview staff implementing the Home Audit or the Manufactured Home Duct Sealing program. The Home Audit program completed in PY2013, and the Manufactured Home Duct Sealing Program is not expected to continue beyond PY2014. The interview centered on the following topics:  Goals;  Program design;  Implementation;  Marketing; and  QA/QC. Participating and General Population Customer Telephone Surveys Telephone surveys constituted a large part of PY2012 - PY2013 evaluation data collection activities, informing both impact and process evaluations of several programs. When conducting surveys, we took special care to address potential issues of bias in the following areas:  Sample selection (which customers to include in the survey sample frames);  Responses (are customers answering the survey as a group representative of the sample frame); and  Data analysis and reporting (analysis conducted with an appreciation for the sample selection and limitation of survey data collection). We conducted all surveys with the assistance of several subcontracted market research firms, selected for their experience with different data collection techniques and market segments. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 192 of 296 8 Participating Customer Surveys Participant telephone surveys offered important insights into program experiences for six residential measure categories (five programs),4 exploring the following topics:  Source(s) of program awareness;  Satisfaction;  Awareness of energy efficiency;  Participation barriers;  Freeridership and spillover; and  Customer characteristics. Cadmus conducted the participating customer surveys in two rounds, one in March and April 2013 and a second in February 2014. This approach ensured that respondents would have a clear recollection of their participation experience. Table 5 provides a summary of unique customers (identified using Avista account number) and surveys completed in each effort. Table 5. Residential Participant Details and Survey Sample (ID and WA) Natural Gas and Electric Programs ENERGY STAR Products 6,429 149 2% 782 65 8% Heating and Cooling Efficiency 3,747 142 4% 2,490 70 3% Water Heating 629 88 14% 316 60 19% Weatherization and Shell Measures 692 102 15% 313 60 19% Electric-Only Programs Second Refrigerator and Freezer Recycling 1,351 133 10% 1,319 65 5% Space and Water Conversions 171 34 20% 156 37 24% Total 13,019 648 5% 5,376 357 7% Cadmus designed participant survey completion targets to yield results with 90% confidence and ±10% precision levels, for measure-category level survey results. In 2012, we expanded this approach to yield results at the measure category and state level. Cadmus deemed this necessary as data collected through these surveys—specifically installation rates—were used to inform an impact assessment of 4 In 2011, Avista combined the Heating and Cooling Efficiency and Water Heating Programs into a single program, High Efficiency Equipment. Given the differences in these measure types and to ensure comparability to survey data collected for earlier evaluations, survey targets and analysis for these respondents remain separated. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 193 of 296 9 Avista’s residential programs. The participant survey sampling plan also drew upon multiple factors, including feasibility of reaching customers, program participant populations, and research topics of interest. Cadmus did not conduct participant surveys with Simple Steps, Smart Savings customers, as that program has an upstream focus and therefore does not track participant contact information. Similarly, for ENERGY STAR New Homes, Cadmus did not survey residential customers purchasing rebated homes because the program paid rebates to builders, not to end-use customers. Cadmus also did not focus evaluation resources on new programs that are subject to review by their own implementation organizations (i.e., Residential Behavior) or temporary programs (e.g., Home Audit). Within each program stratum, Cadmus randomly selected program participant contacts included in survey sample frames. A review of collected data shows geographic distribution of survey respondents clustered around urban centers, specifically the cities of Spokane, Coeur d’Alene, Pullman, Moscow, and Lewiston. This aligns with population distributions in Avista’s service territory. Figure 1 provides the distribution of participating customer survey respondents. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 194 of 296 10 Figure 1. Geographic Distribution of PY2012 - PY2013 Participating Customer Survey Respondents Given the wide range in program sizes, we weighted survey responses by participation (i.e., unique customers in each measure category) when reporting responses in aggregate, thus ensuring feedback represented the overall population. Table 6 shows the weighting scheme applied to PY2012 - PY2013 survey frequencies. Findings from PY2011 surveys included in comparisons also include post-survey weightings.5 5 Avista 2011 Multi-Sector Process Evaluation Report. Cadmus. 2012. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 195 of 296 11 Table 6. PY2012 - 2013 Participant Survey Sample Design and Weights by Program " A" " B" "A / B" 2012 Population and Achieved Surveys ENERGY STAR Products 6,429 149 43.15 Heating and Cooling Efficiency 3,747 142 26.39 Water Heating 629 88 7.15 Weatherization and Shell Measures 692 102 6.78 Second Refrigerator and Freezer Recycling 1,351 133 10.16 Space and Water Conversions 171 34 5.03 2013 Population and Achieved Surveys ENERGY STAR Products 782 65 12.03 Heating and Cooling Efficiency 2,490 70 35.57 Water Heating 316 60 5.27 Weatherization and Shell Measures 313 60 5.22 Second Refrigerator and Freezer Recycling 1,319 65 20.29 Space and Water Conversions 156 37 4.22 General Population Customer Surveys Cadmus conducted two market characterization studies to build on previous evaluation findings and supplement data from available regional resources, such as NEEA’s Residential Building Stock Assessment (RBSA). The purpose of this data collection was to help strengthen Avista’s understanding of:  Saturation of key energy-efficiency measures;  Key demographic and housing characteristics; and  Energy-use awareness, attitudes, and behaviors. Our primary market research activity consisted of a multi-method survey that leveraged direct mail, online web interface, and telephone calls to allow customer to complete the survey in the most convenient way. The goal of these surveys was to characterize Avista’s residential customers and allow Avista to identify savings opportunities and possible new measure offerings. Cadmus also used this data collection as a way to quantify nonparticipant customer spillover. We provide additional discussion on this topic below. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 196 of 296 12 Table 7. Residential General Population Surveys Completed in 2012 and 2013 2012 Survey Effort (n=1,051) Paper Survey 544 313 857 Online Survey 58 36 94 Telephone Survey 69 31 100 2013 Survey Effort (n=1,109) Paper Survey 589 330 919 Online Survey 60 30 90 Telephone Survey 65 35 100 Total 1,385 775 2,160 Cadmus did not apply weights to survey frequencies during analysis. We based this decision on the following rationale:  Customers included in the general population survey sample frames were chosen at random from Avista’s entire residential population.  The only screening was for completeness of customer contact information and removal of customers targeted as part of other EM&V surveys conducted in 2011 and 2012.  Cadmus concluded that there is no correlation between an inherent customer trait or characteristic and the method of responding to the survey chosen. Similar to the participant survey, the geographic distribution of survey respondents is clustered around urban centers. Figure 2 provides the distribution of general population survey respondents. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 197 of 296 13 Figure 2. Geographic Distribution of 2013 and 2014 General Population Survey Respondents All participating customer and general population survey proportions reported below only include feedback from respondents who could provide feedback—i.e., “don’t know” and “refuse” responses are not included in our reporting unless noted. Status of Evaluation Recommendations Avista retained Cadmus to perform annual process and impact evaluations of their residential program portfolio beginning PY2010. These evaluation activities, findings, conclusions, and recommendations are Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 198 of 296 14 articulated in the following reports: Avista 2010 Multi-Sector Process Evaluation Report and Avista 2011 Multi-Sector Process Evaluation Report.6 In this evaluation effort, Cadmus reviewed the recommendations offered in these documents and assessed to what degree Avista had adopted these recommendations (by the end of PY2013). As indicated in Table 8, Avista made significant progress toward addressing these recommendations. Table 8. Status of PY2010 and PY2011 Residential Process Recommendations Complete 8 4 In Progress 5 6 Limited Activity 2 2 A complete summary of recommendations and activity for addressing these recommendations is provided in Appendix A: Status of PY2010 and PY2011 Residential Evaluation Recommendations. Program Participation Savings and Incentives Table 9 provides the number of incentive-based measures and reported savings. The PY2012 and PY2013 Avista Impact Evaluation Reports explore the savings shown in Table 9 in detail. 6Avista 2010 Multi-Sector Process Evaluation Report. Cadmus. 2011. Avista 2011 Multi-Sector Process Evaluation Report. Cadmus. 2012. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 199 of 296 15 Table 9. PY2012 - PY2013 Program Populations and Adjusted Gross Savings Natural Gas and Electric Programs ENERGY STAR Homes 42 18 92 5,478 ENERGY STAR Products 7,233 857 898 13,204 High-Efficiency Equipment 5,906 3,670 1,029 555,076 Home Audit 477 0 0 0 Manufactured Home Duct Sealing 574 1,719 2,594 41,978 Opower 0 73,497 9,091 239* Weatherization and Shell 928 421 251 89,100 Electric-Only Programs Second Refrigerator and Freezer Recycling 1,438 1,415 1,580 0 Simple Steps, Smart Savings 435,561 596,828 49,373 0 Space and Water Conversions 187 168 3,839 0 Total 452,346 678,593 68,747 705,075 *Therm savings from the Opower program were very small and were not statistically significant. A thorough discussion of the adjusted gross savings provided in Table 9 can be found in PY2012 - PY2013 impact evaluation reports. Participation Trends A review of Avista’s residential portfolio over the past several years indicates several significant transitions, specifically:  A sharp increase and subsequent decrease in participation in the ENERGY STAR Products and Weatherization and Shell Programs (between 2008 and 2013);  Elimination of natural gas rebates in Idaho (November 1, 2012);  Reduction in the number of rebates offered for appliances (March 1, 2013); and  Commitment to developing and implementing new programs. Cadmus combined historical participation data from PY2008 through PY2013 to assess participation in Avista’s rebate programs at the program level. These data, shown in Figure 3, clearly indicate increased participation from PY2008 to PY2010, followed by a similarly abrupt decline in participation between PY2011 and PY2013. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 200 of 296 16 Figure 3. Reported Number of Rebates by Avista-Implemented Program: PY2008 - PY2013 This trend runs against trends observed in appliance sales data in Washington and Idaho for the same period. Overall sales generally dipped at the height of the recession and have since rebounded. Figure 4 shows population-normalized sales of several appliances in the ENERGY STAR Products Program (both code and high-efficiency) as reported by the Association of Home Appliance Manufacturers (AHAM) for Washington and Idaho from 2008 through 2013. This indicated that during this time period, a higher percent of appliance sold were likely high-efficiency. Figure 4. Population-Normalized AHAM Appliance Sales Data: 2008 - 2013 -80% -60% -40% -20% 0% 20% 40% 60% 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 2008 2009 2010 2011 2012 2013 Pe r c e n t C h a n g e Y e a r -to -Ye a r Nu m b e r o f R e b a t e s ENERGY STAR Products High-Efficiency Equipment Weatherization and Shell Space and Water Conversions ENERGY STAR Homes Percent Change Year-to-Year 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 Clothes Washers Refrigerators Freezers Dishwashers Nu m b e r o f A p p l i a n c e s P e r P e r s o n 2008 2009 2010 2011 2012 2013 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 201 of 296 17 Several explanations account for this decline in program participation. During interviews conducted to inform the PY2011, PY2012, and PY2013 evaluations, Avista staff reported that a major driver of the change was the expiration of many federal and state tax credits for energy-efficiency renovations and high-efficiency appliances offered under the American Recovery and Reinvestment Act of 2009. Staff reported these tax credits prompted increased participation in late 2009 and 2010, and beginning in 2011, participation slowed without that influence. This effect was particularly noticeable in the Weatherization and Shell Program. Another main cause of decline was the suspension of Avista’s natural gas program in Idaho beginning November 1, 2012 and plans to suspend natural gas programs filed in Washington. These changes led to a dramatic change in the fuel composition of the residential programs between PY2012 and PY2013. Figure 5 provides a graphical depiction of this change. The few natural gas incentives paid in Idaho in PY2013 were for applications submitted prior to the program change. Figure 5. Distribution of Rebates from Avista-Implemented Program Fuel Type: PY2012 - PY2013 Finally, in 2013 Avista also eliminated the ENERGY STAR appliance rebates (e.g., refrigerators, clothes washers, etc.). A primary driver of this decision was increasingly high observed customer freeridership in these measures and decreasing measureable gross savings. While Avista implemented this change in the beginning of PY2013, Avista continued to process appliance rebates for projects installed within the established 90-day grace period. This resulted in numerous units incented in the first half of 2013. Avista took this approach to limit customer confusion and dissatisfaction around termination of the measure offerings. Not surprisingly, these changes had a large impact on the most common types of measures incented through Avista’s program. Table 10 shows the most common measures incented in PY2011 - PY2013 by state, and the percent of rebates they represented. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 202 of 296 18 Table 10. Most Common Incented Measures: PY2011 - PY2013 Washington Measures 1 Refrigerator 15% Natural Gas Furnace 22% Natural Gas Furnace 47% 2 Natural Gas Furnace 12% Refrigerator 17% Variable Speed Motor 16% 3 Clothes Washer, Electric H20 11% Clothes Washer - Electric Water Heater 12% Refrigerator 6% 4 Clothes Washer, Natural Gas water Heater 11% Clothes Washer - Natural Gas Water Heater 11% Attic Insulation - Natural Gas Heat 4% 5 Window Replacement 8% Variable Speed Motor 8% Clothes Washer - Electric Water Heater 4% Idaho Measures 1 Refrigerator 16% Furnace 23% Variable Speed Motor 31% 2 Clothes Washer, Electric H20 14% Refrigerator 19% Clothes Washer - Electric Water Heater 20% 3 Furnace 13% Clothes Washer - Electric Water Heater 14% Refrigerator 14% 4 Clothes Washer, Natural Gas Water Heater 10% Variable Speed Motor 10% Air Source Heat Pump 12% 5 Dishwasher, Electric H2O 8% Clothes Washer - Natural Gas Water Heater 8% Air Source Heat Pump - Electric Heat 6% = Natural Gas Measure * Avista eliminated refrigerator and clothes washer measures March 1, 2013, but allowed rebates for projects completed in the 90-day grace period. This resulted in numerous rebates processed in the first half of the year. Despite cancelling natural gas rebates in Idaho, a review of program tracking data indicates only a small decrease in the percentage of Avista customers applying for multiple program rebates in a given program year. Over the past three years, PY2011 - PY2013, approximately one-quarter of participants applied for more than one rebate. Table 11 shows the results, which exclude participants in the lighting, refrigerator recycling, and behavior programs, as these are not rebate programs. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 203 of 296 19 Table 11. Number of Measures Installed One 14,062 77% 8,953 78% 2,813 74% Two 3,127 17% 1,936 17% 815 21% Three 784 4% 424 4% 153 4% Four 172 1% 91 1% 27 1% Five or more 75 0% 46 0% 15 0% Total 18,220 100% 11,450 100% 3,823 100% It is not uncommon for customers to participate multiple times over several years, although, as indicated in Table 12, this is becoming less common. This downtick is likely the result of more limited rebate offerings, particularly in Idaho, than in previous years. Table 12. Percent of Participants that Participated the Previous Year 2011 participants that participated in 2010 13% 2012 participants that participated in 2011 10% 2013 participants that participated in 2012 4% 2013 participants that participated in 2011 and 2012 1% Customer intentions expressed in PY2013 and PY2012 participant surveys show that the decline is not likely due to lack of customer interest. As indicated in Figure 6, when asked if they thought they would apply for additional rebates in the future, more than half of PY2013 respondents in every program answered in the affirmative. Further, we see a strong increase in the respondent interest in participation compared to results from PY2012 across all programs. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 204 of 296 20 Figure 6. Customer Interest in Repeat Program Participation The decline in rebate program participation is significant, but review of annual reports from other utilities in the region—Pacific Power in Washington, and Rocky Mountain Power and Idaho Power Company in Idaho—indicate similar reductions in participation in their electric rebate programs with comparable measure offerings. Figure 7 provides the number of reported rebates, by category, from year to year. All three utilities have experienced net negative growth, without exception, in the number of participants in these measure categories since 2011. Figure 7. Participation Trends Among in Rebate Programs among Regional Utilities: PY2008 - PY2012 59% 43% 56%61% 49% 42% 69% 58% 71%74% 60%62% 0% 10% 20% 30% 40% 50% 60% 70% 80% ENERGY STAR Products Heating and Cooling Efficiency Space and Water Conversions Water Heating Weatherization and Shell Measures Appliance Recycling 2012 (n=335)2013 (n=309) 0 5,000 10,000 15,000 20,000 20 0 8 20 0 9 20 1 0 20 1 1 20 1 2 20 0 8 20 0 9 20 1 0 20 1 1 20 1 2 20 0 8 20 0 9 20 1 0 20 1 1 20 1 2 20 0 8 20 0 9 20 1 0 20 1 1 20 1 2 Rocky Mountain Power (ID) Idaho Power Company (ID) Pacific Power (WA)Avista (ID & WA) Nu m b e r o f R e b a t e s HVAC (and Water Heating)Appliances Weatherization and Shell Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 205 of 296 21 While participation in Avista’s rebate programs has steadily declined for the last three years, Avista has maintained its commitment to third-party implemented programs—such as Second Refrigerator and Freezer Recycling—and regional programs such as Simple Steps, Smart Savings. Due to this support, participation in these programs has generally remained level or increased. In addition, in PY2012 - PY2013 Avista successfully implemented two pilot programs and a large, fully developed behavior change program. Figure 8 provides a summary of customer participation in these programs. For some programs, participation is shown in “100s” as participation in these programs is significantly higher than others. Figure 8. Reported Number of Rebates by Non-Avista-Implemented Program: PY2010 - PY2013 A possible reason for growth in the Simple Steps, Smart Savings Program is the recent introduction of two additional measures: energy-efficient showerheads (introduced in PY2012); and LEDs (introduced in PY2013). Table 13 provides additional detail on uptake of these new measures. Table 13. Simple Steps, Smart Savings Measures Incentives in PY2012 - PY2013 2012 1,784 0% 426,894 100% 0 0% 428,678 100% 2013 1,011 0% 564,300 95% 31,517 5% 596,828 100% Another possible reason is the increase in the number of participating locations. According to invoice materials, 92 locations participated in PY2012 compared to 125 in PY2013. These additional locations give Avista customer greater access to incented measures. 0 2,000 4,000 6,000 8,000 10,000 12,000 2010 2011 2012 2013 Nu m b e r o f M e a s u r e s Home Audit Manufactured Home Duct Sealing Residential Behavior (100s)Second Refrigerator and Freezer Recycling Simple Steps, Smart Savings (100s) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 206 of 296 22 Program Design, Management, and Implementation This section discusses Cadmus’ observations regarding design of Avista’s residential programs. These observations focused on program definition and organization, logic, and implementation approach. Overview Overall, we found Avista’s the residential program designs work well and are generally well- documented, primarily in the PY2012 and PY2013 DSM Business Plans. Further, we found Avista management and implementation organization staff to be knowledgeable about the programs and invested in their ongoing success. In general, the PY2012 and PY2013 the programs operated smoothly, with few significant issues. However, Cadmus did find one persistent program design issue. First noted in Cadmus’ 2010 residential program process evaluation,7 the naming convention of programs composing the residential portfolio is somewhat inconsistent across Avista Business Plans, marketing materials, and internal documents. In reviewing materials, it became clear that programs are often referred to with different names, and are organized differently within the portfolio. Table 14 identifies several programs as examples. Table 14. Example of Residential Program Naming Convention Re s i d e n t i a l Pr o g r a m s HVAC New Construction / Home Improvement High Efficiency Equipment Shell Home Improvement Weatherization Fuel-Efficiency Conversion from Electric ENERGY STAR Homes ENERGY STAR Homes ENERGY STAR / ECO-Rated Homes Program Logic Camus developed the logic model provided as Figure 9 to articulate the logic behind the residential programs included in this evaluation. 7 Avista 2011 Multi-Sector Process Evaluation Report. Cadmus. 2012. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 207 of 296 23 Figure 9. Avista Residential Program Logic Model Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 208 of 296 24 Implementation Approaches The residential portfolio includes programs with Avista administers, programs with third-party implementers, and programs operated as partnerships. This section summarizes our observations regarding Avista’s implementation decisions for each residential program. Avista residential programs are implemented both internally and with the assistance of several third- party organizations. Table 15 provides a summary. Table 15. Avista Residential Program Implementation Approach Natural Gas and Electric Programs ENERGY STAR Homes Avista and NEEA Mgmt., marketing, QA/QC, and rebate payment ENERGY STAR Products Avista All implementation activities High-Efficiency Equipment Avista Home Audit Municipal Partners Mgmt., marketing, QA/QC, and funding Manufactured Home Duct Sealing UCONS Residential Behavior Opower Mgmt. QA/QC, and invoice payment Weatherization and Shell Avista All implementation activities Electric-Only Programs Second Refrigerator and Freezer Recycling JACO Mgmt. QA/QC, and invoice payment Simple Steps, Smart Savings CLEAResult Space and Water Conversions Avista All implementation activities Staffing Despite these implementation partnerships, over the past several years, Avista has continued to invest in the implementation and management of its energy-efficiency portfolio. A review of Avista DSM labor projections articulated in the 2012 and 2013 DSM Business Plans indicates a generally increasing number of full-time-equivalent (FTE) staff dedicated to program implementation and management activities (Figure 10). Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 209 of 296 25 Figure 10. Avista DSM Labor Projections: PY2008 - PY2013 Also reflected in this staffing increase is the addition of a third and fourth Avista program manager in 2012. Avista added these program managers for the additional work associated with the Residential Behavior and Manufactured Home Duct Sealing Programs. Both staff had previous experience with Avista’s residential energy-efficiency programs. Interviews with Avista staff indicate staffing levels during PY2012 and PY2013 were adequate and no significant implementation staffing issues arose. The four program managers have responsibilities beyond residential program management. To support these program managers, a team of staff contributed to day-to-day program operations, including customer outreach, application review and processing, and data management. In addition to oversight, the program managers also conduct regular quality-assurance tasks. For example, the program manager responsible for Simple Steps, Smart Savings regularly visited participating retail stores to ensure correct prices and correct display of point-of-purchase signage. As Cadmus did not study Avista’s costs in administering these programs, this report does not address their relative efficiency. However, following a recommendation in the PY2011 process evaluation report, Avista and Cadmus staff discussed the possible benefits of contracting elements of the program implementation (e.g., rebate processing). The conversations, while focused, identified no compelling reasons for Avista to consider transferring additional program elements to third-parties at that time. Customer Interaction Feedback from Avista staff indicates customer satisfaction is a high priority for the organization, and energy-efficiency programs are viewed as a powerful method to engage with customers. To ensure customer satisfaction, Avista staff take care in program marketing to limit messaging that might confuse customers—such as why natural gas rebates are available in Washington but not Idaho—and to process rebate applications promptly—a common area for customer dissatisfaction in utility rebate programs. 4.00 6.10 10.70 11.60 11.45 17.00 21.00 23.10 27.70 28.60 28.45 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 2008 2009 2010 2011 2012 2013 Fu l l -Ti m e E m p l o y e e E q u i v a l e n t s Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 210 of 296 26 A review of program data indicates Avista has a strong record of processing rebates within days of receipt, although in PY2013 processing time slipped slightly (Table 16). This increased processing time is likely related to the elimination of the appliance rebates, leaving only the more complicated rebate applications that may take longer to process. The increase in processing time shown in Table 16, two days on average in PY2013 compared to less than a day in PY2012 and PY2011, is also primarily the result of a few applications with processing times far outside the normal range (e.g., greater than 100 days) skewed the average processing time upward. Many of these database entries contain notes indicating issues with customer application completeness. Table 16. Rebate Processing Times: PY2011 - PY2013 Average number of days 0.43 0.61 2.12 Less than one day 73% 80% 56% One day 19% 10% 17% Two days 2% 2% 4% Three days 4% 3% 4% Four days 1% 2% 5% Five or more days 1% 2% 14% To achieve these quick application reviews, Avista implements a structured review process supported by several internal staff. Review staff also regularly follow up directly with customers via telephone calls in the evening, when customers are likely to be home, to address application issues directly. In addition, an increased percent of participants are submitting their application paperwork in electronic format online (Table 17). Table 17. Percent of Applications Submitted In Electronic Format Online by Program All programs 5% 14% ENERGY STAR Homes 2% 6% ENERGY STAR Products 2% 2% High-Efficiency Equipment 8% 17% Weatherization and Shell 7% 8% Space and Water Conversions 5% 12% To inform both the impact and process assessments, Cadmus conducted desk reviews of more than two hundred applications in 2013 and 2014. Table 18 provides a summary. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 211 of 296 27 Table 18. Summary of Cadmus Desk Reviews ENERGY STAR Homes 20 18 ENERGY STAR Products 106 119 Home Improvement (HE equipment, weatherization, and conversion) 100 102 Total 226 239 While application processing is generally quick, Cadmus’ review of original application materials from PY2012 and PY2013 identified some issues with completeness of documentation. Table 19 lists elements that were missing in original application materials, as identified in our application review. No issues were identified in ENERGY STAR Home applications. Table 19. Summary of Missing Application Elements ENERGY STAR Products 1 36 Home Improvement 1 19 ENERGY STAR Products 2 23 Home Improvement 14 Internal Communication During the PY2011 process evaluation effort, Cadmus identified different perspectives among Avista staff around program planning and goal setting. In the PY2011 report, we noted: “program managers depicted the Planning, Policy, and Analysis (PPA) team as the driver of the planning processes, while the PPA team noted program planning was the responsibility of the program managers. This disconnect appeared to result in unmet expectations for both teams, and may have impeded effective collaboration.” To address this and other collaboration issues, between PY2012 and PY2013, Avista invested heavily in a self-evaluation of internal communication protocols (primarily between engineers, account executives, program managers, and PPA staff), and staff roles and responsibilities. To facilitate this assessment, Avista retained the services of Milepost Consulting, a third-party consulting firm specializing in process improvement. Cadmus was not directly involved in these activities. According to Avista staff, this self-evaluation effort has had a limited impact in addressing the issues, and communication and collaboration between groups continues to present challenges. Further, Avista initiated a reorganization of the DSM team in April 2014, which placed program implementation and PPA staff under one common Senior Director. Cadmus strongly supports Avista’s commitment to internal process improvements and decision to adjust the internal organization. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 212 of 296 28 Third-Party Program Implementation Avista uses third-party implementation contractors for four programs, not including the Home Audit Program: (1) Manufactured Home Duct Sealing; (2) Residential Behavior; (3) Second Refrigerator and Freezer Recycling; and (4) Simple Steps, Smart Savings. We provide a summary of these arrangements and an assessment of their effectiveness in the Effectiveness of Implementers section, below. Effectiveness of Implementers Using third-party implementers presents advantages and disadvantages. Generally, utilities maintain direct implementation of programs requiring intimate knowledge of unique customers (e.g., large commercial and industrial customers). Programs benefitting from a uniform approach involve national accounts, or require certain market expertise available from a third-party firm. Research conducted for this—and previous—Avista evaluation efforts leads us to conclude that Avista has succeeded in identifying which programs are most suitable for third-party contracting and partnering. The PY2011 evaluation report provides the results of detail interviews conducted with implementation staff at JACO and CLEAResult. As few changes have been made to these programs since these interviews took place in late spring 2012, we focused our evaluation efforts on Opower. Opower implements the Residential Behavior Program, which began in June 2013. Opower Opower is a publicly held (as of April 4, 2014) software-as-a-service company that partners with utilities to implement behavior-change programs. Based in Arlington, Virginia, Opower has been involved in the energy-efficiency space since 2007 and currently partners with nearly 100 utilities in the United States and abroad.8 In April 2014, Cadmus staff interviewed the Opower sales and engagement manager responsible for Avista’s program. Residential Behavior Program Description The Residential Behavior Program encourages electric customers to implement free or low-cost measures and adopt energy use practices and behaviors that reduce electric consumption. Program participants were selected by Avista (with support from Opower and Cadmus) and receive a Home Energy Report from Opower in the mail. All customer calls are addressed by Avista’s call center. The Home Energy Reports include the following information:  Comparisons of a customer’s usage in the current year to consumption in the same months in the previous year.  Comparison of a customer’s consumption to consumption of other, comparable customers in the same geographical area. This is known as the “Neighbor Comparison.”  Tips about how to save energy and reduce demand during peak times. These tips include: 8 Opower. April 8, 2014. http://opower.com/company. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 213 of 296 29  General conservation tips such as turning down the thermostat, turning off lights, shortening showers, etc.  Low-cost energy-efficiency tips, such as replacing incandescent bulbs with CFLs, installing weather stripping, and using power strips.  Tips about ways to reduce peak loads during peak load season and shift energy use to off- peak periods.  Information on other Avista residential programs. No financial incentives are provided through this program. According to the program theory, by educating customers about their energy use and conservation strategies, customers will gain knowledge to increase their energy efficiency and achieve cost savings. In addition, customers will become more engaged with Avista. Currently Opower reports only electric savings to Avista, although some customers may also have natural gas service and may take actions to reduce their use of this fuel as well. Avista and Opower may take steps to quantify these savings in the future. Residential Behavior Program Implementation Avista implemented this program using an experimental research design with random assignment of customers eligible for the program to treatment and control groups. From their residential customer population, Avista, with support from Opower and Cadmus, selected approximately 70,000 customers for inclusion in a treatment group and 13,000 customers in two, state-specific, control groups (a total of 26,000 customers). Avista did not consider natural gas-only customers. Based on initial cost- effectiveness analysis for program planning, Avista set a minimum energy consumption threshold of 18,000 kWh per year for targeted households. In order to fully populate the participant and control groups in both Washington and Idaho, Avista reduced this threshold to approximately 16,000 kWh as the program was deployed. Treatment group customers received Home Energy Reports beginning in June 2013 and then according to the schedule provided in Table 20. To use implementation resources such as printing and call center staff as efficiently as possible, Opower mails reports in batches staggered throughout the month. Control group customers did not receive Home Energy Reports and were not informed that they belonged to the control group. Opower uses this general approach for most of the programs it implements. Table 20. Home Energy Report Deliver Schedule Home Energy Reports sent  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 214 of 296 30 Opower works with Avista’s billing department to access customer billing data. Using these data, Opower staff quantify program kWh savings. Cadmus reviewed the saving estimates as part of the PY2013 impact assessment and performed an independent billing analysis to determine gas and electric savings.9 According to Opower implementation staff, the Residential Behavior Program has operated as anticipated since inception with only minor challenges. Staff report a very strong relationship with Avista, noting the Avista team is: “super responsive, very polite, and very nice to deal with…overall it’s one of the health[iest] client relationships we have.” The only challenge noted has been with the customer usage data used to populate the Home Energy Reports, but both Opower and Avista are aware of the issue and are working to streamline the process. Participant feedback to the program has been positive. While data were not readily available for this evaluation, implementation staff estimated that—so far—less than one percent of participants have contacted Avista expressing dissatisfaction in the program, and opt-out rates are lower than expected. Only 1.0% of customers in Washington and 1.1% of customers in Idaho have requested to be removed from program mailings as of April 2014. Future of the Residential Behavior Program Given the success of the program, in terms of both implementation and achieved energy savings, Avista and Opower have discussed the possibility of either expanding the program or fine-tuning by targeting specific customer groups. No firm plans are in place, but discussions around this topic are scheduled for later in spring 2014 in order to consider results of Cadmus’ impact evaluation of the program. Given that Avista has already included all cost-effective customers in their target population for this program, future opportunities for expansion may be limited. Data Tracking For each residential program evaluated, Avista or the program implementer provided Cadmus with tracking data. Tracking data were contained in five separate files:  Avista’s internal, multi-program tracking database;  Manufactured Home Duct Sealing tracking spreadsheets;  JACO tracking database;  Opower tracking database; and  Simple Steps, Smart Savings invoice material. Cadmus examined each dataset to: 9 Avista 2012-2013 Washington Electric Impact Evaluation Report. Cadmus. 2014. Avista 2012-2013 Idaho Electric Impact Evaluation Report. Cadmus. 2014. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 215 of 296 31  Determine data fields tracked;  Inform process and impact evaluation activities; and  Assess the data-tracking processes’ effectiveness. The assessment also sought to identify potential evaluability barriers presented by current tracking processes. Data Tracking Summary Avista’s Internal Multi-Program Tracking Database The tracking database included participant, measure-level data for the following programs:  ENERGY STAR Homes;  ENERGY STAR Products;  High-Efficiency Equipment;  Home Audit;  Weatherization and Shell; and  Space and Water Conversions. The internal, multi-program database serves as the electronic repository for customer data collected from application forms, including data for programs Avista implements internally. The two annual extracts provided for this evaluation effort contained 38 variables, constituting six kinds of information. Table 21 summarizes these data. Table 21. Avista Internal Tracking Database Fields Customer Information Number / Text “State, CUSTOMER_NME, Home Sq Ftg, Year Built” Incented Equipment Information Date / Number / Text “Cost, Efficiency Rating, New R Value, Install Date” Measure / Rebate Quantities Number “Number of Rebates” Measure and Program Designation Number / Text “Marketing Measure Type, Marketing Measure Desc” Payment and Savings Number “Rebate Amount, Est KWH Saved, Est Therms Saved” Processing Date-Stamps and Notes Date / Text “App Rcvd Date, Payment Processed Date” We also know from ad hoc requests that Avista tracks several other data in addition to the items outlined above. These variables include a “Do Not Solicit” customer flag and several customer contact and billing information fields with additional detail and formatting. Manufactured Home Duct Sealing Tracking Spreadsheets The Manufactured Home Duct Sealing data extract reviewed in this evaluation contained three quarterly summaries. Tracking data contained 36 fields, including: customer address; Avista account information; Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 216 of 296 32 duct-sealing services performed; and energy savings estimates. We understand from conversations with program staff that information on each job are provided in bulk by UCONS, the implementer and additional fields are then added by Avista staff during the QC process. JACO Tracking Database JACO tracks data on participating customers, their pick-up orders, and refrigerators and freezers recycled through the program. These data are provided in three separate, integrated spreadsheets, allowing comprehensive tracking of customers’ and units’ movements through the program. Through our experience evaluating Avista’s Second Refrigerator and Freezer Recycling program and other similar utility-sponsored appliance recycling programs implemented by JACO, we know these data files are consistent in content and format with JACO’s standard program tracking. While these data are detailed, providing extensive information on the customer, pick-up, and equipment recycled, Cadmus noted the absence of an Avista customer account number. JACO assigned customers their own unique customer identification numbers.10 This made it difficult to match customers participating in this program to other program tracking databases. Opower Tracking Database Opower, the Residential Behavior program implementer, provided the program tracking data we reviewed for this program. The tracking database contained only 10 fields for each participating customer, listed in Table 22. Table 22. Opower Data Tracking Fields “opower_customer_id” “utility_customer_id” “customer_name” “service_address” “recipient_status” “opt_out_date” “inactive_date” “include_in_test_analysis” “deployment_wave” “first_generated_date” Through our experience evaluating other residential behavior programs implemented by Opower, we know these data files are consistent in content and format with their standard program tracking. 10 Customers sign up for the program, either online via Avista’s website or by calling JACO’s toll-free number. They are asked a few questions to verify eligibility, they must be Avista electric customers, and their refrigerator or freezer must meet certain criteria to participate. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 217 of 296 33 However, unlike tracking data from other third-party program implementers, this dataset includes Avista customer account number (utility_customer_id). Simple Steps, Smart Savings Invoice Material Cadmus received data on the Simple Steps, Smart Savings Program. This program tracks monthly reporting from CLEAResult. In interviews conducted to inform both this and the PY2011 evaluation, Avista and CLEAResult staff noted monthly reporting for this program often involved delays and adjustments, caused by difficulties in obtaining sales data from retailers in a timely manner. CLEAResult monthly invoices contained detailed data at the measure level, reporting adjustments to previous months, and current monthly sales at each participating retailer by Stock Keeping Unit code (SKU). Data reviewed for this evaluation contained slightly different fields, but both provided information on:  Participating retailer (e.g., name and location);  Measures (e.g., manufacturer, type, SKU, watts/GPM, etc.);  Sales and sales adjustments; and  Reporting period. Planned Changes in Avista Data Tracking In addition to maintaining the internal tracking database discussed above, Avista is currently engaged in a large, multi-year transition to an advanced customer care and billing system, supported by Oracle®. This transition has been in progress since 2012. In July 2014, Avista hopes to begin moving some aspects of its energy-efficiency program tracking to this new system. Anticipated benefits with this new system include improved access to complete customer account information, enhanced market segmentation tools, and targeted marketing campaigns. Marketing and Outreach Marketing Approach Avista develops, executes, and oversees the marketing efforts to promote its residential rebate programs in Washington and Idaho. These efforts include paid media, social media, earned media, direct mail, website, and broad-based awareness building through the “When it comes to energy efficiency, every little bit adds up” (Every Little Bit) campaign, along with the Efficiency Matters campaign. Most of the outreach tactics include general promotion of the residential rebates, with individual measure or program promotion as needed. Additionally, some program implementers supplement Avista’s marketing through their own turnkey efforts. Avista’s energy-efficiency marketing efforts are also coordinated with regional efforts. Cadmus conducted a review of Avista’s residential energy-efficiency rebate program marketing efforts to: Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 218 of 296 34  Gain an understanding of PY2012 and PY2013 energy-efficiency and program marketing strategies and processes;  Understand customer response and gauge effectiveness of marketing efforts; and  Identify gaps and/or opportunities for consideration in future marketing efforts. As part of this effort, Cadmus conducted a marketing materials review. We also reviewed marketing- related survey results and Avista marketing staff interview findings. Marketing Objectives and Strategies As found through review of the 2013 marketing plan and as supported through the interview with Avista marketing staff, the overarching outreach objectives are to increase awareness of and participation in Avista’s energy-efficiency programs for residential customers. The outreach strategy is to use varied media to highlight customer success stories and communicate program benefits through engaging and interactive promotions and partnerships. Avista’s DSM plan also indicates that residential programs have a strong presence and coordination with regional efforts, such as those offered by NEEA. In our interview with Avista’s key marketing staff, we discussed energy efficiency marketing successes and challenges in the PY2013 year. Overall, Avista staff reported the marketing efforts had been successful—specifically the online Every Little Bit and Efficiency Matters campaigns and high-performing targeted online advertisements. Staff indicated the crossover between Washington and Idaho (and offerings, based on fuel type and regulations) continues to prove challenging with regard to messaging and delivery of mass media. Staff reported they believe the Every Little Bit and Efficiency Matters campaigns are helping to increase broad-based reach to audiences without the use of mass media. In looking forward, staff indicated a need to enhance energy-efficiency awareness and participation through deeper and more meaningful customer engagement. Avista staff hope to learn more about customer motivators and how staff can increase customer engagement along the path to participation in residential energy-efficiency programs. Planning and Processes Avista staff conducts the planning, design, and execution of the residential rebate program marketing efforts. As indicated in the PY2012 and PY2013 DSM plans, there is an internal collaborative process to develop general energy-efficiency marketing and promotions. This process incorporates feedback from the Energy Solutions, Services Development and Marketing, and PPA teams. Some of the turn-key programs, such as the Second Refrigerator and Freezer Recycling Program, include supplemental marketing as part of their program design and implementation plans. Avista’s marketing staff uses the Avista Design System Guidelines to ensure that energy-efficiency marketing and outreach materials deliver a consistent look, feel, and message. The guidelines address items such as logos, color palettes, and fonts, and give an overview of applications, with examples of properly branded materials and collateral. All PY2012 and PY2013 general energy-efficiency marketing materials appear to be aligned with the guidelines. The Every Little Bit and Efficiency Matters campaigns Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 219 of 296 35 and Online Energy Advisor tool present slightly varied creative assets, although generally appear to follow the brand guidelines (i.e., fonts, logos, etc.). Target Audience and Customer Motivators The target audience for Avista’s residential rebate programs is general, and Avista has not specifically segmented customers or targeted outreach efforts. However, based on interviews with Avista staff, the marketing strategy uses a variety of outreach channels to reach a mix of demographics. For example, print ads are used to reach an older customer audience, while online advertisements are aimed at a younger demographic. Although segmentation efforts have been limited to date, Avista staff hopes to have a better grasp of customer segments and preferences in the future. Avista reported conducting a residential customer market research survey in 2013 with 400 customers in both Washington and Idaho. The purpose of the research was to gauge awareness of Avista’s programs and to gain insights to key motivators and messages. Avista will use these data to develop its PY2014 marketing and messaging strategies. The participant surveys conducted by Cadmus also explored motivations for program participation. The most common responses from PY2012 and PY2013 are provided in Figure 11. The most commonly reported deciding factors were old equipment working poorly (26%, up from 12% in 2012) and old equipment not working (22% up from 18% in 2012). The two responses totaled 48% in 2013. Responses reflect the changing composition of residential rebate offerings. The response “like the appearance of the new item more” is a common response amount customers who received a rebate for an energy- efficient appliance—which were eliminated in PY2013. Figure 11. Most Commonly Reported Measure Purchase and Installation Motivations 11% 7% 13% 13% 18% 12% 2% 9% 14% 15% 22% 26% 0%5%10%15%20%25%30% Liked the appearance of the new item more Recommendation of dealer/retailer Wanted to reduce energy costs Wanted to save energy Old equipment didn't work Old equipment working poorly 2013 (n=251)2012 (n=473) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 220 of 296 36 Outreach Channels Avista conducts residential energy-efficiency marketing through a variety of channels. In addition to the general energy-efficiency marketing tactics outlined below, Avista conducts broad-based awareness efforts through its Every Little Bit campaign, as described in the following section. Besides the Efficiency Matters campaign (which are implemented in partnership with KREM 2, a CBS affiliates), there are no mass media or cross-cutting promotional efforts related directly to program offerings, to avoid potential customer confusion across state lines.11 Notable outreach tactics used in PY2012 and PY2013 include:  Paid media: print and online (targeted SEO) banner advertisements;  Social media: Facebook, specifically for campaign and ticket giveaway;  Earned media: local public relations as available;  Direct mail and bill inserts: general and (targeted) program-specific;  Newsletters and e-mail blasts: general outreach;  Website: website (avistautilities.com) was built in 2012; and  Vendor outreach meetings: general overview about programs, application process, project qualifications and customer eligibility. Every Little Bit and Efficiency Matters Campaigns The Every Little Bit campaign launched in 2007 and was informed by findings from market research efforts that gauged customer awareness, willingness to participate, and barriers to participation. The broad-based, multi-media awareness campaign was designed to increase customer engagement and drive awareness of Avista’s energy-efficiency program offerings. Over the years, the campaign has used multiple channels, including website, web banners, print and broadcast outreach (radio and television), print material (brochures, signage, etc.), outdoor billboards, social media, and community events. The objective of the campaign is to educate and inform customers about general energy efficiency programs, with the goal of driving participation. The call-to-action drives customers to Avista’s campaign website (www.everylittlebit.com) to take advantage of energy saving programs from Avista. During subsequent years, the program design shifted to become progressively more specific. Most recently, KREM 2’s Project Green, Toyota and Avista have teamed up in support of energy efficiency, and initiated the Efficiency Matters campaign. Through this campaign, customers entered to win a Toyota Prius by pledging a commitment to energy efficiency. Objectives of the most recent campaign were to:  Increase awareness of and participation in Avista’s energy conservation measures and rebate programs;  Increase traffic to www.everylittlebit.com; 11 Avista also partnered with the Inlander newspaper and ACE Hardware to promote its Home Energy Advisor online audit tool. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 221 of 296 37  Increase traffic and “likes” to the Efficiency Matters Facebook page; and  Allows people to receive ongoing energy-efficiency tips. Through its partnership with KREM TV and Toyota, Avista’s campaign garnered more than 103,000 entries in 2013, with 4,159 people searching for the Every Little Bit keyword. There were 66,907 total entries the previous year. Materials and Messaging Cadmus reviewed all residential energy-efficiency marketing materials provided by Avista. Overall, the general marketing materials present a consistent look and feel, and follow the Avista Design System Guidelines (e.g., fonts, colors, layout, and applications). Materials typically include the Avista logo (appropriately) and a call-to-action, which is usually one of Avista’s websites (or campaign URL). The online advertisements direct customers to the program webpage, which serves as a portal for customer engagement, education and interaction and provides links to rebates and tips. Several of the general marketing materials also include program-appropriate imagery, which may help customers understand and relate to the promoted offerings. Through our review of PY2012 and PY2013 materials, we found there are several uniform resource locators (URLs) included in the collateral, and some items including more than one URL (e.g., www.everylittlebit.com, www.everylittlebit.com/findrebates, www.avistautilities/resrebates). Inconsistent use or use of more than one URL may distract customers and possibly cause confusion. While the materials reviewed focused primarily on the general residential rebate marketing materials, Cadmus also reviewed Every Little Bit and Efficiency Matters campaign outreach materials and Avista’s energy-efficiency web pages, and conducted a high-level review of the Online Energy Advisor materials as a point of reference. Based on this cursory overview of the suite of programs and platforms, Cadmus found that there are varied creative assets across the channels and platforms. While the general energy- efficiency promotional materials present a look and feel consistent with the brand guidelines, the Every Little Bit and Efficiency Matters campaigns and Online Energy Advisor platforms leverage additional assets. For example, the Every Little Bit landing page (www.everylittlebit.com) also includes assets from the Online Energy Advisor personas (with the “shield” creative) and creative developed by a third-party implementer. Marketing Execution and Measurement Avista tracks metrics for its individual campaigns and ties results back to awareness and website traffic. In PY2013, Avista staff reported tracking online advertisements (click-through rates), Every Little Bit and Efficiency Matters campaign metrics (participants and traffic), estimated impressions through paid media and response to direct mail (as applicable). Sources of Participant Awareness To help assess the effectiveness of Avista’s and the implementer’s marketing; Cadmus asked participants how they heard of the program in which they participated. Respondents cited a variety of Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 222 of 296 38 sources of program awareness. Figure 12 lists the top ways respondents said they first heard about the program in both the PY2012 and PY2013 surveys. PY2013 respondents who could provide an answer reported hearing about the program through their contractor (28%), with other responses fairly evenly distributed across information from electric or gas bill (16%), word of mouth (14%), and the Avista website (12%). When Cadmus compared 2012 and 2013 findings, a few key differences emerged:  More respondents heard about the program from a contractor in 2013 (17% in 2012, 28% in 2013).  Fewer respondents heard about the program from a retailer/distributor in 2013 (15% in 2012, 6% in 2013).  Fewer respondents heard about the program from an Avista representative in 2013 (11% in 2012, 7% in 2013). Figure 12 provides additional customer responses. Figure 12. Most Commonly Reported Ways Participants First Heard About the Program Not surprisingly, the ways participating customers first learned of the Avista rebates differs by program. For example, we would expect customers seeking HVAC and weatherization rebates heard of the program from their contractor, while ENERGY STAR Products customers more commonly heard of the rebate from a retailer. Figure 13 provides the most common responses by program. 15% 11% 11% 10% 16% 17% 6% 7% 12% 14% 16% 28% 0%5%10%15%20%25%30% Retailer/Dealer Avista representative Avista Website Family/friends/word-of-mouth Information with my electric or gas bill Contractor 2013 (n=323)2012 (n=597) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 223 of 296 39 Figure 13. Most Commonly Reported Ways Participants First Heard About the Program by Program Avista Customer Awareness of Energy-Efficiency Rebates More than half of Avista’s residential customers report being aware Avista offers rebates for energy- saving equipment and weatherization improvements when asked as part of the Avista general population studies. Indicated in Figure 14, 63% of customer surveys in 2012 and 54% of customers surveyed in 2013 reported being aware of Avista rebates (prior to completing the survey). The decrease in awareness reported in 2013 compared to 2012 may reflect the reduction in rebate offerings in Idaho as well as the challenges Avista faced in marketing dissimilar measure offerings across the two states. 27% 25% 45% 37% 25% 22% 19% 27% 38% 35% 45% 31% 0%10%20%30%40%50% Retailer / dealer (n=16) Retailer / dealer (n=35) Contractor (n=29) Contractor (n=48) Avista website (n=9) Contractor (n=7) Contractor (n=10) Utility bill insert (n=21) Contractor (n=21) Contractor (n=33) Utility bill insert (n=25) Utility bill insert (n=38) 20 1 3 20 1 2 20 1 3 20 1 2 20 1 3 20 1 2 20 1 3 20 1 2 20 1 3 20 1 2 20 1 3 20 1 2 EN E R G Y ST A R Pr o d u c t s He a t i n g & Co o l i n g Ef f i c i e n c y Sp a c e & Wa t e r Co n v e r s i o n Wa t e r He a t i n g Wx & S h e l l Ap p l i a n c e Re c y c l i n g Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 224 of 296 40 Figure 14. Avista General-Population Customer Awareness Customers who reported being aware of Avista rebates indicated that information in their utility bill was the most common way they learned of the measure offerings (38% in 2012 and 43% in 2013). Word of mouth (13% and 14%), the Avista website (11% and 9%) and TV advertisements (11% and 8%) were the next-most-common responses, although feedback was diverse. Figure 15 provides additional detail. Figure 15. Source of General-Population Customer Awareness Participant Experience and Satisfaction To assess customer satisfaction in the residential program and program elements, Cadmus included questions around these topics in participant customer surveys. Overall, as in past evaluations, Cadmus 63% 54% 37% 46% 0% 10% 20% 30% 40% 50% 60% 70% 2012 (n=1,019)2013 (n=1,058) Aware of Avista rebates (prior to taking survey) Not aware of Avista rebates 0%5%10%15%20%25%30%35%40%45% Something else Other website Billboard Event Social media (Facebook, Twitter, etc.) Magazine Avista representative Radio Contractor Newspaper TV Avista website Family / friends / word-of-mouth Information with electric or gas bill 2013 (n=865)2012 (n=1,073) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 225 of 296 41 observed generally very high customer satisfaction across the programs and program elements. The sections below provide additional detail. Overall Program Satisfaction Cadmus asked surveyed participants to rate their overall satisfaction with the program as well as their satisfaction with various program aspects. As Figure 16 shows, overall satisfaction with the programs in PY2013 was very high, with 99% of participants describing themselves as somewhat satisfied or very satisfied with the program in which they participated. This finding closely resembles findings from PY2011 and PY2012, where 98% and 99% of respondents reported satisfaction, respectively. While general satisfaction remained the same across program years, the proportion of participants that were very satisfied rose steadily each year from PY2011 through PY2013. Figure 16. Overall Participant Satisfaction across All Programs As Figure 17 shows, participants expressed generally consistent, high overall satisfaction across programs, with an appreciable increase in very satisfied Heating and Cooling Efficiency Program participants from 2012 (82%) to 2013 (93%). 1%1% 18% 80% 0%1% 16% 83% 1% 10% 89% 0% 20% 40% 60% 80% 100% Not at all satisfied Not very satisfied Somewhat satisfied Very satisfied 2011 (n=461)2012 (n=645)2013 (n=354) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 226 of 296 42 Figure 17. Overall Participant Satisfaction by Program and Year Rebate Amount and Promptness Satisfaction In the survey, Cadmus asked participants how satisfied they were with the amount of the rebate they received and how quickly they received the rebate. Rebate Amount As shown in Figure 18, respondents reported slightly lower satisfaction levels with rebate amounts than with the overall program. This is not uncommon, as most peopled feel they would be made happier if provided with a larger rebate. As shown in Figure 19, participants expressed generally consistent satisfaction with rebate amounts across all programs. However, participant satisfaction (those who said they were somewhat or very satisfied) with the Water Heating Program decreased slightly from 97% in 2012 to 90% in 2013. It is unclear what prompted this decline. 15%15%17%6%18%11%18%19%23%12%15%14% 83%85%82%93%82%86%79%80%77%88%84%86% 0% 20% 40% 60% 80% 100% 2012 2013 2012 2013 2012 2013 2012 2013 2012 2013 2012 2013 ENERGY STAR Products Heating and Cooling Efficiency Space and Water Conversions Water Heating Weatherization and Shell Measures Appliance Recycling Somewhat satisfied Very satisfied Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 227 of 296 43 Figure 18. Weighted Rebate Amount Satisfaction for all Programs Figure 19. Rebate Amount Satisfaction by Program and Year Promptness of Rebate Payment As shown in Figure 20, respondents reported slightly lower satisfaction with rebate promptness than overall program satisfaction, but slightly higher satisfaction than with the rebate amount. The proportion of respondents who were very satisfied with rebate promptness increased slightly from 81% in 2011 to 88% in 2012, but decreased to 80% in 2013. This may reflect the minor uptick in rebate processing times identified in Table 16. 0 1% 32% 67% 2% 38% 61% 2%2% 30% 67% 0% 20% 40% 60% 80% Not At All Satisfied Not Very Satisfied Somewhat Satisfied Very Satisfied 2011 (n=454)2012 (n=632)2013 (n=347) 43%45%30%23%32%31%43%41%30%27%32%32% 54%52%70%74%65%64%54%49%70%73%65%65% 0% 20% 40% 60% 80% 100% 2012 2013 2012 2013 2012 2013 2012 2013 2012 2013 2012 2013 ENERGY STAR Products Heating and Cooling Efficiency Space and Water Conversions Water Heating Weatherization and Shell Measures Appliance Recycling Somewhat Satisfied Very Satisfied Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 228 of 296 44 Figure 20. Weighted Rebate Promptness Satisfaction for All Programs As Figure 21 shows, respondent satisfaction with rebate promptness was relatively high across programs. However, the proportion of respondents who were very satisfied with the promptness of their Energy Star product rebates decreased from 89% in 2012 to 69% in 2013. Figure 21. Rebate Promptness Satisfaction for All Programs 0%2% 17% 81% 0%0% 11% 88% 20% 80% 0% 20% 40% 60% 80% 100% Not at all satisfied Not very satisfied Somewhat satisfied Very satisfied 2011 (n=451)2012 (n=611)2013 (n=340) 11% 29% 10%15%12%19%9%21%9%12%21%24% 89% 69% 90%85%85%81%89%76%88%88%76%76% 0% 20% 40% 60% 80% 100% 2012 2013 2012 2013 2012 2013 2012 2013 2012 2013 2012 2013 ENERGY STAR Products Heating and Cooling Efficiency Space and Water Conversions Water Heating Weatherization and Shell Measures Appliance Recycling Somewhat satisfied Very satisfied Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 229 of 296 45 Residential Program Freeridership and Spillover Freeridership Freeridership, the percentage of savings likely to have occurred in the program’s absence, traditionally refers to participants who would have undertaken an action promoted by a program had the incentive or other program activities not been available. Full freeriders would have undertaken exactly the same action at the same time (i.e., the program had no effect on the degree or timing of their actions). Partial freeriders would have taken some action, but would not have undertaken the action to the level promoted by the program, or would not have taken the action at the time they did. For the PY2012 - PY2013 evaluation, Cadmus estimated freeridership by measure type: appliances; HVAC and water heating; and weatherization and shell using data from surveys with participating customers. We established this grouping based on the needs of the impact evaluation. The customer self-report approach to estimating freeridership adheres to standard industry methodologies. However, the approach does present a potential shortcoming: it may not always be entirely appropriate for capturing the market transformation impacts of multiyear programs. For example, a multiyear program may alter the availability of higher-efficiency products in a region by influencing dealers’ and retailers’ stocking practices. In addition, by increasing dealer experience and comfort with more efficient products, or by impacting demand for efficient products, a program may influence the mix of products manufactured. Customers, when choosing between various makes and models of a given product, may not be aware that a program affected their efficiency selection. Therefore, while a customer may correctly state that he or she would have chosen a particular product in the program’s absence, the availability of that product may have been a result of the program. While the customer would count as a freerider, the customer may have had less-efficient options without the program. A more thorough description of the freeridership methodology is provided in: Avista 2012- 2013 Washington Electric Impact Evaluation Report; and Avista 2012-2013 Idaho Electric Impact Evaluation Report.12 Figure 22 show the freeridership results for the PY2012 and PY2013 program, by fuel type. Estimates from previous evaluations are also provided for context. Further, due to limited participants, before PY2012, Cadmus did not break out freeridership scores by fuel. Cadmus did not calculate separate freeridership estimates for conversion measures in PY2010 and PY2011 for the same reason. 12 Avista 2012-2013 Washington Electric Impact Evaluation Report. Cadmus. 2014. Avista 2012-2013 Idaho Electric Impact Evaluation Report. Cadmus. 2014. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 230 of 296 46 Figure 22. Observed Participating Customer Freeridership (Washington & Idaho) A review of freeridership scores over the past four evaluation efforts indicates a clear upward trend in self-report freeridership—particularly among appliance and HVAC measures. This finding suggests the market for these equipment types may be transformed, and incentives from Avista are less of a factor in customer decision-making. This supposition is supported by a review of available secondary data. As indicated in Figure 23, which shows assumed appliance saturation in Washington and Idaho provided by the NWPCC Regional Technical Forum13, there is little opportunity for customers to purchase and install non-ENERGY STAR certified equipment. The NWPCC Regional Technical Forum estimates are derived from the California Energy Commission (CEC) Appliance Database. 13 2014 NWPCC Regional Technical Forum Unit Energy Savings (UES) Measures and Supporting Documentation http://rtf.nwcouncil.org/measures/Default.asp 48% 62% 79%76%82%81% 39% 58%67%59%68%72%63%62% 45% 33% 50% 37% 56%55% 0% 20% 40% 60% 80% 100% 20 1 0 ( n = 6 7 ) 20 1 1 ( n = 9 4 ) 20 1 2 G a s ( n = 3 2 ) 20 1 2 E l e c t r i c ( n = 1 1 7 ) 20 1 3 G a s ( n = 8 ) 20 1 3 E l e c t r i c ( n = 5 7 ) 20 1 0 ( n = 6 7 ) 20 1 1 ( n = 1 5 5 ) 20 1 2 G a s ( n = 1 3 7 ) 20 1 2 E l e c t r i c ( n = 5 1 ) 20 1 3 G a s ( n = 8 2 ) 20 1 3 E l e c t r i c ( n = 4 8 ) 20 1 2 E l e c t r i c ( n = 7 6 ) 20 1 3 E l e c t r i c ( n = 3 7 ) 20 1 0 ( n = 6 7 ) 20 1 1 ( n = 3 7 ) 20 1 2 G a s ( n = 8 7 ) 20 1 2 E l e c t r i c ( n = 1 5 ) 20 1 3 G a s ( n = 4 9 ) 20 1 3 E l e c t r i c ( n = 1 1 ) Appliances HVAC & Water Heating Conversion Wx & Shell Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 231 of 296 47 Figure 23. ENERGY STAR Appliance Saturation Further, indicated in Figure 24 which shows average freeridership scores across all measures by incentive amount (in $100 bins), customers receiving smaller incentive payments are most likely to be freeriders. As all Avista rebates for appliances were less than $50, it follows that freeridership is highest in these measures. Figure 24. Observed Participating Customer Freeridership by Incentive Amount 80%86% 75% 42% 0% 20% 40% 60% 80% 100% Clothes Washer (2010-2013 CEC Data) Dishwasher (2010-2012 CEC Data) Refrigerator (2010-2013 CEC Data) Freezer (2010-2012 CEC Data) ENERGY STAR Saturation 74% 60%52% 64% 40% 43% 35% 54% y = -0.0375x + 0.6952 R² = 0.4964 0% 10% 20% 30% 40% 50% 60% 70% 80% $0-$100 (n=415) $101-$200 (n=69) $201-$300 (n=54) $301-$400 (n=185) $401-$500 (n=17) $501-$600 (n=9) $601-$700 (n=7) $701-$800 (n=51) Av e r a g e F r e e r i d e r s h i p S c o r e Average Freeridership Linear (Average Freeridership) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 232 of 296 48 Avista has already responded to high levels of observed freeridership in the appliance measure category by discontinuing these measure offerings (Table 2). Spillover Spillover refers to additional savings generated by program participants due to their program participation, but not captured by program records. Spillover also includes savings from actions non- participating customers take because of program messaging or market effects. These savings are also not captured in program tracking. Energy-efficiency programs’ spillover effects can be considered an additional impact that gets credited to program results. In contrast, freeriders’ impacts reduce the net savings attributable to a program. In this evaluation, Cadmus measured spillover achieved through the installation of measures without utility rebates through surveys with participant end-users and general population customer surveys (representing nonparticipating customers). We found these savings to be the easiest to quantify through self-report surveys, an approach in-line with evaluation best-practice. In these surveys, we asked customers whether they had installed any other energy-efficient equipment or had services performed in their homes for which they did not receive an incentive from Avista or another organization. Next we cross-checked respondents against PY2012 - PY2013 Avista and third- party implementer databases to confirm that the customers had not received a utility incentive for the reported measure. From this subset, Cadmus removed participants who did not indicate rebates or information from Avista was “somewhat” or “very important” to their decision(s) to purchase additional measures and general population customers who did not indicate rebates or information from Avista was “very important” to their decision(s) to purchase additional measures. Cadmus did not consider appliances when calculating spillover savings due to saturation in the market of high-efficiency models (Figure 23). Table 23 summarizes the measures considered in PY2012 and PY2013 spillover estimates. Table 23. Technologies Considered in Spillover Analysis and Number of Completed Surveys Equipment Types Participant (n=648) General Population (n=1,051) Air Conditioner 4 15 Air Sealing 3 Clothes Dryer 2 Clothes Washer 2 Gas Furnace 2 2 Heat Pump 2 6 Insulated Doors 4 Insulation 3 3 Programmable Thermostat 1 Weather Stripping 4 Windows 4 2 Total 23 36 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 233 of 296 49 Survey respondents per measure 28.2 29.2 2013 Equipment Types Participant (n=357) General Population (n=1,109) Air Conditioner 4 Air Sealing 2 Clothes Dryer 1 Clothes Washer 1 Electric baseboard / Wall heater 1 Electric Furnace 1 Electric Water Heater 8 Gas Furnace 3 Gas Water Heater 5 Insulated Doors 3 Insulation 2 6 Lighting 1 Refrigerator 1 Weather Stripping 6 Windows 4 4 Wood/Pellet stove 1 Total 12 42 Survey respondents per measure 29.8 27.6 As indicated in Table 23, the number of spillover measures reported by respondents is consistent across the various surveys fielded, with one measure reportedly being installed for 27.6 to 29.8 survey respondents. As a final step, Cadmus estimated energy savings from these additional measures installed, and matched those savings to evaluated gross savings calculated for the sample of survey respondents. This led to spillover ratios at the program levels. The spillover results for the PY2012 and PY2013 are provided in the Avista 2012-2013 Washington Electric Impact Evaluation Report; and Avista 2012-2013 Idaho Electric Impact Evaluation Report. Residential Conclusions and Recommendations This section describes the evaluation’s conclusions and recommendations for the residential programs. Program Participation Conclusion: Avista’s implementation of new and continued support for existing third-party implemented programs such as Simple Steps, Smart Savings and Residential Behavior effectively captures energy savings in the residential market segments.  Recommendation: Continue exploring new measures, program designs, and delivery mechanisms that leverage the national expertise of experienced third-party implementation Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 234 of 296 50 firms. Possible programs may include additional partnership with ENERGY STAR in the form of the Home Performance with ENERGY STAR program. Conclusion: Avista’s continued investment in pilot programs provides a low-risk way test the effectiveness of new measure offerings, delivery channels, and implementation partners.  Recommendation: Continue testing new program designs and measure offerings through the use of pilots—even if secondary sources of funding or local partners are not available. Conclusion: While still early, evaluation findings indicate the Residential Behavior program is an effective way to capture savings in the residential market and Opower is a strong partner for program implementation.  Recommendation: If determined to be cost-effective, consider expanding the Residential Behavior program (for example, lowering the energy consumption threshold for participation) and implementing measures to track the methods these customers use to save energy. Given that Avista has already included all cost-effective customers in their target population for this program, future opportunities for expansion may be limited. Program Design Conclusion: Inconsistencies continue to exist in measure and program naming and organization across program planning, tracking and reporting activities which result in less transparency in program operations and limit effective program evaluation. • Recommendation: As part of the transition to the new data tracking system, consider aligning program and measure names with offerings articulated in annual business plans and other planning materials. Conclusion: Reduction in Avista natural gas rebates and elimination of appliance rebates give customers fewer ways to participate in Avista energy-efficiency rebate programs. • Recommendation: Consider ways to encourage repeat participation (such as marketing targeted at previous participants and online profiles that reduce application paperwork). Conclusion: Considering self-report customer freeridership scores and market baseline data from the RTF is an effective way to assess the appropriateness of measure offerings. • Recommendation: Continue use of customer freeridership and market assessments as a way to assess the appropriateness of measure offerings. Conclusion: Many ongoing changes in Avista’s program design and measure offerings are driven by the need to continue to meet cost-effectiveness requirements. Avista’s examination of measure and program-level cost-effectiveness will determine the character of its portfolio in future program years. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 235 of 296 51 • Recommendation: Develop a transparent process for assessing measure or program cost- effectiveness and communicating results internally. Consider ways to ensure high-quality cost- effectiveness analysis that aligns with industry best practices, such as obtaining an objective third-party review of current cost-effectiveness screening processes. Program Implementation Conclusion: Avista prioritization of customer satisfaction has been very successful and overall participant experience is very positive across all rebate programs. • Recommendation: Continue Avista’s commitment to customer satisfaction, but monitor: – Increased staffing costs; and – Impacts of the 90-day participation window on freeridership. Marketing and Outreach Conclusion: Avista implements a strong general awareness campaign around energy-efficiency, but some room exists in market segmentation and targeting specific customer groups. • Recommendation: Utilize survey results from this evaluation and other data collection activities to understand which audiences are more likely to participate in Avista programs. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 236 of 296 52 Nonresidential Process Report Introduction This nonresidential process evaluation focuses on three Avista programs offered to Idaho and Washington residential natural gas and electric customers during PY2012 and PY2013.14 In this evaluation, Cadmus sought to address the following researchable questions:  What barriers exist to increased customer participation, and how effectively do the programs address those barriers?  How satisfied were customers with the programs?  What changes to design and delivery would improve program performance? In assessing these topics, Cadmus relied on three main data-collection efforts:  Review of program tracking data, documents, and invoice materials;  Interviews with Avista and implementation staff; and  Telephone surveys with participating and nonparticipating customers. Program Overview Avista’s nonresidential programs encourage commercial and industrial customers to install energy- efficient equipment in their facilities. To accomplish this goal, Avista offers incentives directly to customers who install qualifying equipment. This report provides findings and recommendations based on a process evaluation of the three nonresidential energy-efficiency programs: Prescriptive; Site- Specific; and EnergySmart Grocer. Avista implements the Prescriptive and Site-Specific Programs. Avista account managers assist customers and determine project eligibility for the Site-Specific Programs, while program engineers are responsible for measuring and verifying project savings and costs. Trade allies also submit project information and rebate applications on behalf of customers. A third-party vendor, PECI, implements the EnergySmart Grocer Program. EnergySmart Grocer is a turnkey program available across the Northwestern United States. The following sections provide descriptions of each program. 14Similar to the residential portfolio, Avista’s non-residential programs operate on calendar years, with program years running from January through December. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 237 of 296 53 Prescriptive Program The Prescriptive program incents a variety of highly efficient electric and natural gas technologies, including:  PC network controls;  Clothes washers;  Food service equipment;  Lighting;  Motors;  Variable frequency drives (VFDs);  Windows and insulation;  Heating, ventilation, and air-conditioning (HVAC) equipment; and  Standby Generator Block Heaters. Site-Specific Program The Site-Specific Program offers incentives for energy-efficiency measures not included in the Prescriptive Programs. All commercial, industrial, and water pumping customers with electric or retail natural gas service from Avista are eligible for the Site-Specific Program. Site-specific measures consist of electric and gas-saving technologies including:  Appliances;  HVAC equipment;  Industrial processes;  Custom lighting,  Motors, and  Building shell improvements. For a measure to be eligible under the Site-Specific Program, it must have demonstrable kWh or therm savings. The Site-Specific Program is responsible for a large portion of Avista’s overall energy-efficiency portfolio savings. This program generally offers an incentive for any energy-saving measure that has a payback of more than one year and under eight years for lighting, and more than one year and under 13 years for other measures. The incentive typically covers up to 50% of the incremental cost of the efficiency investment. Key drivers to delivering on program objectives include: direct incentives to customers, marketing efforts, account executives relationships with large customers, and ongoing work with trade allies. The Avista website is also used to communicate program requirements and incentives, and to provide Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 238 of 296 54 application materials. The Every Little Bit and Efficiency Matters marketing and outreach campaign (described in the Residential Process Report above) also focuses on commercial customers and is designed to increase awareness of energy efficiency among commercial and industrial customers. EnergySmart Grocer Program The EnergySmart Grocer Program is a regional program that offers prescriptive rebates for a variety of energy-saving food-sales and refrigeration equipment for nonresidential electric and gas customers, with an emphasis on grocery stores. Eligible equipment incentives include:  Compressors;  Controls;  Motors;  Night covers for refrigerated cases;  Case lighting;  Strip curtains for refrigerated spaces;  Insulation for suction lines; and  Hot water tanks. This program helps customers with refrigeration loads to upgrade equipment, streamline operations, and save energy. Customers receive a complete energy analysis of their facility’s refrigeration and lighting, as well as a detailed report showing ways to reduce energy use. The customized report outlines potential energy savings, incentive amounts, retrofit costs, and simple paybacks, and is offered at no cost to the customer. EnergySmart Grocer Program offers 77 prescriptive measures. The average program incentive covers 45% of the customer incremental cost of the efficiency investment—although in some cases the program incentive covers up to 100% of the measure cost. Similar to the Site-Specific Program, key drivers to delivering on the objectives of the program include: direct incentives to customers, marketing efforts, account executives relationships with large customers, and ongoing work with trade allies. Avista website is also used to communicate program requirements and incentives, and to provide application materials Evaluation Methodology and Information Sources Cadmus’ approach to this non-residential portfolio-wide process evaluation relied on four main reviews and data-collection efforts. These activities and the program years they focused on are provided in Table 24. We applied activities to all three non-residential programs. Table 24. Data Collection Activities Applied to Each Program Program Materials Review  Staff Interviews  Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 239 of 296 55 Participating Customer surveys  Nonparticipating Customer Surveys  Realization Rate and Database Review  Materials Review This process evaluation analyzes primary and secondary program data. Cadmus conducted the following primary data-collection activities:  Program staff interviews;  Program participant15 surveys;  Nonparticipant customer16 surveys;  Database review; and  Interviews with lighting contractors. Secondary data included the following program and marketing materials:  Avista’s PY2012 and PY2013 DSM Business Plans;  An internal Avista program implementation manual;  Avista marketing collateral;  Everylittlebit.com website; and  Avistautilities.com website. Information from Avista’s reports for internal and external stakeholders, documents of public record, and information about best practices also informed this evaluation. Program Staff and Market Actor Interviews Interviews with program staff provided first-hand insights into program design and delivery processes, and helped evaluation staff interpret the information collected. We conducted interviews with Avista’s Washington and Idaho program staff in two rounds, one in January 2013 and another in December and January 2014. Cadmus also conducted interviews with participating and nonparticipating lighting contractors in the Avista service territory. These interviews were conducted in late 2013 as part of an ongoing Panel Study Cadmus is conducting for Avista. The interviews included several questions designed to provide feedback on Avista’s programs from the perspective of participant and nonparticipant market actors. Cadmus defined participating contractors as those with over 10% of their customers receiving Avista incentives. Cadmus reached out to contractors on a list of 275 contacts provided by Avista, and offered 15 Customers who received a program rebate in 2012 or 2013. 16 Eligible nonresidential customers that did not participate in the programs during 2012 or 2013 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 240 of 296 56 an incentive for participating in the study. Of the 275 contacts, 167 were ineligible for the study either because they were not commercial lighting contractors or because they operated outside of Avista’s service territory. Cadmus completed interviews with 20 of the remaining 108 contacts. Table 25 provides a summary of interview data collection. Table 25. PY2012 - 2013 Program Staff and Market Actor Interviews Avista Program Implementation Staff 3* 5 Avista Policy, Planning and Analysis Staff 1* 2 Avista Marketing Staff 1* Lighting Contractors 9 (participant) 11 (nonparticipant) * Multiple non-Cadmus staff participated in interview. Participant Surveys Telephone surveys constituted a large part of PY2013 evaluation data collection activities. We conducted all surveys with the assistance of several subcontracted market research firms, selected for their experience with the commercial market segment. To minimize the burden on customers, ensure a more satisfactory experience, and ensure high response rates, Cadmus designed the survey to take approximately 15 minutes to complete. The primary research objectives for participant surveys were to:  Determine participant satisfaction with key program components and delivery;  Understand participant decision-making influences;  Identify: o Information sources and channels’ effectiveness for outreach; o Participants’ perceptions of market barriers; o Participant freeridership and spillover; o Potential areas for program improvements and future offerings; and  Compiling profile information about Avista’s C&I target markets. The process evaluation team used a single survey instrument for participants in all three programs, maximizing survey efficiency by combining process- and impact-related questions into a single survey. Cadmus designed participant survey samples to represent the programs proportionately according to reported kWh savings. We adjusted survey targets to account for the number of survey respondents available for a given program. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 241 of 296 57 Table 26. Participant Survey Summary Details Washington Prescriptive 79 Site Specific 41 Energy Smart Grocer 14 Idaho Prescriptive 33 Site Specific 23 Energy Smart Grocer 11 Total 201 Surveys were not conducted with PY2012 program participants because after conducting a large number of surveys with nonresidential customers in 2010 and 2011, Cadmus and Avista elected not to conduct surveys in 2012 to avoid survey fatigue in this population. Nonparticipant Surveys The primary research objectives for nonparticipant surveys were to:  Determine program awareness levels and information sources;  Understand decision-making influences regarding energy-using equipment;  Identify: o Information sources and channels’ effectiveness for outreach; o Participation barriers or reasons customers aware of programs did not participate; o Nonparticipant spillover; o Potential areas for program improvements and future offerings; and  Compiling profile information about Avista’s C&I target markets. 2011-2012 Database and Realization Rate Review As part of the PY2012 process evaluation, Cadmus reviewed Avista’s PY2012 nonresidential project database and project-level realization rates identified in Cadmus’ PY2011 and PY2012 impact evaluation. The materials reviewed and our associated research questions are listed in Table 27. Table 27. Database and Realization Rate Review Activities Database Review PY2012 SalesLogix Database Extract Are data being tracked accurately and consistently? Are contracts issued in accordance with Avista policy? Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 242 of 296 58 Do incentives comply with tariff rules for Washington and Idaho? Realization Rate Review PY2011 - PY2012 Impact Evaluation Sample Why do some projects have a very low or very high realization rate? Are there opportunities for Avista to improve the process of calculating reported savings to improve the realization rates? Database Review Avista’s tariff Schedules 90 and 190 govern how Avista can spend funds from the Energy Efficiency Rider Adjustment paid by Washington and Idaho ratepayers.17 To assess compliance with these Tariff Schedules, we examined two main indicators: 1. Project incentive amount: electric and natural gas project incentives should not exceed 50% of the incremental cost of the project (p. 3 of Schedule 90; p. 2 of Schedule 190). 2. Project simple payback: a. For lighting measures, the simple payback period must be a minimum of one year and should not exceed eight years. (p. 2 of Schedule 90); and b. For non-lighting electric and natural gas measures, the simple payback period must be a minimum of one year and should not exceed 13 years. (p. 2 of Schedule 90; p. 2 of Schedule 190). The tariff rules make exceptions for the following programs or projects (p. 3 of Schedule 90; p. 2 of Schedule 190):  DSM programs delivered by community action agencies contracted by Avista to serve limited income or vulnerable customer segments, including agency administrative fees and health and human safety measures;  Low-cost electric/natural gas efficiency measures with demonstrable energy savings (e.g., compact fluorescent lamps); and  Programs or services supporting or enhancing local, regional, or national electric/natural gas efficiency market transformation efforts. (In 2012, Avista considered new construction fuel conversions in multifamily building projects and T12 to T8 commercial lighting conversion projects as market transformation efforts.) 17 Schedule 90: Electric Energy Efficiency Programs, Washington. Available at: http://www.avistautilities.com/services/energypricing/wa/elect/Documents/WA_090.pdf; Schedule 190: Natural Gas Energy Efficiency Programs, Washington. Available at: http://www.avistautilities.com/services/energypricing/wa/gas/Documents/WA_190.pdf; and Schedule 90: Electric Energy Efficiency Programs, Idaho. Available at: http://www.avistautilities.com/services/energypricing/id/elect/Documents/ID_090.pdf Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 243 of 296 59 Status of Evaluation Recommendations Avista retained Cadmus to perform annual process and impact evaluations of Avista’s non-residential program portfolio beginning in PY2010. These evaluation activities, findings, conclusions, and recommendations are articulated in the following reports: Avista 2010 Multi-Sector Process Evaluation Report; and Avista 2011 Multi-Sector Process Evaluation Report.18 In this evaluation effort, Cadmus reviewed the recommendations offered in these documents and assessed to what degree Avista had adopted these recommendations (by the end of PY2013). As indicated in Table 28, Avista has made significant progress toward addressing these recommendations. Table 28. Status of PY2010 and PY2011 Nonresidential Process Recommendations Complete 6 8 In Progress 4 11 Limited Activity 3 1 A complete summary of recommendations and activity for addressing these recommendations is provided in Appendix B: Status of PY2010 and PY2011 Nonresidential Evaluation Recommendations. Program Participation Savings and Incentives Table 29 provides the number of incentive-based measures and reported savings. The PY2012 and PY2013 Avista Impact Evaluation Reports explore the reported savings in detail. Table 29. PY2012 - PY2013 Program Populations and Reported Savings1 Prescriptive 3,363 1,813 56,884 212,525 Site Specific 332 328 39,050 504,571 Energy Smart Grocer 338 329 10,858 0 Total 4,317 2,470 106,792 717,096 18 Avista 2010 Multi-Sector Process Evaluation Report. Cadmus. 2011. Avista 2011 Multi-Sector Process Evaluation Report. Cadmus. 2012. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 244 of 296 60 Program Design, Management, and Implementation This section discusses the Cadmus’ observations regarding design and management of Avista’s nonresidential programs. These observations focused on program definition and organization, logic, and implementation approach. Overview Overall, we found Avista’s the non-residential program designs work well and are generally well- documented, primarily in the PY2012 and PY2013 DSM Business Plans. Further, we found that Avista has taken actions to improve internal communications and review processes. Program Logic Camus developed the logic model provided to articulate the logic behind the nonresidential program. The nonresidential program’s logic has not changed substantially since the previous process evaluation. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 245 of 296 61 Figure 25. Avista Nonresidential Program Logic Model Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 246 of 296 62 Internal Communication Avista’s management and implementation of DSM programs has had some persistent organizational challenges. While not limited to any specific part of Avista’s DSM staff, many of the issues noted here and in previous studies have primarily affected the nonresidential program internal review processes. Several external documents and processes have addressed these problems, including:  2008 Ecotope Impact Evaluation – cited potential for improved quality control  2009-2010 Moss Adams Process Evaluation Report – expressed need for central management role and QA/QC checks in the nonresidential program  2010-2011 Cadmus Process Evaluation Report – recommended QA/QC checks at certain threshold  August 2013 Cadmus Memo (see Appendix C) – review of 2012 program data noted some lack of documentation, possible issue with application of tariff rules regarding payback periods and incentive payment caps, and large variations between project-level realization rates  December 2013–January 2014 Cadmus interviews with Avista – noted internal disagreement regarding whether the Top Sheet process was working  March 2014 Idaho Public Utilities Commission staff comments on Avista Corporation’s Application for a Finding that it Prudently Incurred its 2010-2012 Electric and Natural Gas Energy Efficiency Expenditures – noted program implementation issues including a “lack of formal follow-through on program management issues,” “insufficient controls around engineering assumptions and the basis for site-specific incentive payments, [and] incorrect interpretation of Schedule 90 regarding implementation of prescriptive projects”  April 2014 Idaho Public Utilities Commission Order Number 33009 on Avista Corporation’s Application for a Finding that it Prudently Incurred its 2010-2012 Electric and Natural Gas Energy Efficiency Expenditures – approved expenditures as prudent with the exception of incentives for two projects for which recovery was deferred due to incomplete documentation, reiterated need for a central decision maker These documents focused on a variety of issues, but all documents agreed that there were concerns with Avista’s internal QA/QC process, especially for large nonresidential projects. These efforts agreed that the definition of roles and responsibilities for Avista’s DSM staff were not sufficiently clear. Further, several documents noted that Avista’s DSM staff was split into two completely separate teams: the implementation team and the PPA team reported to separate directors. This separation may have fueled internal communication problems. Avista has taken significant steps internally to address these issues:  2009 Avista Internal Audit Department review of DSM processes  2013 Avista retained Milepost Consulting for review of DSM team’s roles and responsibilities  2013 Avista’s implementation of Top Sheets – instituted peer review QA/QC system; associated internal follow-up was completed to verify Top Sheet standard processes Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 247 of 296 63  July 2013 Avista Internal Audit Department memo – noted that previously identified issues need further attention  April 2014 Internal Audit Department memo – found that 70 out of 75 Top Sheets were present and on-site verification is happening for 100% of site-specific projects completed to date in 2014, but noted there is no policy on how many prescriptive projects should get on-site verification As of April 2014, Avista has begun a restructuring process to improve internal communication and delivery of DSM programs. Both the implementation team and the PPA team now report to the same Senior Director. Effectiveness of Implementers As noted in the Residential Process Report, using third-party implementers presents advantages and disadvantages. Generally, utilities maintain direct implementation of programs requiring strong relationships with unique customers (e.g., large commercial and industrial customers). Programs benefitting from a uniform approach involve national accounts, or require certain market expertise available from a third-party firm. Research conducted for this—and previous—Avista evaluation efforts leads us to conclude that Avista has succeeded in identifying which program (EnergySmart Grocer) is most suitable for third-party partnering. The PY2011 evaluation report provides the results of detail interviews conducted with implementation staff at PECI staff. As few changes have been made to this program since the interviews took place in spring 2012, and the program has been the subject of other recent regional Cadmus evaluations,19 we did not conduct additional evaluation in this area. Data Tracking, Verification, and Quality Assurance Cadmus reviewed the PY2012 program tracking database for data accuracy and completeness, and issued a memo in August 2013 describing in detail the methods, findings, and conclusions (Appendix C: 2012 Nonresidential Process Evaluation Memorandum). In summary, we found some documentation was lacking and that there were issues with the application of tariff rules regarding project costs and energy savings specific to prescriptive projects. We also examined the accuracy of Avista’s claimed savings, measured by realization rates, and found that accuracy improved significantly from 2011 to 2012. Three of the four main reasons for savings adjustments in 2012 were largely outside Avista’s control. However, based on the review of 2012 data, 19 Cadmus recently completed an impact assessment and a market potential assessment of the EnergySmart Grocer program in 2013. The results of this work are documented in reports available here: http://www.bpa.gov/energy/n/reports/evaluation/commercial/pdf/Cadmus_ESG_Impact_Evaluation_Report_Fina l.pdf http://www.bpa.gov/energy/n/reports/evaluation/commercial/pdf/BPA_Grocery_Opp_Assessment_05JUN13.pdf Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 248 of 296 64 we concluded that Avista could still improve the reliability of claimed savings estimates by avoiding calculation errors in reported savings. Cadmus reviewed achieved realization rates in each year, as summarized in Figure 26. This review showed that the accuracy of claimed savings declined slightly in 2013, with 52% of electric project realization rates falling within the 90% to 110% range. This range reflects a high degree of accuracy, with realization rate adjustments of 10% or less. It is expected that some portion of projects will fall outside of this range due to factors beyond Avista’s control. Though the proportion of projects with realization rates that fall below 90% is greater than that above 110%, the magnitude of those projects has been steadily decreasing over the years, falling from 42% in 2011 to 29% in 2013. Figure 26. Summary of Avista Nonresidential Project Electric Realization Rates In July 2013, Avista instituted a new process for site-specific project reviews. A major feature of the new review process was the addition of Top Sheets to track and verify applications’ completeness and correctness. Cadmus did not perform a review of the information contained within Top Sheets as part of this process evaluation, but rather gathered information about the Top Sheet process through interviews with staff. Participant Characteristics, Experience and Satisfaction To assess customer satisfaction with Avista’s nonresidential programs, Cadmus included questions around these topics in participant customer surveys. Overall, as in past evaluations, Cadmus observed Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 249 of 296 65 very high customer satisfaction across the programs and program elements. The sections below provide additional detail. Participant Characteristics Cadmus surveyed a total of 210 participating and 140 nonparticipating nonresidential customers. These respondents represented a variety of business sectors, as shown in Table 30. Table 30. Participant and Nonparticipant Survey Respondents’ Industries, By State Retail / personal services 22% 27% 16% 20% Office / professional services 6% 17% 7% 20% Manufacturing 7% 13% 11% 3% Auto repair or service station 14% 6% 11% 17% Warehouse / distribution center 10% 6% 9% 6% Religious 6% 4% 4% 1% Government building 1% 9% 1% 3% Medical 6% 3% 6% 4% Education (K-12) 7% 0% 1% 0% Restaurant 4% 1% 9% 4% Hospitality 0% 3% 1% 3% Dormitory / multifamily housing 1% 0% 4% 3% Education (college / university) - - 3% 1% Agricultural - - 0% 3% Other 14% 11% 16% 10% Program participant respondents were more likely than nonparticipant respondents to own their facilities. Indicated in Figure 27, 78% of participants owned their facilities, compared with 67% of nonparticipants. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 250 of 296 66 Figure 27. Facility Ownership Status, Participants vs. Nonparticipants Most survey respondents, both participants and nonparticipants, used gas heating. Figure 28 shows fuel use for space heating by customer type. Figure 28. Fuel Use for Space Heating, Participants vs. Nonparticipants Participant Satisfaction Overall, participants reported high satisfaction with the programs: 84% of all respondents said they were “very satisfied” in the program overall. Figure 29 shows respondents’ satisfaction ratings by program. In contrast to the 2011 survey, when EnergySmart Grocer participants were less satisfied than 78% 67% 22% 33% 0% 20% 40% 60% 80% 100% Participants (n=206)Non-Participants (n=135) Lease / Other Own 57% 21%18% 4% 47% 22%23% 8% 0% 10% 20% 30% 40% 50% 60% Natural Gas Electricity Both (Gas & Electric) Other Participant (n=206)Non-Participant (n=132) Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 251 of 296 67 other participants, EnergySmart Grocer participants reported the highest satisfaction levels in the PY2013 survey. Figure 29. Overall Participant Satisfaction Satisfaction levels were generally similar across programs, as Figure 30 shows. However, the Washington Site-Specific Program received slightly lower ratings than the other programs. Figure 30. Participant Satisfaction, by Program 1% 12% 87% 2% 23% 75% 12% 88% 0% 20% 40% 60% 80% 100% Not too satisfied Somewhat satisfied Very satisfied Prescriptive Site-Specific EnergySmart Grocer 78% 2011 75% 2011 65% 2011 69% 100%89%86%75%82% 29% 9%14%25%18% 0% 20% 40% 60% 80% 100% Site-Specific Prescriptive EnergySmart Grocer Site-Specific Prescriptive EnergySmart Grocer Washington Idaho Very Satisfied Somewhat Satisfied Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 252 of 296 68 When asked how Avista could improve the program participation experience, Washington Site-Specific participants suggested increased responsiveness and improved program information. Responses included:  “It would be nice if they could have recommend known heating and lighting and steered us to the best installers.”  “Contact me the first time I call.”  “Find a way to do this sooner for better information.”  “Just shorten the timeframe on the initial inquiry.”  “Improve the responsiveness of the technical team.”  “Send me information that I need to finish the rebate process.” Participants also reported generally high satisfaction with individual program elements. As Figure 31 shows, at least 63% of survey respondents indicated they were “very satisfied” with each program element. Avista staff received the highest satisfaction ratings, with 92% of respondents “very satisfied.” Program materials were the element that received the lowest satisfaction rating, with 63% of respondents “very satisfied.” Participant satisfaction with the facility audit improved markedly since the 2011 survey, rising from approximate 50% “very satisfied” in 2011 to 80% “very satisfied” in 2012-2013. Figure 31. Percent of All Participants “Very Satisfied” with Program Elements Program Barriers Participants reported facing several barriers to installing energy-efficient equipment. The most common barriers cited are shown in Figure 32. The high up-front cost of energy-efficient equipment was the most commonly cited obstacle; 50% of participants said it was a challenge. Next, 6% of participants reported operational concerns, such as the inconvenience of having to work around customers and employees 92% 84% 82% 80% 76% 71% 69% 63% 84% 0%10%20%30%40%50%60%70%80%90%100% Avista Staff Performance Of Measure Quality of Contractor Service Facility Assessment Time-to-Receive Check Application Process Rebate Amount Program Materials Program Overall Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 253 of 296 69 during business hours, and a new oven that made the surrounding space too hot. Long return on investment, lack of technical knowledge, and lack of staff time were obstacles according to 4% of respondents. An additional 4% said there were no obstacles at all. A small group of participants (five participants, or 2%) had difficulty finding competent and trustworthy contractors and vendors. One said, “The vendors twist information for their own benefit. If they have different lights, they say [energy- efficient lights are] not going to fit in there, so they install what they want to install.” Figure 32. Obstacles to Installing Energy-Efficient Equipment Program Benefits Two-thirds (67%) of participants said the energy-efficient measures they took resulted in benefits beyond energy savings. As Figure 33 shows, the most common non-energy benefit participants cited was better equipment performance, such as improved comfort, better lighting quality, and less noise. Additionally, 20% of respondents said the project increased productivity (including increased sales, for retail facilities), while 12% cited lower maintenance costs. Other benefits that respondents mentioned were less waste, environmental benefits, increased technical knowledge, and water savings. 4% 2% 4% 6% 10% 50% 4% 14% 62% 0%10%20%30%40%50%60%70% None Contractor Concerns Long Payback Period Operational Concerns Lack of Internal Resources High First / Upfront Cost 2011 2013 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 254 of 296 70 Figure 33. Non-Energy Benefits of Participation Market Feedback Cadmus interviewed 20 commercial lighting contractors to obtain feedback on how Avista’s programs affected the overall market for energy-efficient lighting. Significant findings from these interviews are provided below. Contractor Awareness The most common way the lighting contractors said they had heard about Avista’s energy-efficiency programs was through an Avista mailing. Figure 34 shows the sources of awareness the trade allies reported. Figure 34. How Lighting Contractors Heard About the Programs 1 1 3 4 4 6 0 1 2 3 4 5 6 7 Avista E-Mail Supplier Avista Trade Ally Event Avista Website Past Experience with Programs Avista Mailing Number of Contractors Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 255 of 296 71 Program Impact on Sales Cadmus asked the lighting contractors what impact Avista’s rebate programs had on their business. As Figure 35 shows, 16 of the 20 contractors said their sales had increased, while four said they had seen no effect. (None of the contractors said their sales had decreased due to the programs.) Two contractors said they had noticed large increases in previous years, but that sales had dropped in 2013. One said, “[the programs] increased sales when the T12-to-T8 rebate existed, but now it has no effect on sales.” Figure 35. Avista Programs’ Impact on Lighting Contractors’ Sales Nearly all contractors said energy-efficient sales would decrease if Avista’s rebates were eliminated, as shown in Figure 36. 10 1 6 3 0 2 4 6 8 10 12 Increased Sales No Effect on Sales Nu m b e r o f C o n t r a t o r s Non-Participant Participant Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 256 of 296 72 Figure 36. Hypothetical Effect of Avista Rebate Elimination on Contractors’ Sales Market Transformation Most contractors reported Avista’s programs do not affect their stocking practices, as shown in Figure 37. Figure 37. Avista Programs’ Effect on Contractor Stocking Practices 4 5 22 7 0 1 2 3 4 5 6 7 8 Large Decrease Small Decrease No Change Nu m b e r o f C o n t r a c t o r s Non-Participant Participant 10 1 8 1 0 2 4 6 8 10 12 No Effect Slight Increase Nu m b e r o f C o n t r a t o r s Non-Participant Participant Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 257 of 296 73 Marketing and Outreach Program Marketing Approach Marketing Objectives and Strategies Avista’s marketing approach for 2013 was to increase awareness and participation in Avista’s energy efficiency programs for commercial and industrial customers using customer endorsements, and showcasing additional value through non-energy benefits. Planning and Processes Avista staff plan, design, and execute nonresidential program marketing initiatives. As indicated in the PY2012 and PY2013 DSM plans, an internal collaborative process exists to develop general energy- efficiency marketing and promotions. This process incorporates feedback from the Energy Solutions, Services Development and Marketing, and Programs, Planning, and Analysis teams. The EnergySmart Grocer Program includes supplemental marketing as part of its program design and implementation plan. Avista’s marketing staff use the Avista Design System Guidelines to ensure that energy-efficiency marketing and outreach materials deliver a consistent look, feel, and message. This document includes guidelines for usages of items such as logos, color palettes, and fonts. It also includes an overview of applications, with examples of properly branded materials and collateral. All PY2012 and PY2013 general energy-efficiency marketing materials appear to be aligned with the guidelines. The Efficiency Matters campaign and Online Energy Advisor tool present slightly varied creative assets, although generally appear to follow the brand guidelines (i.e., fonts, logos, etc.). Outreach Channels Avista conducts residential energy-efficiency marketing through a variety of channels. In addition to the general energy-efficiency marketing tactics outlined below, Avista also conducts broad-based awareness efforts through its Efficiency Matters campaign, as described in the following section. Besides the Efficiency Matters campaign (which is implemented in partnership with KREM 2, a CBS affiliates), there are no mass media or cross-cutting promotional efforts, to avoid potential customer confusion across state lines. Notable outreach tactics used in PY2012 and PY2013 include:  Paid media: print advertisements in local and regional magazines and newspapers;  Earned media: local public relations as available;  Direct mail and bill inserts: general and (targeted) program-specific;  Newsletters and e-mail blasts: general outreach;  Website (avistautilities.com): case studies added in 2013; and  Vendor outreach meetings: general overview about programs, application process, project qualifications, and customer eligibility. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 258 of 296 74 Print Advertising The programs used print advertising to highlight customer success stories with call to learn more information at two specialized webpages:  avistautilities.com/bizrebates  avistautilities.com/casestudies Figure 38: Example Case Study Print Advertisement The ads appeared in select local and regional print publications, as shown in Table 31, targeted to reach key business decision makers. The ads ran from May through December 2013, and delivered over 1,041,000 gross impressions. Table 31. Print Advertisement Publications Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 259 of 296 75 - Spokane Journal of Business - North Idaho Business Journal - Coeur d’ Alene Press - Spokesman Review - The Wall Street Journal (zoned) - HVAC/R Insider - The News (HVAC) - Today’s Facility Manager - Alaska Airlines - Horizon Airlines Materials and Messaging Cadmus reviewed Efficiency Matters campaign outreach materials and Avista’s energy efficiency web pages, and conducted a high-level review of the Online Energy Advisor materials as a point of reference. The evaluation team found that there are varied creative assets and look and feel across channels and platforms. While the general energy efficiency promotional materials present a look and feel consistent with the brand guidelines, the Efficiency Matters campaign and Online Energy Advisor platforms leverage additional assets. For example, the Efficiency Matters landing page (www.everylittlebit.com) also includes assets from the Online Energy Advisor personas (with the “shield” creative) and creative developed by a 3rd party implementer. Marketing Execution and Measurement Avista tracks metrics for its individual campaigns and ties results back to awareness and website traffic. In PY2013, Avista staff reported tracking Efficiency Matters campaign metrics (participants and traffic), estimated impressions through paid media, and response to direct mail. Customer Awareness Most of the customers surveyed had not heard of Avista’s nonresidential programs; 38% of nonparticipants recalled having heard about the programs. As Figure 39 shows, nonparticipants’ awareness has remained relatively stable since 2010. Figure 39: Nonparticipant Program Awareness 34% 41% 38% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 2010 2011 2013 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 260 of 296 76 As shown in Figure 40, nonparticipants who were not previously aware of Avista’s nonresidential programs overwhelmingly say they want to hear about them through the mail – bill inserts or direct mail. Nearly a quarter reported wanting to hear about the programs through e-mail. Figure 40. How Nonparticipants Want to Hear about the Programs Sources of Participant Awareness In both Washington and Idaho, most participating customers reported hearing about the program from a contractor or vendor, as shown in Figure 41. Contact from Avista and word-of-mouth were also commonly reported sources of awareness in both states. Among Avista’s marketing efforts, the program website was the most commonly cited source of awareness, with 7%. Three percent each said they learned about the program from printed materials (such as flyers or brochures) and the electronic newsletter. No participants reported they heard about the program through magazine or newspaper advertisements. 1% 1% 4% 23% 35% 35% 0%5%10%15%20%25%30%35%40% Other Social Media Avista Account Representative E-Mail Updated from Avista Direct Mail Notices in Utility Bill Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 261 of 296 77 Figure 41. How Respondents Heard About the Program (Participants - Idaho)20 Nonresidential Program Freeridership and Spillover Freeridership Freeridership, the percentage of savings that are likely to have occurred in the program’s absence, traditionally refers to participants who would have undertaken an action promoted by a program had the incentive or other program activities not been available. Full freeriders would have undertaken exactly the same action at the same time (i.e., the program had no effect on the degree or timing of their actions). Partial freeriders would have taken some action, but would not have undertaken the action to the level promoted by the program, or would not have taken the action at the time they did. Table 32 shows overall nonresidential freeridership results for 2013, including gas and electric projects and participants in both Washington and Idaho. These results are based on 2013 participant survey response data and weighted by project savings. Table 32. Nonresidential Freeridership Estimates PY2013 Prescriptive 119 9.1% Energy Smart Grocer 26 14.3% Site-Specific 65 30.4% Total 210 19.5% 20 Percentages may add up to more than 100% because respondents were permitted to give multiple answers. 1% 1% 1% 3% 3% 4% 7% 7% 15% 23% 37% 0%5%10%15%20%25%30%35%40% Other Program-sponsored Event Trade/Professional Organization Print Materials Electronic Newsletter Rebate for Other Measure Program Website Customer Contacted Avista Contacted by Avista Word of Mouth Contractor/Vendor Washington Idaho Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 262 of 296 78 The PY2013 prescriptive program showed a low level of freeridership, while the site-specific program showed slightly over 30% freeridership. As shown in Figure 42, these results differ from 2011 freeridership results, but are fairly similar to the results found in 2010. Figure 42. 2010, 2011, and 2013 Nonresidential Program Freeridership Because nonresidential projects can be very large, and freeridership results are weighted by savings, the highest saving projects in the sample can have a strong influence on year-to-year results. To further examine the difference between the 2013 and 2011 analysis, Cadmus identified the top three savers in each program category and their freeridership scores.  Prescriptive showed a decrease in freeridership: A key driver of the decrease is that in the 2011 analysis, the three respondents with the highest gross energy savings accounted for 34% of the survey sample’s total gross savings. The top energy saver was estimated as a 75% freerider, and represented 19% of the total survey sample savings, while the second and third highest energy savers were estimated as 0% freeriders. In 2013, the three participants who achieved the greatest savings accounted for 38% of the total gross savings for the survey sample and all three respondents were estimated to have 0% freeridership. As such, the high level of savings achieved by these three 2013 participants, relative to the rest of the 2013 survey sample, resulted in these participants’ freeridership scores greatly reducing the overall freeridership estimate reported in 2013 compared to what was observed through the 2011 evaluation efforts.  Energy Smart Grocer showed an increase in freeridership: A key driver of increase is that in the 2012 analysis, the three respondents with the highest gross energy savings accounted for 72% of the survey sample’s total gross savings and all three respondents were estimated to have 0% freeridership. As such, the high level of savings achieved by these three participants, relative to Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 263 of 296 79 the rest of the survey sample, resulted in these participants’ freeridership scores greatly reducing the overall freeridership estimate reported in 2011. In 2013, the three participants who achieved the greatest savings only accounted for 64% of the total gross savings for the survey sample and the top energy saver was estimated as a 0% freerider. The second largest energy saver, representing 16% of 2013 survey sample savings, was estimated as a 75% freerider and the third highest energy saver as a 0% freerider. As such, the high level of savings achieved by these three 2013 participants, relative to the rest of the survey sample, resulted in these participants’ freeridership scores greatly increasing the overall freeridership estimate reported in 2013 compared to what was observed through the 2011 evaluation efforts.  Site-specific showed an increase in freeridership: A key driver of the increase is that in the 2011 analysis, the three respondents with the highest gross energy savings accounted for 35% of the survey sample’s total gross savings, and first and second highest energy savers were estimated as 0% freeriders, and represented 28% of the total survey sample savings, while the third highest energy saver (7% of total survey sample savings) was estimated as a 100% freerider. In 2013, the three participants who achieved the greatest savings accounted for 41% of the total gross savings for the survey sample. The top energy saver, representing 21% of the survey sample savings, was estimated as a 0% freerider. The second highest energy saver was estimated as a 50% freerider and the third largest saver as a 100% freerider. As such, the high level of savings achieved by these three participants, relative to the rest of the survey sample, resulted in these participants’ freeridership scores increasing the overall freeridership estimate reported in 2013 compared to what was observed through the 2011 evaluation efforts. These year to year variations accurately reflect the activity of participants within each program year, but they can reduce clarity when observing year-to-year trends. For example, since the site-specific program did not change substantially between 2011 and 2013, the large change in freeridership may reflect differences between individual customers, rather than changes in the market or in the program’s implementation. Therefore, Cadmus also calculated combined freeridership values that reflect the aggregated survey data from 2011 and 2013. These values may portray a more reasonable estimate of the programs’ overall level of freeridership that could be expected in future years if programs do not change substantially. Table 33. Nonresidential Freeridership Estimates: Combined PY2011 and PY2013 Prescriptive 189 16.2% Energy Smart Grocer 43 12.7% Site-Specific 128 24.3% Total 360 19.5% Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 264 of 296 80 Spillover Participant spillover refers to additional savings generated by program participants due to their program participation, but not captured by program records. Spillover occurs when participants choose to purchase energy-efficient measures or adopt energy-efficient practices due to a program, but choose not to participate (or are otherwise unable to participate) in an incentive program. These customers’ savings are not automatically credited to the utility program. Energy-efficiency programs’ spillover effects can be considered an additional impact that gets credited to program results. In contrast, freeriders’ impacts reduce the net savings attributable to a program. In this evaluation, Cadmus measured spillover achieved through the installation of measures without utility rebates through surveys with participant end-users. We have found these savings to be the easiest to quantify through self-report surveys. As shown in Table 34, Cadmus found a small amount of participant spillover for PY2013, equivalent to 0.05% of total program gross savings. The reported measures included in the spillover savings included LEDs (350 total units) and energy-efficient light fixtures (10 total units). Table 34. Nonresidential Spillover Estimates for PY2013 Prescriptive 204,728 7,812,790,682 0.00% Energy Smart Grocer 0 2,885,093,921 0.00% Site-Specific 14,148,104 19,838,919,241 0.07% Total 14,352,833 30,536,803,843 0.05% Nonresidential Conclusions and Recommendations This section describes the evaluation’s conclusions and recommendations for the nonresidential programs. Program Management and Implementation Conclusion: Several parties over several years, internal and external to Avista, have observed the need for greater data quality assurance, in both documentation and input tracking. Quantitative inputs to the savings and rebate calculations have repercussions for tariff compliance,21 incentive payments, and savings realization rates.  Recommendation: Avista should continue efforts to improve program processes. Cadmus understands that a reorganization of the DSM group has occurred concurrent to the delivery of this report. This change may be an opportunity for fresh perspectives, clarified responsibilities, 21 As noted in Idaho Public Utilities Commission Order Number 33009 on Avista Corporation’s Application for a Finding that it Prudently Incurred its 2010-2012 Electric and Natural Gas Energy Efficiency Expenditures. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 265 of 296 81 and improved coordination within and between teams. We believe unifying the organizational structure under central leadership is a step in the right direction and may help alleviate some previously documented issues with internal communications. In addition to the reorganization, Cadmus recommends that Avista develop standardized processes within the DSM group, including clear delineation of roles and precise description and assignment of all processes and responsibilities for both residential and nonresidential programs. All affected parties should be included in formalizing and standardizing the DSM group’s processes, roles, and responsibilities. Further, all parties must formally agree to clearly delineated responsibilities under the new organizational structure. While these activities need to be prescriptive and precise, we caution that the resulting structure should still allow some flexibility: increased clarity, transparency, and accountability should serve to enhance program delivery and customer satisfaction. Customer Feedback Conclusion: Customers were highly satisfied with the program overall and with individual components. Customer satisfaction has increased since 2011, which had in turn increased from 2010.  Recommendation: Continue to prioritize and monitor program satisfaction. Conclusion: Customers appeared to be slightly less satisfied with the Washington Site-Specific program than with other programs. The largest source of lower satisfaction was the participants’ reactions to program materials. Many customers said they received no program materials, and many participants learned about the program from their trade allies.  Recommendation: Consider taking action to strengthen the use of program materials. Consider providing trade allies with printed program information flyers or brochures to give to customers. Maintaining up-to-date information for trade allies is critical when they are the key party delivering the program’s message and participation details. Market Feedback Conclusion: According to commercial lighting contractor feedback, the nonresidential programs are successful in driving incremental energy-efficient equipment sales, and the market has not yet transformed to make energy efficiency standard practice.  Recommendation: Continue to monitor market transformation indicators to measure programs’ market impact over time. Marketing and Outreach Conclusion: The characteristics of Cadmus’ survey respondents indicate that the office / professional services and local government sectors may be underserved by the programs relative to their incidence in the nonparticipant population. Further research is necessary to determine whether this is true. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 266 of 296 82  Recommendation: Identify underserved industries, and seek opportunities to target outreach to specific underserved industries: – Investigate overall customer industry distribution – Compare to participant industry distribution – Develop targeted outreach strategies for any underserved sectors Quality Assurance and Verification Conclusion: Avista monitored its site-specific project review process and instituted refinements during the evaluation period in response to feedback from users. While this has led to improvements, including notably improved reliability of reported savings in 2012, quality assurance problems may persist.  Recommendation: Continue to monitor the effectiveness of the site-specific project review process and refine as needed. Cadmus recommends implementing the following to ensure continued improvement: – All large prescriptive or site-specific projects reporting savings over a threshold of 300,000 kWh or 10,000 therms should undergo a complete QA/QC review prior to incentive payment in addition to the standard Top Sheet review process. Typically, a QA/QC process reviews engineering calculations, verifies inputs, checks payback period and incentive payments for reasonableness, and ensures compliance with program requirements and tariff rules. In order to align with the above recommendation regarding program management and implementation, Cadmus recommends that Avista determine and document the specific requirements and steps in the QA/QC process through a collaborative process that will ensure accountability and balance needs for efficiency and customer satisfaction. – Conduct an external third-party review of Top Sheets, including reviewing a random sample of completed Top Sheets for completeness and accuracy. These were not reviewed as part of the current process evaluation, but should be included in the next process evaluation. Review should not only verify the presence of the Top Sheets, but also the quality and accuracy of the information provided. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 267 of 296 83 Appendix A: Status of PY2010 and PY2011 Residential Evaluation Recommendations Table 35. Implementation of PY2010 Residential Evaluation Recommendations Program Participation Research market saturation and participation to track achievement of potential. Complete Using the Avista Electric Conservation Potential Assessment Study completed in August 2011, along with available data sources such as ENERGY STAR and additional primary research, Avista should track the residential portfolio’s progress toward capturing projected realistic achievable potential. This effort will inform program planning and design decisions to allow for the long-term success of the residential portfolio. Discontinue rebate for ENERGY STAR dishwashers. Complete ENERGY STAR data shows that 78 percent of dishwashers sold nationally are ENERGY STAR models. Therefore, this measure is likely to suffer from high freeridership, and the Avista rebate is unlikely to affect market transformation. Emphasize ease of participation in marketing. In Progress In order to address the nonparticipant perception that program participation may be difficult, Avista should emphasize the ease of participating in residential marketing Program Design Simplify and document program organization structure. In Progress Cadmus recommends grouping programs in logical clusters, in order to reduce complexity of documentation and tracking. While streamlining program organization, Avista should also document institutional knowledge of programs to avoid loss of continuity. Assess viability of redesigning some programs to include contractor rebates. In Progress Avista should consider the suggestion from HVAC trade allies to provide rebates direct to contractors. Other utilities have seen success with this model, which reduces the administrative burden on customers, allows for batch processing of rebates by Avista, and ensures close communication with trade allies. Anti-fraud provisions (such as requiring customer information and signature on rebate forms, or conducting site visits to verify installation) must be included in any such program adaptation. Data Tracking Consider enhancing uniformity of program tracking by standardizing data formats. Complete Wherever possible, Avista should develop tracking methods that support consistent analysis across programs. For example, a standardized format for customer address data across separate databases would ease database combination or integration. Track follow-through on audit recommendations. In Progress In planning for future Audit program implementation, Avista should consider additional tracking of customer follow-through on recommendations, both through other Avista rebate programs, and independently without rebates. Marketing and Outreach Continue pursuing diverse marketing and outreach strategies. Complete Avista should maintain its multi-faceted approach to reaching a broad range of customers, while targeting difficult-to-reach customers where appropriate. Continue enhancing social media marketing. Complete Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 268 of 296 84 Recommendations Offered in PY2010 Residential Evaluation Report Activity Since Avista reported that younger customers can be more difficult to reach, the marketing team should continue to enhance its social media marketing efforts. Ensure contractors have adequate information to disseminate. Limited Activity Since trade allies were one of the commonly reported ways that participants learned about the program, Avista must focus on providing trade allies with adequate and accurate information. This can be achieved by distributing updated materials regularly, holding trainings for contractors, or formalizing the trade ally network to ensure frequent communication. For example, Avista should consider providing printable online information sheets that trade allies can print and disseminate to their customers. Participant Experience and Satisfaction Continue emphasizing good customer service and offering customer-friendly programs. Complete These areas should be maintained as priorities in future program planning and implementation. Effectiveness of Implementers Consider expanding offerings of Simple Steps program. Complete Avista should consider the benefits of adding measures to the Simple Steps program. Additional measure offerings may increase potential participation and savings. Require [CLEAResult] to ensure evaluators have access to retailers. Limited Activity Upstream program evaluation often requires access to retail locations, for shelf-stocking studies and in-store intercepts, for example. In order to ensure future evaluability of the Simple Steps program, [CLEAResult] should require participating retailers to grant such access to evaluators when necessary. Trade Ally Participation and Satisfaction Enhance and formalize trade ally network. In Progress Avista should offer additional training and informational materials to contractors who serve the HVAC program, to ensure high-quality program information reaches customers, and to encourage program promotion through contractors. Residential Portfolio Consider various opportunities for expansion. Complete Avista should regularly assess the viability of expanded program and measure offerings. Avista may consider various possible expansions including: - Adding showerheads to Simple Steps - Additional cost-effective measures in HVAC program - Behavioral programs, energy education programs Table 36. Implementation of PY2010 Residential Evaluation Recommendations Program Participation Renew emphasis on customer outreach and mass marketing, including refreshing campaign messaging and using trade allies. Complete Consider using lessons learned from the Home Energy Audit Pilot Program to design and implement a full-scale program that employs audits or a similar whole-house approach. Limited Activity Program Design Consider additional program requirements to ensure measure savings remain in line with expectations. Limited Activity Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 269 of 296 85 Recommendations Offered in PY2011 Residential Evaluation Report Activity . Explore possible benefits of outsourcing simple rebate processing for ENERGY STAR appliances and hot water heaters in order to allow program managers to focus on long-term program considerations. In Progress Market Characteristics Ensure future program effectiveness by continuing to update program offerings and design to reflect changes in market conditions Complete Data Tracking Ensure consistency in data tracked across multiple databases including: the multi-program database; the JACO database; the Home Energy Audit database; and Avista’s central customer information database. In Progress If Avista continues the Home Energy Audit Program, audit tracking should be enhanced to include: integration into the central participant rebate database; and more robust tracking of data collected through the audit, and of follow-through installations. In Progress Marketing and Outreach Avista should maintain its multifaceted approach to reaching a broad range of customers, while targeting difficult-to-reach customers, where appropriate. Possible website enhancements include: In Progress Participant Experience and Satisfaction Continue to prioritize customer satisfaction, and take advantage of high satisfaction by targeting past participants for future participation. Complete Residential Program Freeridership Continue conducting research to inform decision making about future program improvements/continuation. Complete Effectiveness of Implementers Explore possible benefits of third-party program implementation. In Progress Avista’s newly launched online rebate application system may alleviate staff burden associated Trade Ally Participation and Satisfaction Avista should investigate the possibility of a more formal relationship with trade allies. In Progress Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 270 of 296 86 Appendix B: Status of PY2010 and PY2011 Nonresidential Evaluation Recommendations Table 37. Implementation of PY2010 Nonresidential Evaluation Recommendations Program Documentation Developing a program manual, with implementation plans, operational procedures, marketing strategies, and verification protocols aggregated into a single program handbook, could help to establish a link between EM&V policies found in the high level planning documents and the program’s operational management. Complete Customer Feedback Address customers’ perceived lack of information about program offerings. In Progress  Enhance outreach and communication efforts for participants, nonparticipants, and partial participants.  Develop additional printed program materials to educate customers about program opportunities.  Consider regularly scheduled online Webinars to assist customers with questions about program incentives, eligibility, and application processing. Trade Ally Participation and Satisfaction Provide regular trade ally communications through targeted outreach efforts, such as a Website, monthly e-mails, or a newsletter. Complete A Website dedicated for trade allies could enable registration, thereby providing a method for compiling (and updating) trade ally profiles and contact information. Consider providing additional promotional materials that would highlight various program technologies available to customers. This would not require that Avista endorse any one contractor. Complete Explore ways to leverage strong working relationships forged between customers and contractors within the community by sponsoring additional program working sessions, luncheons, or Webinars that provide guidance for trade ally outreach efforts. Complete Application Processing and Data Tracking Offer site-specific application forms online. Limited Activity Although it would be ideal to enable submission of forms online, simply making the forms downloadable and mail-in would provide a good first step. In addition, consider including guidelines for completing site-specific forms. Gather additional feedback from customers and trade allies about how site-specific form enrollment and processing could be streamlined. In Progress Gathering more detail about program and project measures in the participant database would enable a better understanding of the kinds of projects done in the past (by different types of customers and end-uses). In Progress Additional information could be used to market specific types of projects to other customers who have the same end-use equipment. Marketing and Outreach Ensure allocation in future marketing budgets dedicated for nonresidential program marketing and outreach efforts. Complete Develop additional marketing materials targeted specifically for trade ally outreach to customers. Complete These materials would enable Avista staff to leverage existing trade ally relationships in the community. Make them available at a trade ally website for printing. Conduct marketing surveys, and targeted marketing research that would gather additional Limited Activity Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 271 of 296 87 PY 2010 Recommendation Activity information about customer facilities and technology end-uses. Conduct targeted marketing research of largest 100 customers with hourly demand data. Limited Activity Quality Assurance and Verification Consider developing a verification protocol to document pre- and post-inspection procedures for prescriptive programs, and ensure data tracking for project installation. In addition, protocols should highlight any differences in verification procedures used for prescriptive and site-specific programs. In Progress Table 38. Implementation of PY2011 Nonresidential Evaluation Recommendations Program Management and Implementation Consider a method for prioritizing management tasks, thus enabling allocation of more time for planning and development of program documentation. In Progress Revisit the staffing needs for delivering the current programs. In Progress Revisit the option of using third-party implementers for some programs. Limited Activity Consider round tables with the program implementation, management, and policy team to facilitate additional communication regarding planning and evaluation. Complete Consider designating a central leadership role for the Site-Specific Program to oversee future planning and vision, and ensure that it continues to deliver cost-effective energy savings to the C&I portfolio. In Progress Further investigate contractor issues to ensure high satisfaction levels of EnergySmart Grocer program participants Complete Customer Feedback Continue to leverage contractors to reinforce the program’s messages, particularly in communicating program offerings to small-to-medium customers. Complete Further explorations could determine if contractors offer better market coverage, are more likely to connect with customers when purchases are being contemplated, provide a more compelling value proposition, or offer other lessons Avista could apply, both with contractors and across other communications channels. Strategies should be developed to penetrate leased C&I spaces, targeting building owners, managers, and brokers of leased space. Examples could include: In Progress  Tailored messages, delivered through presentations or workshops in conjunction with the Building Owners and Managers Association and commercial real estate associations.  Designated point-of-contact and web information for building managers and brokers.  Incentive and financing solutions, such as on-bill financing, green lease arrangements, and bonus incentives targeting retrofits when new tenants move in. Cadmus recommends Avista evaluate alternative strategies for reaching small-to-medium businesses cost-effectively via contractors, direct install, or more Prescriptive, “self-serve” options via the Avista website. Such strategies could include: In Progress  Promote newsletter sign-ups and exploration of program information on the website.  In program information, cross-reference sources or the availability of answer lines.  Evaluate measures installed by small customers in the Site-Specific Program for inclusion in a Prescriptive program. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 272 of 296 88 PY2011 Recommendation Activity Where customers expressed lower satisfaction levels, program elements should be investigated. Such investigations might include: In Progress  Review audit program communications and supporting collateral to improve customers’ understanding of the depth of audits, and recommendations. Consider providing information about economic advantages to energy efficiency such as improved benefits to costs ratios, and simple payback.  Determine/track cycle times for customer follow-up after audits and for rebate applications; if reasonable times are exceeded, consider implementing follow-up communications to keep customers informed and ensure internal follow-up, if needed.  Confirm issues identified in the EnergySmart Grocer program have been resolved. Trade Ally Feedback Explore more formalized ways to aid trade allies in promoting nonresidential programs to customers. Avista should continue efforts to expand outreach to trade allies, through sponsored events and workshops, breakfast meetings, focus groups, and other targeted communications. Complete Given trade allies’ requests for a dedicated Avista contact, more one-on-one communication, and additional materials to inform customers about the programs, more timely feedback could be achieved through online resources. These resources may also help to reinforce the program’s messages, offering resources through multiple channels by providing the following services: Complete  Offering a dedicated website, containing guidance through webinars and video presentations.  Online registration for events or information requests.  An online help desk or phone hotline, which would direct customers to answers for frequently asked questions, or would reserve more complicated questions for program staff.  Other, additional promotional materials, posted online, such as handouts regarding costs and benefits of energy-efficiency equipment. Special Report: Lighting Take a more proactive role in communicating with customers: Complete  Upcoming changes in lighting product availability  Avista’s program availability to offer them help  When the T-12 program will end  Communications should also offer help in identifying T-12 lamps (descriptions or illustrations of size), and inform customers about the lighting quality of alternatives. To motivate contractors and accelerate customer action, Avista may consider creating a lighting contractor partnership program, with incentives paid to contractors (or rebates paid directly to contractors) for encouraging customers to update lighting fixtures while incentives remain available. Complete Avista should consider a new program, targeting replacements of T-12s in inventory, to help customers upgrade to more efficient new fixtures and lamps, and to move toward realization of energy savings in their facilities. In Progress Marketing and Outreach To ensure the recognition and longevity of focused outreach efforts, Cadmus recommends Avista continue expanded annual market campaigns to enable more focused targeted marketing for the nonresidential programs. In addition, nonresidential programs may benefit from these additional suggestions: Complete  Develop a detailed marketing plan enabling annual tracking and assessment of activities. The marketing plan would identify target audiences, clarify marketing objectives, and identify evaluation metrics.  Continue efforts to enhance the business website through promotions and featured business Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 273 of 296 89 PY2011 Recommendation Activity Application Processing and Data Tracking Drawing upon the review of application forms and databases, interviews with staff, and survey results, Cadmus recommends the following: In Progress    Work toward integrating customer information tracking databases, thus enhancing efficiency and reducing error. In Progress Consider incorporating changes to forms to account for new data collected through calculators. In Progress QA and Verification Cadmus recommends Avista continue strengthening feedback loops for performance review of large projects. To achieve greater consistency, Avista should consider documenting pre- and post- inspection protocols, which could include the following, recommended, industry best practices for C&I programs: In Progress  Establish inspection frequency, based on a program’s relationship with vendors, number of     Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 274 of 296 90 Appendix C: 2012 Nonresidential Process Evaluation Memorandum This section provides the text from the nonresidential process evaluation memo drafted by Cadmus and sent to Avista on August 2, 2013. MEMORANDUM To: Lori Hermanson, Avista From: Danielle Kolp and Hope Lobkowicz, Cadmus Subject: 2012 Process Evaluation Memorandum Date: August 2, 2013 Cadmus’ 2012 process evaluation activities for the Avista nonresidential portfolio included the following:  A Best Practice Comparative Review (memo delivered in February 2013);  In-person interviews with program stakeholders; and  Database and realization rate review. Because Cadmus is not developing a formal process evaluation report for Avista until 2014, this memo presents the findings of the staff interviews and database and realization rate review conducted for the 2012 program year. Our objective is to provide key personnel at Avista with findings now to assist them in improving program processes in real-time. Key Findings Interview Findings: Large Project Review Challenges and Changes In August 2011, Avista instated a new internal system to independently review site-specific projects with incentives greater than $50,000. This review stemmed from a recommendation in the 2010 Moss Adams process report, pursuant to the 2010 Washington Utilities and Transportation Commission (UTC) rate case settlement terms. The objective of the independent review was to examine project evaluation reports prior to entering into contract with the customer, to ensure that:  All supporting documentation was in place,  Savings calculations were reasonable and well supported, and  The project complied with tariff rules. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 275 of 296 91 Avista staff who participated in the review process experienced multiple challenges, which are discussed in more detail below. By the end of 2012, staff concluded that the review process was not functioning efficiently, nor did it align with the intention of the Moss Adams report recommendation. Avista suspended the review process on January 1, 2013. In 2013, Avista intends to implement a new approach for reviewing site-specific projects, with the goal of balancing customer service and expediency with a sound review. In June 2013, Avista demand-side management (DSM) staff were finalizing this new approach. Review Process Challenges Identified by Avista Cadmus interviewed five Avista DSM staff who were involved in the review process. During the interviews, we discussed several core areas of concern with the process and determined that the intended protocol was not being followed. The process dictated that the Planning, Policy, and Analysis (PPA) team independently review the energy savings and proposed incentive levels of all site-specific projects with incentives greater than $50,000, to ensure these impacts were calculated reasonably. In 2012, only one-third of projects that met the criterion were sent to PPA for review. When Cadmus asked staff about the challenges with this review process, the following four main issues surfaced: 3. Different focused attention across teams. One staff person reported that the key personnel within the DSM department involved in the review had different focused attention, which in some cases translated to varying objectives for reviewing and approving projects. This is a problem across many organizations and is, by no means, limited to Avista. While implementation teams are most concerned with customer satisfaction and speedy and efficient delivery, planning and evaluation teams are most concerned with compliance. At Avista, the Implementation team was focused heavily on the customer relationship, while PPA was focused on ensuring compliance with the tariff, minimizing the risk of uncertainty associated with claimed savings, and navigating relationships with regulatory bodies and stakeholders. This is not to say that neither team was unconcerned with the other’s objectives. While staff agreed that their roles support the comprehensive functions and all overarching goals of Avista’s DSM programs, specific daily priorities added to misunderstandings about the value of the review and, in some cases, differing opinions on how and when to resolve issues. 4. Transparency. Some staff who were heavily involved in Avista’s site-specific projects reported not understanding the purpose, actions, or outcomes of the review. Without program- stakeholder buy-in at all levels of the process, successful implementation was challenging. One particular concern was a lack of information regarding how long the review would take to complete for each project; this made it difficult to communicate accurate information to customers on the status of their projects and the expected timeline. 5. Time lag and time commitment. A common obstacle cited by all staff interviewed by Cadmus was that the review process took too long to complete for each project. Often, the issues identified during the review required further discussion to understand the assumptions behind Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 276 of 296 92 the savings estimation, new data or information requests from the customer, or new analysis, which caused delays. Another challenge was the volume of the projects and limited staff resources. Having only one engineer dedicated to reviewing the large projects was problematic and often caused bottlenecks. 6. Linking review with concrete actions. The review process lacked a formal follow through procedure for problems uncovered during the review. This caused frustration as, at times, findings and recommendations were not implemented. Interviews and documentation of the review process indicated that the extent to which the issues were resolved varied. For enhanced delivery of DSM services, there needs to be an agreement regarding the best path forward for calculating savings. Issues Identified Through the Large Project Review One of the major findings of the review was the overall reliance on customer-supplied data and the need for a reliable and replicable approach to source that data. Avista staff were in agreement that increasing the clarity and transparency about where engineering assumptions and inputs were coming from was a needed improvement and a successful outcome of the review process. Cadmus reviewed the communication logs for 22 projects that underwent the internal review. In addition to the above issue of reliance on customer-supplied data or assumptions (which was inaccurate in some cases), the following issues were documented for these projects:  Interactive effects were accounted for incorrectly;  Projects had missing documentation, such as invoices; and  Engineering errors resulted in incorrect claimed savings and incentive amounts (the significance of these errors varied in size). Planned Process Improvements In 2013, Avista staff worked together to design a new system to address the challenges cited and issues discovered with the 2012 review process. The staff is currently implementing a two-step review process for all site-specific projects that entails a technical review by the engineering team and an administrative review by program staff.  Technical Review: Ensures that savings and incentive calculations in a project’s Evaluation Report are well-supported, and calculated according to tariff terms and Dual Fuel Incentive Calculator policy. The new system includes a checklist with questions that guide the review, along with instructions and policy guidelines. The Technical Review will be completed before the evaluation report is sent to the customer, which contains estimated energy savings and the corresponding incentive level.  Administrative Review: Ensures that minimum requirements are met before a contract is issued with a customer and before an incentive is paid. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 277 of 296 93 In the new process, PPA conducts random spot-checks to QA/QC projects, and ensures that the review process is smooth and effective. A main distinction between the 2012 and 2013 process is that this random spot-check is intended to happen after the project has entered contract, or, in some cases, after the incentive has been paid. According to implementation staff, this will help overcome bottleneck challenges. Both checklists (the Technical Review and Administrative Review) will be formalized documents known as Top Sheets, which will be attached to project documentation through the life of the project. Avista intends to synchronize the Top Sheet information with Tracker, the engineering database, and with SalesLogix, the customer information system that houses nonresidential rebate and incentive information. In June 2013, the Implementation team began using Top Sheets for all projects. 2011-2012 Database and Realization Rate Review As part of the 2012 process evaluation, Cadmus reviewed Avista’s 2012 nonresidential project database and the 2011 and 2012 realization rates for the nonresidential portfolio. The documents that were part of each effort and our associated research questions are listed in Table 39. Table 39. Database and Realization Rate Review Activities Database Review 2012 SalesLogix Database Extract Are data being tracked accurately and consistently? Are contracts issued in accordance with Avista policy? Do incentives comply with tariff rules for Washington and Idaho? Realization Rate Review 2011 and 2012 Impact Evaluation Sample Why do some projects have a very low or very high realization rate? Are there opportunities for Avista to improve the process of calculating reported savings to improve the realization rates? Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 278 of 296 94 Database Review Tariff Schedules 90 and 190 govern how Avista can spend funds from the Energy Efficiency Rider Adjustment paid by Washington and Idaho ratepayers.22 To assess compliance with these Tariff Schedules, we examined two main indicators: 1. Project incentive amount: electric and natural gas project incentives should not exceed 50% of the incremental cost of the project (p. 3 of Schedule 90; p. 2 of Schedule 190). 2. Project simple payback. a. For lighting measures, the simple payback period must be a minimum of one year and should not exceed eight years. (p. 2 of Schedule 90). b. For non-lighting electric and natural gas measures, the simple payback period must be a minimum of one year and should not exceed 13 years. (p. 2 of Schedule 90; p. 2 of Schedule 190). The tariff rules make exceptions for the following programs or projects (p. 3 of Schedule 90; p. 2 of Schedule 190):  DSM programs delivered by community action agencies contracted by Avista to serve limited income or vulnerable customer segments, including agency administrative fees and health and human safety measures;  Low-cost electric/natural gas efficiency measures with demonstrable energy savings (e.g., compact fluorescent lamps); and  Programs or services supporting or enhancing local, regional, or national electric/natural gas efficiency market transformation efforts. (In 2012, Avista considered new construction fuel conversions in multifamily building projects and T12 to T8 commercial lighting conversion projects as market transformation efforts.) Applicability of Tariff to Prescriptive Projects At the time of this memo, Avista’s tariff was undergoing revisions and a new tariff was filed on June 26, 2013. Avista uses the tariff provisions to: 1) design prescriptive measure offerings and incentive amounts and 2) evaluate the eligibility of site-specific projects on a project-by-project basis to ensure compliance before approving them. Cadmus does not believe the tariff language was clear enough on the topic of 22 Schedule 90: Electric Energy Efficiency Programs, Washington. Available at: http://www.avistautilities.com/services/energypricing/wa/elect/Documents/WA_090.pdf; Schedule 190: Natural Gas Energy Efficiency Programs, Washington. Available at: http://www.avistautilities.com/services/energypricing/wa/gas/Documents/WA_190.pdf; and Schedule 90: Electric Energy Efficiency Programs, Idaho. Available at: http://www.avistautilities.com/services/energypricing/id/elect/Documents/ID_090.pdf Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 279 of 296 95 compliance to conclude whether individual prescriptive projects should be subject to the simple payback period and incentive cap restrictions at the time of rebate application approval. Internally, Avista staff also expressed disagreement on this matter. For purposes of this review, Cadmus evaluated both prescriptive and site-specific projects against the provisions of the tariff described above, to allow Avista to review the findings and incorporate them into their planning. It should be clear that by presenting the prescriptive findings below, Cadmus is simply suggesting that better clarity is needed and not necessarily that these projects were out of compliance. Avista’s proposed tariff clarifies that moving forward, site-specific projects are subject to the incentive cap and simple payback periods at the time of project approval, while these parameters will be used in the planning process for prescriptive measure offerings and incentive amounts. Simple Payback Findings The majority of projects were in compliance with simple payback rules. Cadmus found that all site- specific projects met the 13-year and eight-year payback periods, with the exception of some legacy projects that were initiated before the new tariff rules took effect on January 1, 2011. Less than 10% of prescriptive projects exceeded tariff simple payback periods. Table 40 summarizes our findings. Table 40. 2012 Projects Exceeding Simple Payback Periods Site-Specific Projects 0 0 n/a n/a n/a n/a Prescriptive Lighting (includes market transformation and T12 projects)* 281 9% 4,438,942 kWh 13% $855,535 10% Prescriptive Non-Lighting (excludes multifamily) 39 6% 113,398 kWh 2% $72,131 7% 7,810 therms 7% Total 320 8% 4,552,340 kWh 12% $927,666 10% 7,810 therms 7% * Avista’s database extract does not denote which projects involved T12-T8 lighting conversions. Upon reviewing a sample of 10 prescriptive lighting projects that exceeded the eight-year simple payback period, Avista found that five projects involved a T12 to T8 conversion and three projects contained database errors that inflated the simple payback period. In these cases, what should have been entered as months were assumed to be years, and multiplied by 12. The sample size for this manual review was not large enough to extrapolate findings to the full population. However, based on the review findings, it is probable that a large proportion of the projects Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 280 of 296 96 included in Table 40 involved T12 to T8 conversions and/or experienced database errors, thus significantly lowering the impact on energy savings and incentive costs. Project Incentive Findings Site Specific The vast majority of site-specific projects had incentive costs that were compliant with the tariff rule not to exceed 50% of the incremental project cost. Initially, Cadmus found 74 site-specific projects (19%) that exceeded this cap. Upon reviewing these projects, however, we found that nearly half experienced a rounding error from Avista’s Dual Fuel Incentive Calculator that put them over the 50% limit by just $0.25 (see Figure 43). Avista staff reviewed the remaining projects to understand why they exceeded the incentive cap, and found that the majority were incorrectly entered in SalesLogix. Avista reported that these projects had been calculated and processed as prescriptive projects, but incorrectly entered into the database as site-specific. Figure 43. Range of Incentive Amounts Exceeding 50% of Incremental Costs, 2012 Site-Specific Projects Prescriptive Significantly more prescriptive projects (74%) exceeded the 50% cap. As noted above, this finding was expected because Avista’s program design and delivery strategy did not consider prescriptive payments as being subject to the tariff rules, and the lighting market transformation effort exceeded 50% by design. Table 41 outlines the incentive payment and energy savings impacts from projects that exceeded the 50% incentive cap. 56 9 4 2 2 1 0 10 20 30 40 50 60 Under $10 $10-$100 $100-$500 $500-$1,000 $1,000-$5,000 Over $5,000 Pr o j e c t C o u n t Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 281 of 296 97 Table 41. 2012 Prescriptive Projects Exceeding 50% Incentive Cap Prescriptive Lighting (includes market transformation and T12 projects)** 2,574 80% 26,747,965 kWh 81% $2,290,031 28% Prescriptive Non-Lighting (excludes multifamily) 349 50% 3,220,704 kWh 58% $475,437 45% 16,684 therms 14% Total Prescriptive 2,923 74% 29,968,669 kWh 77% $2,765,468 30% 16,684 therms 14% * Cost impact represents the aggregate amount exceeding 50% of the incremental cost. ** Avista’s database extract does not denote which projects involved T12-T8 lighting conversions. Again, Avista manually reviewed 10 lighting projects that were over the 50% cap, and found that eight were T12 to T8 conversion projects, considered market transformation. Based on these findings, it is probable that a large proportion of the lighting projects listed in Table 3 involved T12 to T8 conversions, which would greatly reduce the cost impacts and energy saving impacts of from lighting projects over the 50% cap. Data Entry and Data Tracking In addition to assessing policy conformance, Cadmus reviewed the 2012 database for data accuracy and completeness. We found that:  8 projects were recorded as paid before construction was completed (most of these were entry errors)  12% of all projects were missing Construction Complete dates  44 projects (1% of all projects) were missing incremental cost data  18% of site-specific projects were missing contract date fields in SalesLogix  44% of site-specific projects were missing post-verification dates (and it is Avista’s policy to conduct post-installation inspections of all site-specific projects) Avista reviewed 20 prescriptive lighting projects to determine whether they were market- transformation projects (as noted above). They also uncovered several data errors with these specific projects. In all 20 projects, at least one of the following issues was found:  Simple payback periods were entered in the database in years instead of months,  Simple payback periods were entered incorrectly (SalesLogix data fields were not consistent with calculations),  Prescriptive projects were entered as site-specific projects, Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 282 of 296 98  Information from invoices regarding quantity and type of light fixtures was not transferred to prescriptive incentive forms and SalesLogix correctly,  Ineligible measures were rebated, and  Incentives were calculated incorrectly. Realization Rate Review Cadmus’ impact evaluation methodology consisted of validating the reported savings for a sample of projects by conducting independent metering, simulation, or regression analysis and by visiting the project sites to verify that equipment was installed and operating as intended. The result of our project- level measurement and verification tasks is a verified, or ex post, savings value for each project in the sample. The ratio of verified savings to reported savings is the project’s realization rate. A realization rate of 100% indicates that no adjustments were made to the reported savings value. In 2011, Cadmus’ nonresidential impact evaluation sample consisted of 179 electric and gas projects.23 Of those , the majority (n=112) required a saving adjustment by more than 10%. That is, 63% of projects had realization rates of either 110% or greater, or 90% or lower. Specifically, just 35% of electric projects and 42% of gas project realization rates ranged between 90% and 110%. This changed in 2012, when the majority of projects (64 of 101)24 experienced realization rates between 90% and 110% (see Figures 4 and 5 below). Cadmus analyzed how frequently the evaluation resulted in an upward or downward adjustment of reported savings, by how much, and the reasons behind the discrepancy between reported and evaluated savings. The purpose of this review is to provide Avista with information to assist in improving the reliability of the reported savings in the future, thereby improving realization rates for the nonresidential portfolio. Direction, Frequency, and Magnitude of Verified Savings Adjustments Cadmus determined that when savings needed to be adjusted by more than 10%, they were more likely to decrease than increase. In other words, most reported savings for projects in this group were being overestimated, and the verification process resulted in a downward adjustment. This was true for all 2011 projects, and for all 2012 electric projects. In 2012, gas projects required more upward adjustments. 23 This number reflects projects with gas savings and electric savings. We actually evaluated 157 unique projects, some of which achieved dual-fuel savings. For the purpose of the realization rate review, we treated gas savings separately from electric savings. 24 The full 2012 impact evaluation sample contained 109 projects. We excluded eight projects from our analysis that still had measurement and verification activities occurring at the time of writing this report. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 283 of 296 99 2011 Projects Figure 44 illustrates the distribution of realization rates in increments for 2011 projects. In 2011, 51 electric projects had a realization rate below 90% (42%), while 27 electric projects had a realization rate above 110% (23%). Gas projects exhibited a similar pattern, with 26 projects having a realization rate below 90% (44%) and eight having a realization rate above 110% (14%). Figure 44. Distribution of 2011 Realization Rates by Increments for Electric and Gas Projects* *Note: Percentages may not match above text exactly due to rounding For electric projects, the relative proportion of reported kWh savings in each increment was relatively consistent with the number of projects in that increment. However, for gas projects, the relative proportion of reported therm savings in each increment did not accurately represent the corresponding number of projects. For example, while just 19% of gas projects experienced a realization rate of below 50% (but more than 0%), these projects represented 47% of reported savings. Dividing the projects by increments revealed that a large portion of the projects with realization rates below 90% were in fact below 50%, and most of the projects with realization rates over 110% were actually over 150%. This indicates that not only was the range of realization rates large, but a significant portion of reported savings values were substantially different from verified savings, requiring an adjustment of 50% or greater. 2012 Projects In 2012, realization rates improved. Rates were less variable, and projects required smaller reported savings adjustments than those in 2011. For example, 61% of electric projects and 67% of gas projects had a realization rate between 90% and 110%, leaving only approximately one-third of projects that required an adjustment over 10% (see Figure 45). 3% 7% 8% 4% 47% 19% 16% 14% 9% 12% 7% 10% 4% 7% 16% 14% 29% 42% 38% 35% 6% 3% 5% 3% 2% 2% 4% 8% 10% 15% 0%10%20%30%40%50%60%70%80%90%100% Proportion of Reported Therms Gas Projects (n=59) Proportion of Reported kWh Electric Projects (n=120) Ga s El e c t r i c 0 Below 50%50 to 75%75 to 90% 90 to 110%110% to 125%125% to 150%Over 150% Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 284 of 296 100 Of the 2012 electric projects that required an adjustment over 10%, most required a downward adjustment (18 projects; 31%). This is consistent with 2011 results. Of those 2012 gas projects that required an adjustment over 10%, the direction was upward (eight projects; 19%). Figure 45. Distribution of 2012 Realization Rates by Increments for Electric and Gas Projects *Note: Percentages may not match above text exactly due to rounding Cataloging Projects with High and Low Realization Rates To understand more about the projects that had severe adjustment factors (very high or very low realization rates), we conducted a desk review of the project files and engineering analyses for a sample of projects from 2011 and 2012. Specifically, this sample entailed projects with electric savings that had been adjusted by over 25% in either direction (a realization rate below 75% or above 125%). The original sample size was 75 projects; 57 from 2011 and just 18 from 2012. Upon reviewing the 2011 project files, we found that seven projects did not have sufficient reported savings documentation to accurately conclude the reason for the savings adjustment. Therefore, the final 2011 sample size was 50, leading to an overall sample size of 68. Based on our review, Cadmus concluded that there were nine main reasons for the savings adjustments; these are outlined in Table 42. 11% 5% 5% 4% 10% 12% 8% 7% 5% 2% 7% 70% 67% 64% 61% 9% 12% 3% 2% 2% 2% 9% 5% 7% 1% 0%10%20%30%40%50%60%70%80%90%100% Proportion of Reported Therms Gas Projects (n=42) Proportion of Reported kWh Electric Projects (n=59) Ga s El e c t r i c 0 Below 50%50 to 75%75 to 90% 90 to 110%110% to 125%125% to 150%Over 150% Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 285 of 296 101 Table 42. Reason Categories for Variable Realization Rates 1. Participant Operator Error Savings required adjustment due to customer actions, such as installing or operating equipment incorrectly 2. Calculation Error in Reported Savings Reported savings calculations or assumptions were incorrect 3. ENERGY STAR® Appliances Deemed Savings Update Cadmus used updated deemed savings values for ENERGY STAR clothes washers, dishwashers, freezers, and refrigerators to verify savings, requiring an adjustment from the reported values, which relied on older deemed savings estimates 4. Cadmus Metering Results vs. Avista Simulation or Analysis Cadmus used metering results to inform verified savings, while Avista used other tools to generate reported savings estimates 5. Cadmus Metering Results vs. Avista Metering Results Both Cadmus and Avista used metering results to inform savings values; however, the companies’ parameters or timing differed 6. Database Error Some values in the database extract were erroneous due to a database error, not a human error, and savings needed adjustment to reflect the accurate value 7. Cadmus Calculation Methodology vs. Avista Calculation Methodology Cadmus and Avista used different methodologies to calculate savings (i.e., regression analysis versus simulation), creating different results 8. Inaccurate Lighting Hours-of-Use (HOU) Estimates The reported savings for some lighting projects were based on incorrect HOU assumptions 9. Equipment Verification The on-site equipment parameters (size and efficiency) differed from the assumptions used in the original savings estimate In 2011, the most frequent reasons for savings adjustments of 25% or greater were due to metering results being over the original estimates formed using simulation or analysis (n=10) and calculation or assumption errors in the reported savings values (n=10). Other top reasons included ENERGY STAR deemed savings updates (n=9) and differences in Cadmus’ and Avista’s calculation methodology (n=8). In 2012, there were far fewer projects with adjustment factors of 25% or greater. The top reason categories in 2012 stayed relatively consistent with those in 2011, excluding the ENERGY STAR deemed savings updates. Figure 46 illustrates the number of projects in each of the reason categories outlined in Table 42, across both years. Table 46 at the end of the memo, lists the specific projects included in the review and a description of each project’s specific savings adjustment. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 286 of 296 102 Figure 46. Number of Projects with Savings Adjustments of 25% or Greater by Category, 2011-2012 Impact on Gross Savings While the majority of savings adjustments in 2011 resulted in decreased savings, certain reason categories experienced realization rates higher than 100%, on average. For example, three reason categories (Cadmus Metering Results vs. Avista Simulation or Analysis, ENERGY STAR Appliances Deemed Savings Update, and Equipment Verification) resulted in increased savings. In other words, the projects in these groups experienced realization rates higher than 100%, on average. In 2012, just one reason category (Cadmus Metering Results vs. Avista Simulation or Analysis) resulted in increased savings. Projects in the other 2012 reason categories (Calculation Error in Reported Savings, Cadmus Calculation Methodology vs. Avista Calculation Methodology, and Participant Operator Error) resulted in decreased savings. The aggregate kWh impact for each 2011 reason category is listed in Table 43. The aggregate kWh impact for each 2012 reason category is listed in Table 44. 6 5 6 1 10 10 9 8 6 3 2 1 1 0 2 4 6 8 10 12 Nu m b e r o f P r o j e c t s 2012 2011 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 287 of 296 103 Table 43. 2011 Reported and Verified Savings Associated with Reason Categories for Projects with Savings Adjustments of 25% or Greater Cadmus Metering Results vs. Avista Simulation or Analysis 10 1,563,768 3,189,989 -326,768 3% 1,952,989 16% 1,626,221 13% Calculation Error in Reported Savings 10 1,377,230 547,131 -859,210 7% 29,111 0.2% -830,099 7% ENERGY STAR Appliances Deemed Savings Update 9 892 2,043 -55 0% 1,206 0% 1,151 0% Cadmus Calculation Methodology vs. Avista Calculation Methodology 8 151,231 143,709 -57,262 0% 49,740 0.4% -7,522 0% Inaccurate Lighting HOU Estimates 6 394,977 128,449 -267,472 2% 944 0% -266,528 2% Participant Operator Error 3 788,713 0 -788,713 7% - 0% -788,713 7% Database Error 2 186,832 111,571 -75,261 1% - 0% -75,261 1% Cadmus Metering Results vs. Avista Metering Results 1 637,534 477,180 -160,354 1% - 0% -160,354 1% Equipment Verification 1 869 1,111 - 0% 242 0% 242 0% Total 50 5,102,046 4,601,183 -2,535,095 21% 2,034,232 17% -500,863 4% * This is the net difference as a percent of the total verified savings in the impact evaluation sample. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 288 of 296 104 Table 44. 2012 Reported and Verified Savings Associated with Reason Categories for Projects with Savings Adjustments of 25% or Greater Cadmus Metering Results vs. Avista Simulation or Analysis 6 1,544,211 1,768,173 -243,923 2% 499,241 4% 255,318 2% Cadmus Calculation Methodology vs. Avista Calculation Methodology 6 1,491,355 968,424 -534,120 4% 24,777 0% -509,343 4% Calculation Error in Reported Savings 5 420,208 340,768 -173,092 1% 93,652 1% -79,440 1% Participant Operator Error 1 21,000 - -21,000 0% - - -21,000 0% Total 18 3,476,774 3,077,365 -972,135 8% 617,670 5% -354,465 3% * This is the net difference as a percent of the total verified savings in the impact evaluation sample. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 289 of 296 105 Figure 47 illustrates 2011 projects in each reason category as a percentage of the total sample compared to the percentage of each categories’ net kWh impact. While the ENERGY STAR Appliances Deemed Savings Update category contained nine projects (representing about 8% of the total sample), the net difference in ex ante and ex post savings was actually minimal: a gain of 1,151 kWh (see Table 43), less than 0.07% of savings in the impact evaluation sample. The Cadmus Calculation Methodology vs. Avista Calculation Methodology category had similarly minimal savings despite containing a relatively large number of projects (eight). On the other hand, the Cadmus Metering Results vs. Avista Simulation or Analysis and Participant Operator Error categories represented 8% and 3% of projects, respectively, but the net differences in ex ante and ex post savings represented 13% and 7% of the total verified savings in the impact sample, respectively. Figure 47. Relative Proportions of Projects and Savings Impacts by Reason Category, 2011 In 2012, the percentage of projects in each category was higher than the respective percentage of kWh savings in each category (see Figure 48). For example, the Cadmus Metering Results vs. Avista Simulation or Analysis and the Cadmus Calculation Methodology vs. Avista Calculation Methodology categories both represented 10% of all projects in the evaluation sample, but their net differences in ex ante and ex post savings were relatively small, representing only 2% and 4% of the total verified savings in the sample, respectively. 8% 13% 8% 7% 8%7% 2% 3% 7% 2% 1% 1% 1% 1% 0%5%10%15%20%25%30%35%40% % of Total Projects in Sample Net Difference as % of Verified Savings in Sample Metering vs. Simulation Calculation Error, Rprt'd Savings ES Appliances Update Diff. Methodology Inaccurate HOU Participant Error Database Error Diff. Metering Results Equip. Verification Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 290 of 296 106 Figure 48. Relative Proportions of Projects and Savings Impacts by Reason Category, 2012 Conclusions and Recommendations Based on the above findings, we offer the following conclusions and encourage Avista consider the recommendations listed below to improve their internal processes. Large Project Review Process Conclusion: Avista’s 2011 Large Project Review process was not implemented successfully due to a series of communication issues and the absence of a mechanism to address concerns about project parameters and correct mistakes. In the first half of 2013, Avista has been designing a new process for all site-specific projects. While this process is underway, we have several recommendations may assist Avista with successful implementation and an effective process. Recommendations:  Effectively communicate the new project review process to all key team members. Many of the issues identified through Avista staff interviews regarding the prior review process centered on communication challenges. When implementing the new process, ensure that all stakeholders have a clear understanding of the review goals and correct protocol.  Ensure there are clear protocols in place for addressing issues identified during the review and the spot-check. To ensure that Avista and its customers are benefiting from the time and resources dedicated to this process, consider implementing some check-points and policies to clarify how and when to alter project savings and incentive levels if issues arise during the review. This may include designating a senior-level point person to serve as the decision-maker for questions or disagreements regarding a project or its calculation methodology. Consider identifying methods to ensure that all issues are discussed and resolved before incentive amounts are communicated to the customer. 10% 2% 8% 1% 10% 4% 2% 0%5%10%15%20%25%30%35% % of Total Projects in Sample Net Difference as % of Verified Savings in Sample Metering vs. Simulation Calculation Error, Rprt'd Savings Diff. Methodology Participant Error Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 291 of 296 107  Establish a goal for the number or percentage of projects that should undergo a random spot- check. Avista’s new process dictates that the PPA team will independently review a sample of projects, in addition to the peer review process. We suggest establishing a clear metric for the number or percentage of projects this sample will include, such as five projects or 10% of all projects.  Establish a reasonable goal for how long the review process should take. A core challenge with the prior review process was the time lag. Keeping in mind that any process aimed at improving the quality and accuracy of incentive payments and claimed savings will add time to existing procedures, Avista should internally discuss the amount of delay that is reasonable. It may be beneficial to create objectives for how long various steps of the process should reasonably take. For example, Avista could establish one goal to complete the first Top Sheet review within a certain timeframe, then establish another goal to guide how long it should take to resolve any issues, if identified.  Consider adopting a tiered approach to the review so that larger, high-risk projects receive more scrutiny before contracts are issued and incentives are paid. Under the planned approach, all site-specific projects will undergo peer review. Often, utilities employ a risk- mitigation approach to ensure that the largest and most expensive projects receive the most rigorous review before they are approved. Avista might explore adjusting their review process to focus the most time and resources on larger projects. An example of this type of approach is provided in Table 45. Table 45. Example of Tiered Approach to Large Project Review Peer Review All projects Second Engineering Review Projects above $50,000 Third Engineering Review Projects above $75,000 PPA Review Projects above $100,000 Pre-Installation Visits Projects above $100,000, plus others as needed Random Audit (spot-check) 5 projects or 10% of all projects  Consider structuring random spot-checks, or “audits,” to occur at various times of the process. The current review structure plans to have some projects receive independent review after the project evaluation report is complete or after the project is paid, so that any mistakes can be corrected for future projects. However, it may be beneficial to stagger projects so that a random portion also receives independent audits before incentive information is communicated to the customer. Database and Realization Rate Review Conclusion: The accuracy of Avista’s claimed savings, measured by realization rates, improved significantly from 2011 to 2012. Three of the four main reasons for large savings adjustments in 2012 Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 292 of 296 108 are largely outside Avista’s control. However, Avista can still improve the reliability of claimed savings estimates falling into the reason category of Calculation Error in Reported Savings.  Recommendation: Continue to move forward implementing the new review process to identify and resolve savings calculation errors. Conclusion: Most of the nonresidential projects were compliant with the 2012 tariff rules, but disagreement among DSM staff on tariff interpretation makes it difficult to draw conclusions about prescriptive projects. Avista has already begun updating the tariff to address this concern and create a more coherent policy. There are several improvements Avista can make to data tracking activities to clarify policy compliance on a project-by-project basis and improve data collection overall. Recommendations:  Clearly document legacy projects or market transformation projects in SalesLogix. Avista’s tracking system specifies measure type, but lacks detailed information such as whether the project involved a T12 to T8 lighting conversion. This makes it challenging to understand which projects are considered market transformation. Further, legacy projects are not specified. To streamline internal tracking, auditing, and evaluation, consider adding a field to denote which projects are eligible for transition policy (legacy projects) and which projects are considered market transformation, as well as any other project characteristics that warrant exception to tariff rules under Avista’s new policy.  Continue to improve data entry in SalesLogix to reduce missing or incorrect fields and enhance the comprehensive dataset. Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 293 of 296 109 Memo Appendix A Table 46 catalogues the projects requiring a savings adjustment of 25% or greater. Table 46. Projects Included in Realization Rate Review Cataloging 2011 36888 WA Industrial Process 59,728 105,220 176% Diff. Methodology 2011 34681 ID Shell 1,957 2,699 138% Diff. Methodology 2011 34682 ID Shell 983 198 20% Diff. Methodology 2011 35372 ID Shell 48,950 5,988 12% Diff. Methodology 2011 36974 WA Appliances 211 20 9% Diff. Methodology 2011 33651 WA HVAC Combined 4,015 6,660 166% Diff. Methodology 2011 35820 WA Appliances 32,760 19,436 59% Diff. Methodology 2011 35838 ID Prescriptive Lighting Interior 2,627 3,488 133% Diff. Methodology 2011 36170 ID Prescriptive LED Traffic Signals 53,784 27,973 52% Calculation Error, Rprt'd Savings 2011 30481 WA Industrial Process 283,902 117,823 42% Calculation Error, Rprt'd Savings 2011 29129 WA Industrial Process 571,750 283,747 50% Calculation Error, Rprt'd Savings 2011 34262 ID Shell 209 26 12% Calculation Error, Rprt'd Savings 2011 36341 WA Prescriptive Commercial Shell 2,411 10,682 443% Calculation Error, Rprt'd Savings 2011 36628 WA Prescriptive Commercial Shell 1,124 0 0% Calculation Error, Rprt'd Savings 2011 36315 WA Prescriptive Motors 438 274 63% Calculation Error, Rprt'd Savings 2011 23335 WA Industrial Process 308,652 0 0% Calculation Error, Rprt'd Savings 2011 35540 ID Prescriptive Lighting Exterior 20,417 41,257 202% Calculation Error, Rprt'd Savings 2011 32654 WA HVAC Combined 134,543 65,349 49% Calculation Error, Rprt'd Savings 2011 37395 WA HVAC Combined 32,570 16,285 50% Database Error 2011 37396 WA Lighting Interior 154,262 95,286 62% Database Error 2011 37074 WA Energy Star Clothes Washer 14 322 2301% ES Appliances Update 2011 37075 WA Energy Star Dishwasher 36 22 62% ES Appliances Update 2011 37070 WA Energy Star Clothes Washer 240 494 206% ES Appliances Update Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 294 of 296 110 Year Project ID State Measure Description Reported kWh Verified kWh Realization Rate Project Category 2011 37385 WA Energy Star Clothes Washer 240 322 134% ES Appliances Update 2011 36616 WA Energy Star Dishwasher 36 22 62% ES Appliances Update 2011 35371 Idaho Energy Star Dishwasher 36 22 62% ES Appliances Update 2011 35841 ID Energy Star Dishwasher 36 22 62% ES Appliances Update 2011 37089 WA Energy Star Clothes Washer 14 322 2301% ES Appliances Update 2011 37025 WA Energy Star Clothes Washer 240 494 206% ES Appliances Update 2011 36894 WA Prescriptive Comm Clothes Washer 869 1,111 128% Equip. Verification 2011 36140 ID Industrial Process 637,534 477,180 75% Diff. Metering Results 2011 33889 WA HVAC Combined 230,543 58,277 25% Metering vs. Simulation 2011 33510 WA HVAC Cooling 188,879 34,377 18% Metering vs. Simulation 2011 34653 WA Motor Controls HVAC 25,550 73,193 286% Metering vs. Simulation 2011 33334 WA Motor Controls HVAC 81,760 234,219 286% Metering vs. Simulation 2011 33424 ID HVAC Combined 16,414 25,557 156% Metering vs. Simulation 2011 33432 ID HVAC Combined 10,644 32,997 310% Metering vs. Simulation 2011 37477 ID Motor Controls HVAC 168,630 483,076 286% Metering vs. Simulation 2011 37471 ID Motor Controls HVAC 296,380 849,042 286% Metering vs. Simulation 2011 37478 ID Motor Controls HVAC 419,020 1,200,370 286% Metering vs. Simulation 2011 29646 WA HVAC Cooling 125,948 198,881 158% Metering vs. Simulation 2011 36137 WA Lighting Interior 20,207 3,160 16% Inaccurate HOU 2011 36470 WA Prescriptive Lighting Interior 5,676 1,765 31% Inaccurate HOU 2011 36559 WA Prescriptive Lighting Interior 353,228 113,298 32% Inaccurate HOU 2011 37187 ID Prescriptive Lighting Interior 9,108 3,803 42% Inaccurate HOU 2011 36016 WA Lighting Interior 4,218 2,939 70% Inaccurate HOU 2011 36017 WA Prescriptive Lighting Interior 2,540 3,484 137% Inaccurate HOU 2011 31378 ID HVAC Heating 48,173 0 0% Participant Error 2011 21278 ID Compressed Air 648,560 0 0% Participant Error 2011 35430 WA Motor Controls HVAC 91,980 0 0% Participant Error Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 295 of 296 111 Year Project ID State Measure Description Reported kWh Verified kWh Realization Rate Project Category 2012 37981 WA SS Multifamily 692,700 448,232 65% Diff. Methodology 2012 35602 WA SS Multifamily 692,700 448,232 65% Diff. Methodology 2012 33914 WA HVAC Combined 59,549 24,472 41% Diff. Methodology 2012 39533 WA SS HVAC Heating 7,986 0 0% Diff. Methodology 2012 38992 WA PSC EnergySmart- Case Lighting 3,720 2,236 60% Diff. Methodology 2012 38397 WA PSC EnergySmart- Industrial Proc 34,700 45,252 130% Diff. Methodology 2012 40766 WA SS HVAC Combined 53,250 7,650 14% Calculation Error, Rprt'd Savings 2012 34998 WA SS Appliances 91,823 38,934 42% Calculation Error, Rprt'd Savings 2012 39118 WA SS Compressed Air 8,413 0 0% Calculation Error, Rprt'd Savings 2012 35000 WA Lighting Interior 165,141 258,793 157% Calculation Error, Rprt'd Savings 2012 39794 WA SS Shell 101,581 35,391 35% Calculation Error, Rprt'd Savings 2012 35972 ID SS Industrial Process 1,047,737 1,406,904 134% Metering vs. Simulation 2012 39969 WA SS Industrial Process 115,911 165,636 143% Metering vs. Simulation 2012 38236 WA SS Lighting Interior 177,934 103,425 58% Metering vs. Simulation 2012 38276 WA SS Lighting Interior 185,688 86,794 47% Metering vs. Simulation 2012 39750 WA PSC Lighting Interior 6,318 3,953 63% Metering vs. Simulation 2012 39411 WA PSC Lighting Interior 10,623 1,461 14% Metering vs. Simulation 2012 32376 ID PSC PC Network Controls 21,000 0 0% Participant Error Exhibit No. 1 AVU-E-14-__ / AVU-G-14-__ B. Folsom, Avista Schedule 2, Page 296 of 296