20100323Knox Di.pdf

DAVID J. MEYER
VICE PRESIDENT AND CHIEF COUNSEL OF
REGULATORY & GOVERNMENTAL AFFAIRS
AVISTA CORPORATION
P.O. BOX 3727
1411 EAST MISSION AVENUE
SPOKANE, WASHINGTON 99220-3727
TELEPHONE: [phone]FACSIMILE: [phone]
DAVI D . MEYER~AVI STACORP . COM
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BEFORE THE IDAHO PUBLIC UTILITIES COMMSSION
) CASE NO. AVU-E-10-01
) CASE NO. AVU-G-IO-01
)
)
) DIRECT TESTIMONY) OF) TARA L. KNOX
)
IN THE MATTER OF THE APPLICATION
OF AVISTA CORPORATION FOR THE
AUTHORITY TO INCREASE ITS RATES
AND CHARGES FOR ELECTRIC AND
NATURAL GAS SERVICE TO ELECTRIC
AND NATURAL GAS CUSTOMERS IN THE
STATE OF IDAHO
FOR AVISTA CORPORATION
(ELECTRIC AND NATURAL GAS)
1
2
I . INTRODUCTION
Q.Please state your nam, business addess and
3 present position with Avista Corporation?
4
5
A.My name is Tara L. Knox and my business address
is 1411 East Mission Avenue, Spokane, Washington.I am
6 employed as a Senior Regulatory Analyst in the State and
7 Federal Regulation Department.
8
9
Q.Would you briefly describe your duties?
A.I am responsible for preparing the regulatory
10 cost of service models for the Company, as well as
11 providing support for the preparation of results of
12 operations reports.
15 Yes.
your educational background13Q.Would you
14 and professional experience.
A.I am a/of Washington State
16 Uni versi ty with a Bachelor of Arts degree in General
17 Humanities in 1982, and a Master of Accounting degree in
18 1990. As an employee in the State and Federal Regulation
19 Department at Avista since 1991, I have attended several
20 ratemaking classes, including the EEI Electric Rates
21 Advanced Course that specializes in cost allocation and
22 cost of service issues.I have also been a member of the
23 Cost of Service Working Group and the Northwest Pricing and
24 Regulatory Forum, which are discussion groups made up of
25 technical professionals from regional utili ties and
Knox, Di 1
Avista Corporation
1 utilities throughout the United States and Canada concerned
2 wi th cost of service issues.
3 Q.What is the scope of your testimony in these
4 proceedings?
5 A.My testimony and exhibi ts will cover the
6 Company's electric and natural gas cost of service studies
7
8
performed for this proceeding.Additionally,I am
sponsoring the electric and natural gas revenue
9 normalization adjustments to the test year results of
10 operations and the proposed retail revenue credit rate to
11 be used in the Power Cost Adjustment mechanism. I will
12 also provide an ove-rview of the electric load research
13 study that was recently completed by the Company. A table
14 of contents for my testimony is as follows:
15
16
17
18
19
20
21
22
23
24
25
26
27
Table of Contents Page
I . Introduction
II. Revenue NormalizationElectric
Natural Gas
III. Proposed Retail Revenue Credit Rate
IV. Electric Cost of Service
Illustration 1 Base Case Results
Illustration 2 Methodology Change Impact
Demand Study
V. Natural Gas Cost of Service
Illustration 3 Base Case Results
1
3
3
7
10
12
20
21
21
27
31
Q.Are you sponsoring any Exhibits with your pre-
28 filed testimony?
29 A.Yes. I am sponsoring Exhibit No. 13 composed of
30 six schedules as follows: Schedule 1, retail revenue credit
Knox, Di 2
Avista Corporation
1 rate calculation; Schedule 2, electric cost of service
2 study process description; Schedule 3, electric cost of
3 service study summary results; Schedule 4, load research
4 study report; Schedule 5, natural gas cost of service study
5 process description; and Schedule 6, natural gas cost of
6 service summary results.
7 Q.Were these exhibits prepared by you or under your
8 direction?
9
10
11
12
A.Yes, they were.
II . REVENU NOmmIZATION
Electric Revenue Normlization
Q.Would you please describe the electric revenue
13 adjustmnt included in Comany witness Ms. Andrews pro
14 form results of operations?
15 A.Yes.The electric revenue normalization
16 adjustment represents the difference between the Company's
17 actual recorded retail revenues during the twelve months
18 ended December 2009 test period and retail revenues on a
19 normalized (pro forma)basis.The total revenue
20 normalization adjustment increases Idaho net operating
21 income by $3,620,000, as shown in column (z) on page 6 of
22
23
Ms. Andrews Exhibit No. 12, Schedule 1.The revenue
normalization adjustment consists of three primary
24 components: 1) re-pricing customer usage (adjusted for any
25 known and measurable changes) at present base tariff rates
Knox, Di 3
Avista Corporation
1 in effect,2) adjusting customer loads and revenue to a
2 12-month calendar basis (unbilled revenue adjustment), and
3 3) weather normalizing customer usage and revenue1.
4 Q.Since these three elemnts are combined into a
5 single adjustmnt, would you please identify the imact
6 (before taxes and revenue rela ted expenses) of each
7 component?
8
9
A.Yes.The re-pricing of billed usage comprises
the majority of the change in test year revenue.The
10 combined impact of the rate increase effective August 1,
11 2009 and the elimination of revenue and amortization
12 expense from adder schedules (Schedule 59 Residential
13 Exchange, and Schedule 91 Public Purpose Tariff Rider2) is
14 an increase of $9,302, 000. Revenue from unbilled calendar
15 usage compared to the amount included in results of
operations is a reduction of $134,0003.Finally, the16
17
18
19
weather normalization adj ustment reduces revenue by
$3,497,000.The combined impact of these elements is an
increase of $5,671, 000 which,after revenue-related
20 expenses and income taxes, results in the increase to net
21 operating income of $3,620, 000.
J Documentation related to ths adjustment is detaled in the Knox workper accompanyig ths cae.
2 City Frachise Fee and Power Cost Adjustment revenues are elimate in separte adjustments.
3 The unbiled adjustment consist of removing Deember 2008 usge biled in Janua 2009 from the
2009 test year, adding December 2009 usge biled in Janua 2010 to the 2009 test year, and re-pricing
the net adjustment to usage at the base rates presently in effect.
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Avista Corporation
1 Q.Would you please briefly discuss electric weather
2 normlization?
3 A.Yes.The Company's weather normalization
4 adjustment calculates the change in kWh usage required to
5 adjust actual loads during the twelve months ended December
6 2009 test period to the amount expected if weather had been
7 normal.This adjustment incorporates the effect of both
8 heating and cooling on weather-sensi ti ve customer groups.
9 The weather adjustment is developed from regression
10 analysis of five years of billed usage per customer and
11 billing period heating and cooling degree-day data.The
12 resulting seasonal weather sensitivity factors (use-per-
13 customer-per-heating degree-day and use-per-customer-per-
14 cooling degree-day) are applied to monthly test period
15 customers and the difference between normal heating/cooling
16 degree-days and monthly test period observed
17 heating/cooling degree-days.
18 Q.Have the seasonal weather sensitivity factors
19 been uPdted since the last rate case?
20 A.No.Regression analysis was performed on 2004
21 through 2008 billing data which resulted in higher
22 sensitivity factors.Use of these higher sensi ti vi ty
23 factors would have resulted in a greater reduction in usage
24 which in turn would have increased the current rate
25 request.In an effort to present a conservative estimate
Knox, Di 5. Avista Corporation
1 of the impact of abnormal weather during 2009 (beneficial
2 to customers), the Company elected to stay wi th the
3 previous factors.
4 Q.What data did you use to determne "norml"
5 heating and cooling degree days?
6 A.Normal heating and cooling degree-days are based
7 on a rolling 30-year average of heating and cooling degree-
8 days reported for each month by the National Weather
9 Service for the Spokane Airport weather station. Each year
10 the normal values are adjusted to capture the most recent
11 year with the oldest year dropping off, thereby reflecting
12 the most recent information available at the end of each
13 calendar year.
14 Q.Is this proposed weather adjustmnt methodology
15 consistent with the methodology utilized in the Company's
16 last general rate case in Idaho?
17
18
A. Yes.
Q.What was the imact of electric weather
19 normlization on the twelve months ended Decemer 2009 test
20 year?
21 A.Weather was colder than normal during the winter
22 and spring, and warmer than normal during the summer of
23 2009.The adjustment to normal required the deduction of
24 430 heating degree-days during the heating season4 and 155
4 The heatig season includes the month of Janua though June and October though Deceber.
Knox, Di 6
Avista Corporation
1 cooling degree-days.The total adjustment to Idaho sales
2 volumes was a reduction of 44,832,283 kWhs which is
3 approximately 1.3 percent of billed usage.
4 Natural Gas Revenue Normlization
5 Q.Would you please describe the natural gas revenue
6 adjustmnt included in Ms. Andrews pro form results of
7 operations?
8 A.Yes.The natural gas revenue normalization
9 adjustment is similar to the electric adjustment and
10 represents the difference bètween the Company's actual
11 recorded retail revenues during the twelve months ended
12 December 2009 test period and retail revenues on a
13 normalized (pro forma) basis. The adjustment includes the
14 re-pricing of pro forma sales and transportation volumes at
15 present rates (effective November 1, 2009) using pro forma
16 sales volumes that have been adjusted for unbilled sales,
17 abnormal weather, and any material customer load or
18 schedule changes.The rates used exclude:1) Temporary
19 Gas Rate Adjustment Schedule 155, which reflects the
20 approved amortization rate for deferred gas costs approved
21 in the Company's last PGA filing and 2) Public Purposes
22 Rider Adjustment Schedule 1915.
23 Q.Does the Revenue Normlization Adjustmnt contain
24 a component reflecting normlized gas costs?
S Documentation related to this adjustment is detailed in the Knox workpapers accompanying ths case.
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Avista Corporation
1 A.Yes. Purchase gas costs are normalized using the
2 gas costs approved by the Commission in Case No. AVU-G-09-
3 as, the Company's 2009 PGA filing, as set forth under
4 Schedule 150. Those gas costs are then applied to the pro
5 forma retail sales volumes so that there is a matching of
6 revenues and gas costs.
7 The total net amount of the natural gas revenue
8 normalization, which includes the purchase gas cost
9 adjustment, is a decrease to net operating income of
10 $537,000, as shown in column (h), page 6 of Ms. Andrews
11 Exhibi t No. 12, Schedule 2.
12 Q.Would you please briefly discuss natural gas
13 weather normlization?
14 A.Yes.The natural gas weather adjustment is
15 developed from a regression analysis of ten years of billed
16 usage-per-customer and billing period heating degree-day
17 data.The resulting seasonal weather sensitivity factors
18 (use-per-customer-per-heating degree-day) are applied to
19 monthly test period customers and the difference between
20 normal heating degree-days and monthly test period observed
21 heating degree-days. This calculation produces the change
22 in therm usage required to adjust existing loads to the
23 amount expected if weather had been normal.
24 Q.In your discussion of electric weather
25 normlization you indicated that the adjustmnt utilized
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Avista Corporation
1 sensitivity factors from the last case.Is this true for
2 natural gas as well?
3 A.Yes. Once again, in an effort to present a more
4 conservative reduction to usage due to abnormal weather,
5 the factors from the last case were used instead of updated
6 factors which indicated slightly higher sensi ti vi ty.
7 Q.What data did you use to determne "norml"
8 hea ting degree days?
9 A.Normal heating degree-days are based on a rolling
10 30-year average of heating degree-days reported for each
11 month by the National Weather Service for the Spokane
12 Airport weather station.Each year the normal values are
13 adjusted to capture the most recent year with the oldest
14 data dropping off, thereby reflecting the most recent
15 information available at the end of each calendar year.
16 Q.Is the proposed weather adjustmnt methodology
17 consistent with the methodology utilized in the Comany's
18 last general rate case in Idaho?
19 A. Yes.The process for determining the weather
20 sensitivity factors and the monthly adjustment calculation
21 are consistent with the methodology presented in Case No.
22 AVU-G-09-01.
23 Q.What was the imact of natural gas weather
24 normlization on the twelve months ended Decemer 2009 test
25 year?
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Avista Corporation
1
2
A.Weather was colder than normal during the 2009
winter and spring months.The adjustment to normal
3 required the deduction of 430 heating degree-days from
4 January through June and October through December. 6 The
5 adjustment to sales volumes was a reduction of 3,762,074
6 therms which is approximately three percent of billed
7 usage.The margin impact (revenue less gas cost) of the
8 weather adjustment was a reduction of $1,187,000.
9 III. PROPOSED ELECTRIC RETAIL RENU CREIT RATE
10 Q. Company witness Mr. Johnson indicates that the
11 retail revenue credit rate to be used in the Power Cost
12 Adjustmnt (PCA) represents the average cost of production
13 and transmission in this filing.How is that rate
14 determned?
15
16
A.. The retail revenue credit rate is determined by
computing the proposed revenue requirement on the
17 production and transmission costs contained within Ms.
18 Andrews'Idaho electric pro forma total results of
19 operations. The production/transmission revenue requirement
20 amount is then divided by the Idaho normalized retail load
21 used to set rates in order to arrive at the average
22 production and transmission cost-per-kWh embedded in
23 proposed rates.
6 Warer than normal weather tht occurd durng July though September did not imact the natu gas
weather normlization adjustment as the seasonal sensitivity factor is zero for sumer month.
Knox, Di 10
Avista Corporation
1 Q. Do you have an exhibit that shows the calculation
2 of the proposed retail revenue credit rate?
3 A. Yes.Exhibit No. 13, Schedule 1 begins with the
4 identification of the production and transmission revenue,
5 expense and rate base amounts included in each of Ms.
6 Andrews actual, restating, and pro forma adjustments to
7 resul ts of operations. The "Pro Forma Total" at the bottom
8 of page 1 shows the resulting production and transmission
9 cost components.
10 Page 2 shows the revenue requirement calculation on
11 the production and transmission cost components. The rate
12 of return and debt cost percentages on line 2 are inputs
13 from the proposed cost of capital.The normalized retail
14 load on Line 10 comes from the workpapers to the revenue
15 normalization adjustment.The proposed retail revenue
16 credit rate is shown on Line 11 and represents the average
17 production and transmission cost-per-kWh proposed to be
18 embedded in Idaho customer retail rates.
19 The proposed retail revenue credit rate is $0.05026
20 per kWh or $50.26 per mWh. The calculation of the retail
21 revenue credit rate will be revised based on the final
22 production and transmission costs and rate of return that
23 are approved by the Commission in this case.
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Avista Corporation
1
2
iv. ELECTRIC COST OF SERVICE
Q.Please briefly sumrize your testimny related
3 to the electric cost of service study.
4 A.I believe the Base Case cost of service study
5 presented in this case is a fair representation of the
6 costs to serve each customer group. The Base Case study
7 shows Residential Service Schedule 1, Extra Large General
8 Service Schedule 25 and 25P, and pumping Service Schedule
9 31 provide less than the overall rate of return under
10 present rates. General Service Schedule 11, Large General
11 Service Schedule 21 and Street and Area Lighting Service
12 provide more than the overall rate of return under present
13 rates.
14 Q.What is an electric cost of service study and
15 what is its purpose?
16 A.An electric cost of service study is an
17 engineering-economic study, which separates the revenue,
18 expenses, and rate base associated with providing electric
19 service to designated groups of customers. The groups are
20 made up of customers with similar load characteristics and
21 facilities requirements. Costs are assigned in relation to
22 each group's characteristics, resulting in an evaluation of
23 the cost of the service provided to each group.The rate
24 of return by customer group indicates whether the revenue
25 provided by the customers in each group recovers the cost
Knox, Di 12
Avista Corporation
3 groups of customers.Exhibi t No. 13, Schedule 2 explains
4 the basic concepts involved in performing an electric cost
5 of service study. It also details the specific methodology
6 and assumptions utilized in the Company's Base Case cost of
7 service study.
8 Q.What is the basis for the electric cost of
9 service study provided in this case?
10 A.The electric cost of service study provided by
11. the Company as Exhibit No. 13, Schedule 3 is based on the
12 twelve months ended December 2009 test year pro forma
13 results of operations presented by Company witness Ms.
14 Andrews in Exhibit No. 12, Schedule 1.
15 Q.Would you please explain the cost of service
16 study presented in Exhibit No. l3, Schedule 3?
17 A.Yes. Exhibit No. 13, Schedule 3 is composed of a
18 series of summaries of the cost of service study results.
19 The summary on page 1 shows the results of the study by
20 FERC account category. The rate of return by rate schedule
21 and the ratio of each schedule's return to the overall
22 return are shown on Lines 39 and. 40.This summary was
23 provided to Mr. Ehrbar for his work on rate spread and rate
24 design. The results will be discussed in more detail later
25 in my testimony.
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Avista Corporation
1 Pages 2 and 3 are both summaries that show the
2 revenue-to-cost relationship at current and proposed
3 revenue. Costs by category are shown first at the existing
4 schedule returns (revenue); next the costs are shown as if
5 all schedules were providing equal recovery (cost). These
6 comparisons show how far current and proposed rates are
7 from rates that would be in alignment with the cost study.
8 Page 2 shows the costs segregated into production,
9
10
transmission,distribution,and common functional
categories.Page 3 segregates the costs into demand,
11 energy, and customer classifications. Page 4 is a summary
12 identifying specific customer related costs embedded in the
13 study.
14 The Excel model used to calculate the cost of service
15 and supporting' schedules has been included in its entirety
16 both electronically and hard copy in the workpapers
17 accompanying this case.
18 Q.Does the Company's electric Base Case cost of
19 '. service study follow the methodology accepted in the
20 Company's last electric general rate case in Idaho?
21 A.Only in part.The methodology applied to
22 distribution and administrative and general costs has not
23 changed from the methodology accepted by the Idaho
24 Commission in Case No. AVU-E-04-01 and subsequently
25 presented in AVU-E-08-01 and AVU-E-09-01.However, the
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Avista Corporation
1 Company is proposing a revision to the peak credit
2 classification for production costs and a change to the
3 methodology applied to transmission costs in this case.
4
5
Q.With respect to the components that have not
changed (given that the specific details of this
6 methodology are described in Exhibit No. 13, Schedule 2),
7 would you please give a brief overview of the key elemnts
8 and the history associated with those elemnts?
9 A.Yes.Distribution costs are classified and
10 allocated by the basic customer theory7 accepted by the
11 Idaho commission in Case No. WWP-E-98-11.Additional
12 direct assignment of demand related distribution plant has
13 been incorporated to reflect improvements accepted by the
14 Commission in Case No. AVU-E-04-01.
15 Administrative and general costs are first directly
16 assigned to production, transmission, distribution, or
17 customer relations functions. The remaining administrative
18 and general costs are categorized as common costs and have
19 been assigned to customer classes by the four-factor
20 allocator accepted by the Idaho Commission in Case No. AVU-
21 E-04-01.
22 Q.Moving on to comonents of the study that have
23 changed, let's start with production costs.You said the
7 Basic customer theory classifies only meters, serces and the direct assignent of strt light fixtues as eustome-
related plant; all other distrbution failties are considered demad-related.
Knox, Di 15
Avista Corporation
1 Company is proposing a revision to the peak credi t
2 classification for production cost. Please explain.
3
4
A.In addition to preparing a new load study, the
Company also decided to examine the operating
5 characteristics, and associated costs, o£ its electric
6 system resources in conjunction with the allocation of
7 costs wi thin its cost of service study.Traditionally,
8 both production and transmission costs have been classified
9 into energy-related and demand-related components by the
10 peak credit ratio method.Therefore the "peak credit"
11 classification methodology was evaluated to determine
12 whether it was appropriate to make any changes, given our
13 current electric system characteristics.
14 Q.How was the prior peak credi t methodology
15 determned and applied?
16 A.In the Company's prior cost of service studies,
17 Avista's electric system resource costs were classified to
18 energy and demand using a comparison of the replacement
19 cost-per-kW of the Company's peaking units, to the
20 replacement cost-per-kW of the Company's thermal and hydro
21 plants (separately).This analysis created separate peak
22 credi t ratios applied to thermal plant and hydro plant.
23 Transmission costs were assigned to energy and demand by a
24 50/50 weighting of the thermal and hydro peak credit
25 ratios. Fuel and load dispatching expenses were classified
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Avista Corporation
1 entirely to energy, and peaking plant related costs were
2 classified entirely to demand.
3 Q.Wha t is the Company proposing with regard to the
4 peak credit methodology and how was it developed?
5 A.Energy Resources Department personnel were
6 enlisted to examine the issue. The result of their analysis
7 is reflected in Company witness Mr. Kalich's recommended
8 revised peak credit classification ratio of 38.1% applied
9 uniformly to all production costs.As explained by Mr.
10 Kalich, the peak credit ratio (the proportion of total
11 production cost that is capacity-related) is determined
12 using the operational model of the incremental capacity
13 resource detailed in the Company's latest Integrated
14 Resource Plan.The ratio of the costs remaining after
15 dispatch into the wholesale marketplace relative to the
16 entire cost of the incremental resource is the share of
17 production costs' attributable to demand.
18 Q.What is the net effect of the proposed change in
19 the peak credit method?
20 A.The net effect of this change is to increase the
21 overall production costs that are classified as demand-
22 related.Using the prior method, approximately 26% of
23 total production costs were classified as demand-related,
24 compared to 38.1% under the revised method.Thj,s change
25 shifts costs away from high load factor customer groups as
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Avista Corporation
1 well as customer groups which have a limited contribution
2 to system peak usage (pumping and street lighting).
3 Q.Moving on to transmission, you mentioned the
4 Company is proposing "a change to the methodology applied
5 to transmission costs". What are you changing and why?
6 A.The proposed method applied in the Base Case cost
7 of service study incorporates changes to both the
8 classification and allocation of transmission costs. These
9 changes resulted from examining the issues raised by the
10 intervening parties in Case No. AVU-E-09-01.In fact, as
11 part of the Settlement Agreement in Case No. AVU-E-09-01,
12 the Company agreed to the following:
13 As part of its next general rate case (GRC), the14 Company will prepare an analysis of the impacts of15 allocating 100% of transmission costs to demand, as16 well as allocating transmission costs to reflect any17 peak and off-peak seasonal cost differences over18 seven months, rather than assuming an equal19 weighting over twelve months. (page 11).
20 Q.How did you change the classification of
21 transmission costs?
22 A.Historically, Avista has included transmission
23 costs in the production peak credit classification. It has
24 been done this way largely because it is the accepted
25 process in Washington, even though, as the interveners
26 pointed out, 100% demand is the more universally accepted
27 classification of transmission costs in other states
28 (including the other investor-owned utilities in Idaho).
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Avista Corporation
1 In the Base Case cost of service study in this case, all
2 transmission costs have been classified as demand-related.
3 Q.Did you make any further changes to the
4 allocation of transmission costs?
5 A.Yes.In prior studies,demand-related
6 transmission costs have been allocated to customer groups
7 by their contributions to the average of the twelve monthly
8 system coincident peaks.In this study, only the system
9 coincident peaks occurring in 4 winter months and 3 summer
10 months were included in the average. The rationale behind
11 this allocation is that the lower customer demands in the
12 off-peak fall and spring seasons do not impose the same
13 capacity utilization of the transmission facilities as the
14 high demand winter and summer seasons.
15 Q.The Settlemnt Agreemnt only required the
16 Company to prepare an analysis of the imact of these two
17 issues. Why did you include them in the Base Case cost of
18 service study?
19
20
A.There are reasonable arguments supporting both of
these changes, some of which are identified above.In
21 addition, these changes reduce cost allocation to high load
22 factor customers.Since the last test year, we have seen
23 the number of Schedule 25 Extra Large General Service
24 customers reduced by one-third, as the forest industry in
25 particular continues to experience financial difficulties.
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Avista Corporation
1 Choosing acceptable methodologies that can legitimately
2 reduce cost pressure for this group of customers represents
3 a conscious effort to help keep this segment in business.
4 Q.What are the results of the Company's Base Case
5 cost of service study?
6 A.The following table shows the rate of return and
7 the relationship of the customer class return to the
8 overall return (relative return ratio) at present rates for
9 each rate schedule:
10 Illustration 1 :
Customer Class Rate of Return Return Ratio
Residential Service Schedule 1 4.060/0 0.78
General Service Schedule 11 8.68%1.67
Large General Service Schedule 21 6.47%1.25
Extra Large General Service Schedule 25 2.72%0.53
Ex. Lg. Gen. Svc. Clearwater Paper Schedule 25P 4.47%0.86
Pumping Service Schedule 31 4.55%0.88
Lighting Service Schedules 41 . 49 6.30%1.21
Total Idaho Electric System 5.19%1J
11 As can be observed from the above table, residential,
12 extra large general service, and pumping service schedules
13 (1, 25, 25P, and 31) show under-recovery of the costs to
14 serve them, while the general, large general, and lighting
15 service schedules (11, 21, and 41 - 49) show over-recovery
16 of the costs to serve them.The summary results of this
Knox, Di 20
Avista Corporation
1 study were provided to Mr. Ehrbar as an input into
2 development of the proposed rates.
3 Q.Can you illustrate how the changes to the
4 methodology applied to production and transmission costs
5 impacted the cost of service study results?
6 A.Yes.The following table contains the
7 progression in the relative return ratio from the model run
8 of the study using the prior method to the proposed Base
9 Case method.
10 Illustration 2:
Step 2 Base Case
Step 1 Revised Peak Credit Revised Peak Credit
Prior Revised and Transmission Transmission 100%
Customer Class Method Peak Credit 100% Demand Demand & 7CP
Schedule 1 0.87 0.83 0.80 0.78
Schedule 11 1.72 1.70 1.67 1.67
Schedule 21 1.25 1.24 1.24 1.25
Schedule 25 0.46 0.49 0.51 0.53
Schedule 25P 0.59 0.74 0.83 0.86
Schedule 31 0.79 0.83 0.85 0.88
Schedules 41-49 1.12 1.17 1.21 1.21
Total Idaho .1 1.00 1i 1i
11 This illustration shows the impact of each incremental
12 change to the electric cost of service methodology.
13 Demnd Study
14 Q.An issue was raised in Case No. AW-E-08-01
15 regarding the load data used to develop demnd allocations
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Avista Corporation
1 in the electric cost of service. Please elaborate on this
2 issue.
3 A.In the Company's 2008 general rate case, the
4 Company indicated that, while the estimation process used
5 to create the demand allocators in the cost of service
6 study provides a reasonable assignment of cost to the
7 existing customer groups, the Company's load data was in
8 the process of being updated. Accordingly, the Commission
9 provided the following directive on page 13 of its Order
10 No. 30647:
11 In this case the Commission finds the Company-filed12 cost of service study to be sufficient to determine13 rate design in this case. We direct the Company in
14 its next general rate case to provide updated load15 data as part of its COS study or, in the16 alternative, show how the lack of such an update
17 affects COS-based revenue allocations to customer18 classes.
19
20 Q.How was this issue treated in the Company's 2009
21 general rate case?
22 A.The load study was in progress during the
23 pendency of Case No. AVU-E-09-01. Even though the Company
24 presented sensitivity analysis to illustrate the potential
25 impact of updated load information on cost of service based
26 revenue allocations, the parties ultimately agreed to
27 spread the increase in electric base revenue on a uniform
28 percentage basis.The Company also agreed as part of the
29 approved settlement to share the results of the load study
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Avista Corporation
1 as soon as it became available. This contingency was meant
2 to assure the parties that if another case had been filed
3 before the load study had been completed, the results could
4 be considered during the case as soon as they did become
5 available.
6 Q.Has Avista incorporated current load research
7 into the cost-of-service study presented for this case?
8
9
A.Yes. The Company designed and implemented a load
research study in 2009.The results of that study were
10 applied wi thin the Company's cost-of-service study.
11 Q.How does the load research influence the cost-of-
12 service study?
13 A.Many of the components of a cost-of-service study
14 are distributed among the various rate classes based upon
15 the energy use and demand of that customer class during
16 different time periods.A load research study is a
17 measurement of a statistically valid sample of each
18 customer class used to estimate how that customer class
19 contributes to the overall system load.Those
20 contributions then become part of the cost-of-service
21 study.
22
23
Q.How was this load study performd?
A.In 2008, Avista reviewed the tasks necessary for
24 the design and implementation of a long-term load research
25 study that would deliver usable results based upon one full
Knox, Di 23
Avista Corporation
1 year of data.The goal was to have this study ready for
2 regulatory proceedings no later than the Spring of 2010.
3 The requirement of randomly selecting customers for
4 participation in the study and the diverse and often low-
S density nature of much of our service territory demanded a
6 high-quali ty and reliable metering and communication system
7 to support a long-term study. The Company retained a load
8 research consulting specialist to design the sample to
9 deliver statistically valid results.
10 Avista interviewed four consulting firms.Based on
11 these interviews and other due diligence, the Company
12 engaged the services of Mr. Curt Puckett of KEMA (formerly
13 known as RLW Analytics) to provide planning, sample design
14 and selection, as well as analysis and reporting associated
15 with Avista's Load Research Project.KEMA is a respected
16 consulting firm specializing in electric utility load
17 research.
18
19
Q.How many customers were selected for the project?
A.In total, 629 Avista customers were included in
20 the overall sample. This included 225 customers within the
21 Company's Idaho service terri tory.The remaining 404
22 customers were in the Company's Washington service
23. terri tory.
24 Q.How were external stakeholders involved in this
25 process?
Knox, Di 24
Avista Corporation
1 A.The Company's load research team (consisting of
2 Jon Powell, Jon Seubert, and myself) as well as Mr. Puckett
3 of KEMA met with Commission Staff May 21, 2008 in Boise.
4 The Company presented the initial plan for the study and
5 requested input from the parties before finalizing the plan
6 and commencing implementation of the project.A project
7 update was also sent on October 31, 2008 to mark the
8 installation of the first of the sample meters.Finally,
9 periodic updates were presented to the Company's External
10 Energy Efficiency Board (Triple-E).
11 Since that time, Avista has been collecting the data
12 from the meters and forwarding the resulting meter reads to
13 KEMA for their analysis. On March 16, 2010, KEMA delivered
14 to Avista the final load research studyB.The load
15 research study report is attached as Exhibit No. 13,
16 Schedule 5 and the supporting electronic files have been
17 included in the accompanying workpapers.
18 Q.Were the stakeholders made aware of the key
19 elements of the load research study?
20 A.Yes.Stakeholders were informed of the issues
21 involved in choice of technology, sample selection and the
22 timetable for the completion of the installation and
23 eval ua tion .
8 Key resut tables were provided in lat Febru to failtate incorporation of the load study resuts in the
presented cost of serce analysis, however the complete load stdy report was not delivered until March.
Knox, Di 25
Avista Corporation
1 Q.Did the resul ts from the new load study cause
2 major changes in the allocation of demnd-related costs in
3 the cost of service study in this case, as compared to
4 prior cost of service studies?
5 A.No. Using the prior case method cost of service
6 run (for an apples to apples comparison), the demand
7 contributions produced by the load study increased the
8 relative costs assigned to pumping service and reduced the
9 costs assigned to lighting service.Otherwise, the over-
10 and under-recovery relationships are similar to studies
11 from prior cases.
12 Q.Is the cost-of-service study the only anticipated
13 use of the load research study?
14 A.No.We have found additional use of the load
15 research in improving transformer dèsign and potentially in
16 the design and implementation of Smart Grid technologies.
17 We are also contemplating the future use of this data to
18 develop end-use load profiles.
19 Q.How will Avista maintain the study in the future?
20 A.It is Avista's intent to annually augment the
21 existing customer sample with additional, randomly-selected
22 participants,beginning in 2011.These addi tional
23 installations will ensure that the study sample continues
24 to be representative of the population as a whole.The
25 additional samples will be selected to maximize statistical
Knox, Di 26
Avista Corporation
1 precision of the rate classes and to serve the needs of
2 evaluating future alternative rate designs and engineering
3 topics that arise over time.
4
5
V. NATUR GA COST OF SERVICE
Q.Please describe the natural gas cost of service
6 study and its purpose.
7 A.A natural gas cost of service study is an
8 engineering-economic study which separates the revenue,
9 expenses, and rate base associated with providing natural
10 gas service to designated groups of customers. The groups
11 are made up of customers with similar usage characteristics
12 and facility requirements. Costs are assigned in relation
13 to each groups' characteristics, resulting in an evaluation
14 of the cost of the service provided to each group.The
15 rate of return by customer group indicates whether the
16 revenue provided by the customers in each group recovers
17 the cost to serve those customers. The study results are
18 used as a guide in determining the appropriate rate spread
19 among the groups of customers.Exhibit No.13, Schedule 5
20 explains the basic concepts involved in performing a
21 natural gas cost of service study.It also details the
22 specific methodology and assumptions utilized in the
23 Company's Base Case cost of service study.
24 Q.What is the basis for the natural gas cost of
25 service study provided in this case?
Knox, Di 27
Avista Corporation
1 A.The cost of service study provided by the Company
2 as Exhibit No. 13, Schedule 6 is based on the twelve months
3 ended December 2009 test year pro forma results of
4 operations presented by Ms. Andrews in Exhibit No. 12,
5 Schedule 2.
6 Q.Would you please explain the cost of service
7 study presented in Exhibit No. 13, Schedule 6?
8 A.Yes. Exhibit No. 13, Schedule 6 is composed of a
9 series of summaries of the cost of service study results.
10 Page 1 shows the results of the study by FERC account
11 category.The rate of return and the ratio of each
12 schedule's return to the overall return are shown on lines
13 38 and 39. This summary is provided to Mr. Ehrbar for his
14 work on rate spread and rate design. The results will be
15 discussed in more detail later in my testimony. Additional
16 summaries show the costs organized by functional category
17 (page 2) and classification (page 3), including margin and
18 unit cost analysis at current and proposed rates. Finally,
19 page 4 is a summary identifying specific customer related
20 costs embedded in the study.
21 The' Excel model used to calculate the cost of service
22 and supporting schedules has been included in its entirety
23 both electronically and hard copy in the workpapers
24 accompanying this case.
Knox, Di 28
Avista Corporation
1 Q.Does the Natural Gas Base Case cost of service
2 study utilize the methodology from the Company's last
3 natural gas case in Idaho?
4 A.Yes.The Base Case cost of service study was
5 prepared using the methodology accepted by the Idaho
6 Commission in Case No. AVU-G-04-01, AVU-G-08-01 and AVU-G~
7 09-01.
8 Q.What are the key elemnts that define the cost of
9 service methodology?
10
11
A.Purchased gas costs are derived from the current
purchased gas tracker methodology.Underground storage
12 costs are allocated by normalized winter throughput.
13 Natural gas main investment has been segregated into large
14 and small mains.Large usage customers that take service
15 from large mains do not receive an allocation of small
16 mains.Meter installation and services investment is
17 allocated by number of customers weighted by the relative
18 current cost of those items. System facilities that serve
19 all customers are classified by the peak and average ratio
20 that reflects the system load factor, then allocated by
21 coincident peak demand and throughput,respectively.
22 Demand side management costs are treated in the same way as
23 system facilities.General plant is allocated by the sum
24 of all other plant. Administrative & general expenses are
25 segregated into labor-related, plant-related, revenue-
Knox, Di 29
Avista Corporation
1 related, and "other".The costs are then allocated by
2 factors associated with labor, plant in service, or
3 revenue , respectively.The "other" A&G amounts get a
4 combined allocation that is one-half based on O&M expenses
5 and one-half based on throughput.A detailed description
6 of the methodology is included in Exhibit No. 13, Schedule
7 5.
8 Q.What are the results of the Comany's natural gas
9 . cost of service study?
10 A.I believe the Base Case cost of service study
11 presented in this filing is a fair representation of the
12 costs to serve each customer group.The study indicates
13 that Residential service Schedule 101 is providing slightly
14 less than the overall return (unity), while all other
15 schedules are providing slightly more than unity to varying
16 degrees.The return for all of the Schedules are
17 relatively close to the overall return indicating the
18 current rate spread is fair.
19 The following table shows the rate of return and the
20 relative return ratio at present rates for each rate
21 schedule:
22
Knox, Di 30
Avista Corporation
1 Illustration 3:
Customer Class
Residential Service Schedule 101
Large Firm Service Schedule 111
Interruptible Service Schedule 131
Transportation Service Schedule 146
Total Idaho Natural Gas System
Rate of Return
6.57%
8.65%
7.51%
8.83%
U3cr
Return Ratio
0.95
1.25
1.08
1.27
1J
2
3
4
5
6
The summary results of this study were provided to Mr.
Ehrbar as an input into development of the proposed rates.
Q. Does this conclude your pre-filed direct
testimony?
A. Yes.
Knox, Di 31
Avista Corporation
DAVID J. MEYER
VICE PRESIDEN AN CHIEF COUNSEL OF
REGULATORY & GOVERNTAL AFFAIRS
AVISTA CORPORATION
P.O. BOX 3727
1411 EAST MISSION AVE
SPOKA, WASHINGTON 99220-3727
TELEPHONE: [phone]
FACSIMILE: [phone]
DAVID. MEYER~AVISTACORP. COM
BEPORE THE :IDAO PUL:IC UT:IL:ITIES COII:ISS:ION
IN THE MATTER OF THE APPLICATION
OF AVISTA CORPORATION FOR THE
AUTHORITY TO INCREASE ITS RATES
AN CHAGES FOR ELECTRIC AN
NATUR GAS SERVICE TO ELECTRIC
AN NATU GAS CUSTOMERS IN THE
STATE OF IDAHO
CASE NO. AVU-E-10-01
CASE NO. AVU-G-10-01
EXHIBIT NO. 13
TAR L. KNOX
FOR AVISTA CORPORATION
(ELECTRIC AN GAS)
A VITA UTIT
AVERAGE PRODUCTON ANTRASMISSION COST
IDAHO ELEC
TWLVE MONTHS ENDED DECEMBER 31. 2009
Colum Deption of Adjust
b Per Reslts Repor
c Deer FI Rate Ba
d Deer Gain on Offce Building
e Colsp 3 AF Elimnationf Colsp Coon AF
g Ketle Falls & Bouder Park Dillow.
h Cuer Advace
Weather and DSM Invesent
j Restating CDA Setlemt
k Restating CDA Setement Defer
i Resting CDAlSRR CDR
m Restating Spokane Rvr Reliceing
n Restig Spokae Rive Deeil
o Resting Spoka River PM&E Deer
p Retig Monta Le
Actul
(ooO's)
PrctonrassionReenue Exse Rate Bas
84,836 205,345 359,043
(51,323)
84,836
q Eliminate B & 0 Taxes
r Prop Taxs Uncollec. Exp
t Reguato Exp
u Injures and Damges
v FIT
w IdaoPCA
x Nez Perce Setlemt Adjustment
y Elimte AI Expen
z Revue Norizon Adjusent
aa Mise Reting Adjs
ab Colstrp Merur Emiss. O&M
ac Restating CS2 Leeli Adj
ad Restatig Warila Amortzation
ae Restatig Colsp Lawst Stlnt
af Reting CCX
ag O&M Saving
ah Worg Capita
ai Restae Debt Intet
Rested Total
59
193 1,700
903
(2,034)
307
101
756
118
19
156
44
207,039
776
465
(15)
2,400
481
221
108
154
425
(83)
294
(17)
168
40
(459)
32
253
1,289
310,249
84,895
PFI Pr Fon Power Suply
PF2 Pr Fon Pruction Prop Adj
PF3 Pr Fon Laor Non-Exec
PF4 Pr Fon Labor Exec
PF5 Pro Fon Tramission Rev/Exp
PF6 Pr Fon Caital Add 200
PF7 Pro Form Caital Ad 2010
PF8 Pro Fon Noxon Ge 2010 & 201 1
PF9 Pr Fon Inforion Serces
PFI0 Pr Fon Employee Beefits
PFI i Pr Form Insuance
PF12 Pro Form Clak ForSpokane ReI PM&E
Pro Fon Total
(61,099)
(774)
1,036
24,058
211,971
(50,780)
(4,505)
324
1
94
130
558
201
2
(204)
1,089
158.81
310,249
318,259
(4,853)
7.824
677
4,362
exibit No. 13
Case No. AVU-E-1G-1
T. Knox, Avls
Schedule 1, p. 1 of 2
A VITA UTIT
AVERAGE PRODUcnON AND TRSMISSION COST
IDAHO ELECC
TWELVE MONTHS ENDED DECEMBER 31. 2009
Pred Proon and Traion Revenue Reuireent
Caculaon of Reil Revenue Cret Rae at Prop Ret
Line ($O's)Debt Co
1 Prras Pr For Ra Bas 5318,259
2 Pr Rate of Ret 8.550%3. 1 OOA.
3 Rate Bas Net Optig Incoe Reent 527,211
4 Tax Effec Net Oping Incoe Requient (53,453)
(Rte Bas x Det Cost x -35%)
5 Net Expese Net Operg Income Requirement 134,823
(Expense - Revenue)
6 Tax Effec Net Opting Inco Requiement ($47,188)
(Net Exp x -.35%)
7 Total Proras Net Opng Inco Requiement 511 1,393
8 I -Tax Rate Coverion Facto (Excl. Rev. ReI. Ex.)0.65
9 Prodra Revenue Requirent 517,3741
10 ID Tes Yea Nómli Retl Lo MW 3,409,476
11 Prodran Rev Reqirent per kWh (Retal Revenue Creit Rate)IS 0.50:261
Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Scedule 1, p. 2 of 2
1. ELECTRC COST OF SERVICE
2 A cost of service study is an engineenng-economic study, which apportons the revenue,
3 expenses, and rate base associated with providing electrc servce to designated groups of
4 customers. It indicates whether the revenue provided by the customers recovers the cost to sere
5 those customers. The study results are used as a guide in detering the appropnate rate spread
6 among the groups of customers.
7 There are thee basic steps involved in a cost of service study: fuctionalization,
8 classification, and allocation. See flow char below.
9 First, the expenses and rate base associated with the electrc system under study are
10 assigned to fuctional categones. The unifonn system of accounts provides the basic segregation
1 I into production, transmission, and distrbution. Traditionally customer accountig, customer
12 infonnation, and sales expenses are included in the distrbution fuction and adinistrative and
13 general expenses and generl plant rate base are allocated to all fuctions. In this study I have
14 created a separate fuctional category for common costs. Administrtive and general costs that
15 canot be directly assigned to the other fuctions have been placed in this category.
16 Second, the expenses and rate base items that canot be dictly assigned to customer
17 groups are classified into three pnmar cost components: energy, demand or customer related.
18 Energy related costs are allocated based on each rate schedule's share of commodity consumption.
19 Demand (capacity) related costs are allocated to rate schedules on the basis of each schedule's
20 contrbution to peak demand. Customer related items are allocated to rate schedules based on the
21 number of customers within eah schedule. The number of cutomers may be weighte by
22 appropnate factors such as relative cost of metenng equipment. In addition to these thee cost
23 components, any revenue related expense is allocated based on the proporton of revenues by rate
24 schedule.
Exhbit No. 13
Case No. j\~-E.I0-0l
T. Knox, A vista
Schedule 2, p. 1 of 9
ELECTRIC COST OF SERVICE STUDY FLOWCHART
Functionalization/
Production Transmission
Distrbution and
Customer
Relations Common
Energy I
Commodity
Related
Residential Small Generl Ex LargeGenerl
Pumping
Pro Forma Results of Operations by Customer Group Exhibit No. 13
Case No. AVU-E-I0-01
T. Knox, Avista
Schedule 2, p. 2of9
The fmal step is allocation of the costs to the varous rate schedules utilizing the allocation
2 factors selected for each specific cost item. These factors are derived from usage and customer
3 information associated with the test period results of opertions.
4 BASE CASE COST OF SERVICE STUY
5 Producton Classifcation (peak Credit)
6 This study utilizes a Pea Credit methodology to classify production costs into demand and
7 energy classifications. The Peak Credit method acknowledges that all energy production costs
8 contain both capacity and energy components as they provide energy thoughout the year as well as
9 capacity durng system pea. The peak credit ratio (the proporton of total production cost that is
10 capacity related) is determined using the operational model of the incremental capacity resoure
11 detailed in the Company's latest Integrted Resource Plan. The ratio of the costs rema~ing after
12 dispatch into the wholesale marketplace relative to the entie cost of the incremental resource is the
13 share of production costs attbutable to demand.
14 Production Allocation
15 Production demand related costs are allocated to the customer classes by class contrbution
16 to the average of the twelve monthly system coincident peak loads. Although the Company is
17 usually techncally a witer peag utilty, it experiences high summer pea and carful
18 mangement of capacity requirements is required thoughout the year. The use of the average of
19 twëlve monthly pea recognizes that customer capacity needs are not limited to the heatig
20 seaon. Energy related costs are allocated to class by pro forma anual kilowattour sales adjusted
21 for losses to reflect generation level consumption.
22 Transmission Classifcation and Allocation
23 Transmission costs are classified as 100% demand related because the facilties are
24 constrcted primarly for meetig system peak 10ads. These costs are then allocated to the
Exhibit No. 13
Case No. AVU-E-IO-Ol
T. Knox, Avista
Schedule 2, p. 3 of9
customer classes by class contrbution to the average of the four monthy syste coincident peak
2 loads durg the winter and the thee monthly system coincident peak load durg the sumer.
3 Lower customer demands in the off-peak fall and sprig seaons do not impose the same capacity
4 utilization of the trmission facilties as the high demand witer and sumer seasons.
5 Distrbution Facilties Classification (Basic Customer)
6 The Basic Customer method considers only servces and meters and dirctly assigned
7 Street Lighting appartu (pERC Accounts 369, 370, and 373 respectively) to be customer related
8 distrbution plant. All other distrbution plant is then considered demand related. This division
9 delineates plant which benefits an individual customer from plant which is par of the syste. The
i 0 basic customer method provides a reasonable, clearly definable division between plant that
11 provides service only to individul customers from plant that is par of the interconnected
12 distrbution network.
13 Customer Relations Distrbution Cost Classifcation
14 Customer serice, customer information and sales expenes are the core of the customer
15 relations fuctiQnal unit which is included with the distrbution cost category. For the most par
16 they are classified as customer related. Exceptions are sales expenes which are classified as
17 energy related and uncollectible accounts expense which is considered separately as a revenue
18 conversion item. Demand Side Management expenses recorded in Account 908 are also
19 considered separately from the other customer information costs.
20 The demand side management investment and amortzation are classifed implicitly to
21 demand and energy by the sum of production plant in serice, then allocated to rate schedules by
22 coincident peak demand and energy consumption respectively.
23
Exhibit No. 13
Case No. AVU-E-I0-0l
T. Knox, Avist
Schedule 2, p. 4 of9
Distrbution Cost Alocation
2 Distrbution demand related costs which canot be diectly assigned are allocated to
3 customer class by the average of the twelve monthly non-coincident peak for eah class.
4 Distrbution facilties that serve only seconda voltage customers are allocated by the non-
5 coincident peak excluding primar voltage customers or number of customers excluding primar
6 voltage customers. This includes line trsformers, servces, and seconda voltage overhead or
7 underground conductors and devices. The costs of specific substations and related primar voltage
8 distrbution facilties are directly assigned to Extra Lage General Serice customers based on their
9 load ratio share of the substation capacity from which they receive servce.
10 Most customer costs are allocated by average number of customers. Weighted customer
11 allocators have been developed using tyical curent cost of meters, estimated meter reang time,
12 and direct assignent of biling costs for hand-biled customers. Street and area light customers
13 are exclude from meterig and meter readg expenses as their serice is not metered.
14 Admiistrative and General Costs
15 Administrtive and general costs which are directly associated with production,
16 transmission, distrbution, or customer relations fuctions are directly assigned to those fuctions
17 and allocated to cutomer class by the relevant plant or number of customers. The remainder of
18 adinistrative and general costs are considered common costs, and have been left in' their own
i 9 fuctional category. These common costs are classified by the implicit relationship of energy,
20 demand and customer within the four-factor allocator applied to them. The four-factor allocator
21 consists of a 25% weighting of each of the followig: 1) operating & maintenace expenses
22 excludig resource costs, labor expenses, and adinistrative and general expenses; 2) operaing
23 and maintenance labor expenses excluding adinistrtive and general labor expenses; 3) net
24 production, tranmission, and distrbution plant; and 4) number of customers.
Exhbit No. 13
Case No. AVU-E-IQ-l
T. Knox, Avist
Schedle 2, p. 5 of9
Revenue Conversion Items
2 In this study uncollectible acounts and commission fees have been classified as revenue
3 related and are allocated by pro forma revenue. These items var with revenue and are included in
4 the calculation of the revenue conversion factor. Income ta expense items are allocated to
5 schedules by net income before income ta adjusted by interest expense.
6 For the fuctional sumares on pages 2 and 3 of the cost of servce study, these items are
7 assigned to component cost categories. The revenue related expene items have been reduced to a
8 percent of all other costs and loaded onto each cost category by that ratio. Similarly, income ta
9 items have been reduced to a percent of net income before ta then assigned to cost categories by
10 relative rate base (as is net income).
11 The following matr outlines the methodology applied in the Company Base Case cost of
12 serce study.
Exhibit No. 13
Cas No. AVU-E-I0-0l
T. Knox, Avista
Schedule 2, p. 6 of 9
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SUmcst AVISTA UTILmES Ida Juriic
8cnano: Copay Ba Case Cos of Serv Ba Sury EJ Utit 0310
Re Pea Creit & Trans by Dend w 7CP For li Twe Mo End Dec 31,20
PROPOSED METDOLOGY
(b)(e) (d) (e)(I)(g)(h)(0 (j (k)G)(m)
Resentil Geera LaGe Ex La Ex La Pump strt &
Sysm Se Se Se Ge Se SerCP Serv Ar Li
Depti Totl Sc 1 8t 11.12 SC21.22 Sc25 Sc25P Sel 31.32 Sc41-49
Plant In Sece
1 Pructon Plnt 38,726,00 138,076,219 37,390,129 81,414,m 27,914,925 90,519,88 6.2,58 1,146,479
2 Transmisn Plnt 170,04,00 70,622,98 17,520,718 35,50,635 11,426,915 32,62,274 2,165,65 183,816
3 Distbuti Plat 410,44,00 206,186,645 56,987,812 99,180,942 9,287,2 2,268,27 15,50,289 21,028,80
4 Intang Plant 46,342,00 19,036,97 4,89,903 9,143,825 2,941,567 9,221,331 7'n,967 30,43
5 Genera Plt 70,516,00 37,784,547 8,873,594 11,133,1'n 2,785,53 7,43,33 1,36,061 1,143,736
6 Tot Plant In Sece 1,080,078,00 471,707,372 125,869,156 236,381,370 54,35,168 142,06,106 26,087,55 23,811,270
Ac Deati
7 Pructn Plant
(457,90)
8 Transmis Plt (62,98)
9 Dibibun Plat (9,570,391)
10 Intangibl Plant (95,04)
11 Gel Plt
12 Tota Acmulate Depti
13 Net Plan 701,82,00 30,69,34 83,576,331 154,65,349 34,901,675 89,44,183 17,3'n,333 13,165,782
14 Aculated Deferr FI (104,938,00)(45,88,00)(12,181,072)(22,nO,895)(5,317,675)(14,04,80)(2,498,108)(2,240,43)
15 Misclaneous Rate Bae 11,074,00 4,314,83 1,211,449 2,615,407 649,99 1,788,30 265,670 228,33
16 Tot Rate Base 607,96,00 267,122,176 72,60,707 134,498.861 30,233,99 n,186,88 15,159,89 11,153,68
17 Revue Fro Retal Rate 229,698,00 90,495,00 29,245,00 50,597,000 12,45,00 39,45,00 4,40,00 3,047,00
18 0l Oprating Revenue 25,572,00 9,667,45 2,582,807 5,467,241 1,765,04 5,512,029 435,n9 141,65
19 Tot Revenue 25,270,00 100,162,454 31.8,807 56,06,241 14,2,04 44,967,029 4,839,77 3,188,650
Opting Exnse
20 Pruc Exnse 128,873,00 46,502,632 12,591,819 27,415,026 9,398,786 30,470,572 2,108,613 38,553
21 Transmi Exses 9,720,00 4,03,80 1,001,46 2,02,673 65,162 1,86,575 123,789 10,507
22 Dibibuti Exse 8,62,00 4,109,043 1,097,2 1,99,914 234,221 94,21 30,111 797,290
23 Custr Acnting Expeses 4,287,00 2,99,672 63,527 276,791 114,62 193,50 54,65 17,217
24 Cutor Inforti Exse 1,30,00 58,769 142,495 22,23 76,89 249,287 19,94 3,410
25 Saes Exs 243,00 82,80 22,84 51,30 18,173 62,642 4,27 993
26 Ad & Geer Exse 22,849,00 11,928,175 2,849,229 3,n8,746 93,170 2,5,94 45,511 38,224
27 Totl O&M Exnses 175,90,00 70,239,90 18,339,619 35,m,657 11,432,031 35,45,730 3,06,88 1,597,194
28 Taxs Olr Th Inc Taxes 7,760,00 3,179,53 852,734 1,697,29 451,38 1,29,565 166,90 121,581
29 0l Inco Rel It 56,00 20,203 5,471 11,913 4,08 13,245 916 168
Deprtion Exse
30 Proucton Plt Detion 9,987,00 3,603,014 975,67 2,124,46 728,23 2,38,061 163,44 29,917
31 Transmi Plt Deprti 3,442,00 1,429,496 35,641 718,738 231,2 66,274 43,83 3,721
32 Disti Plnt Deati 10,53,00 5,207,718 1,414,120 2,ns,282 271,741 55,791 420,552 3'n,79
33 Geerl Plant Depr 6,473,00 3,46,424 814,549 1,021,96 255,698 682,525 124,84 104,989
34 Am Exse 1,314,00 476,88 128,64 279,315 95,541 30,455 21,316 3,837
35 Totl De Exns 31,754,00 14,185,54 3,687,63 6,919,m 1,582,697 4,069,107 m,99 53,259
36 Inco Tax 8.2,00 1,679,198 2,639,878 2,95,713 (73,938)68,647 143,261 232,241
37 Tot Opti Exses 223,73,00 89,30,381 25,525,33 47,35,3 13,39,255 41,517,2 4,149,94 2,46,442
38 Net Inco 31,532,00 10,85,073 6,302,475 8,705,88 823,784 3,449,73 689,8 702,20
39 Rate of Retum 5.19%4.06%8.68%6.47%2.72%4.47%4.55%6.30
40 Retm Rati 1.00 0.78 1.67 1.25 0.53 0.86 0.88 1.21
41 Inte Exse 18,847,00 8,280,86 2,250,829 4,169,50 937,263 2,392,810 469,961 34,768
Exibit No. 13
case No. AVU-E.1o-1
T. Knx, Avista
Schedule 3, p. 1 of 4
sumc AVlTA UTILITES Idah Juriic
Scar: Co Base Cas Reveue 10 Cos by Fun Coponet SUmm EI Ut 0310
Rev Peak Creft & Tras by Ded w 7CP For Ut Twelv Moth End De 31, 20
PROPOSED METODOOGY
(b)(e) (d) (e)(ij (g)(h)(~Ol (k)(0 (m)
Resientil Gener LargGe Ex Large Ex Larg Pumpg Stt &
Sysm Sø Sø Se Ge Sø SeiCP Se Ar LihtDeTotSC 1 SC 11.12 SC21.22 Sch25 SC25P SC 31-3 SC4149
Fun Co Copont at Curr Retrn by SCle
1 Pructon 140,702,33 49,472,169 15,04,524 31,04,55 9,647,433 32,79,33 2,2,79 43,527
2 Trasm 16,818,90 6,332,86 2,337,424 3,99,38 879,55 3,050,148 20,163 20,36
3 Distrbutin 42,766,82 19,423,502 7,807,82 10,68,50 839,910 552,250 1,36,40 2,09,632
4 Comm 29,40,935 15.2,465 4,059,425 4,875,56 1,088,107 3,06,26 561,63 498,473
5 Total Currt Rae Revnue 22,698,00 90,495,000 29,245,00 50,597,00 12,45,00 39,455,00 4,40,00 3,047,00
Exse as $I
6 Pructon $0.04127 $0.0429 $0.04732 $0.04 $0.03729 $0.035 $0.0385 $0.03152
7 Trasmissi $0.0093 $0.0055 $0.00735 $0.0055 $0.0034 $0.00342 $0.0034 $0.00147
8 Ditrbut $0.01254 $0.0168 $0.0245 $0.01493 $0.00325 $0.00 $0.02314 $0.15146
9 Como $0.0086 $0.01325 $0.0127 $0.0061 $0.0021 $0.00343 $0.0095 $0.03
10 Tot Curr Melded Rates $0.06737 $0.07854 $0.09200 $0.07070 $0.0414 $0.0422 $0.0740 $0.2254
Funal Cost Compo at Unnn Currnt Retrn
11 Prct 141,234,327 50,94,910 13,79,630 30,04,34 10,301,80 33,410,488 2,311,735 423,417
12 Trasmisio 17,05,05 7,08,5 1,757,342 3,561,545 1,146,129 3,271,84 217,217 18,437
13 Ditrbuti 41,914,937 21,705,248 5,769,238 9,419,878 1,072,520 56,00 1,46,131 1,916,916
14 Como 29,492,684 15,739,415 3,705,44 4,696,60 1,171,675 3,124,750 572,20 482,591
15 Totl Unifo Currt Cost 229,69,00 95,475,116 25,028,659 47,721,374 13,692,124 40,375,081 4,56,284 2,841,361
Exsse as $I
16 Pruc $0.04142 $0.0422 $0.0434 $0.04198 $0.03982 $0.03744 $0.03921 $0.03
17 Transmon $0.0050 $0.0015 $0.0053 $0.00498 $0.003 $0.007 $0.00 $0.00133
18 Ditrbu $0.0122 $0.0188 $0.01815 $0.01316 $0.0015 $0.00 $0.0248 $0.13875
19 Coon $0.00 $0.0136 $0.01166 $0.006 $0.0053 $0.00 $0.00971 $0.0393
20 Tota Currnt Unif Melded Rate $0.06737 $0.08286 $0.07874 $0.069 $0.05 $0.045 $O.0n42 $0.256
21 Reen to Co Ra at Cu Ra 1.00 0.95 1.7 1.06 0.91 0.98 0.96 1.07
Funon Co Copont at Prop Ret by SCe 46,60522Pron152,34,69 53,50,968 16,26,196 33,615,707 10,473,028 35,56,180 2,46,014
23 Trasmiss 21,96,878 8,38,679 2,907,737 5,112,393 1,215.96 4,04,754 26,976 24,372
24 Distrbuton 55,511,218 25,66,231 9.811,698 13,95,188 1.133,45 622,651 1.862,134 2,45.65
25 Como 31,99,206 16,56,122 4,407,36 5,337.712 1,193,54 3,349,215 614,876 531,36
26 Tot Prose Rate Revenue 261,812,00 104,119,00 33,390,00 58,024,00 14,016,00 43,578,00 5,21,00 3,473,00
Exse as $I
27 Pructon $0.04 $0.04 $0.05116 $0.0497 $0.04 $0.03985 $0.04181 $0.033
28 Tramis $0.00 $0.00728 $0.0015 $0.00714 $0.0070 $0.00 $0.00 $0.00176
29 Ditrbu $0.01628 $0.0228 $0.03087 $0.01950 $0.00 $0.0070 $0.03159 $0.1781
30 Co $0.0038 $0.01437 $0.01387 $0.00746 $0.001 $0.00375 . $0.01043 $0.038
31 Tota Pro Melded Ra $0.07679 $0.097 $0.105 $0.08108 $0.05418 $0.04 $0.0880 $0.25138
Funal Co Co at Unifon Reques Retrn
32 Pructon 152,814,45 55,124,679 14,927,942 32,50,713 11,146,421 36,149,34 2,501,252 45.106
33 Trasmis 22,17,m 9,210,642 2.285,05 4.631,032 1,490,27 4,254.332 282.44 23,973
34 Disb'ibutin 54,731,378 28.170,731 7,623,598 12,549,570 1,372,83 637,815 1,95,43 2,420,396
35 Comon 32,088,393 17,079,243 4,027,39 5,138,69 1,279,54 3,410.46 624,96 52,08
36 Totl Unifrm Co 261,812,00 109.58,295 28,86,98 54,826,00 15,289,09 44,451,95 5.36,09 3.430,56
Exse as $I
37 Pructon $0.04 $0.04784 $0.04 $0.042 $0.0430 $0.041 $0.04243 $0.03316
38 Transmis $0.0050 $0.00799 $0.00719 $0.00647 $0.0076 $O.OOn $0.0079 $0.00174
39 Ditrbu $0.01605 $0.02445 $0.02398 $0.01754 $0.00531 $0.0071 $0.0318 $0.17519
40 Comon $0.001 $0.0148 $0.0126 $0.00718 $0.0095 $0.00 $0.0106 $0.0322
41 Tot Unif Melde Rate $0.07679 $0.0911 $0.0980 $0.07661 $0.05910 $0.0498 $0.09100 $0.248
42 Reue to Cost Raio at Prop Raes 1.00 0.95 1.6 1.06 0.92 0.98 0.97 1.01
43 Cu Revnu to Prpo Co Ra 0.88 0.83 1.01 0.92 0.81 0.89 0.82 0.89
exhibi No. 13
case No. AVU-E-1Q.1
T. Knox. Avlsta
SCedulE 3. p. 2 of 4
Sumcst AVISTA UTLmES Idaho Juic
scario: Compay Ba Cas Revee to Co By Class Summry EIe Utli1 01.15-9
AYUE-01 Melh For th Twelv Moth Ended Sep 30, 20
(b)(e) (d) (e)(n (g)(h)(Q Q)(k)(~(m)
Resientl Genra LargeGen Ex La Ex Larg Pung St &
Sys 8e 8e 8e Ge 8e 8e Poua 8e ArUgts
Dept Tot Sc 1 Sc 11.12 Sc 21.22 SOO25 Sc25P Sc31-3 Sc 41-4
Co Classificaons at Curnt Retm by Sche
1 Ener 94.641,059 31,447,737 9,73.552 20.726,57 6.656,502 24.04,50 1.629,82 39,3
2 Ded 113.959.079 44.88.443 15,291.873 29.190.347 5.713,427 15.3.192 2.498.111 982.88
3 Cust 21.097,862 14,163.820 4,216.574 68,075 85.071 11.30 276,070 1.664,94
4 Tot Curnt Rate Reue 229,698.00 90.495.00 29.245,00 50.597.00 12.45.00 39,45.00 4.40.00 3.047.00
Ex as Unit Cost
5 En $/$0.276 $0.02729 $0.0303 $0.02896 $0.02573 $0.0295 $0.2764 $0.02891
6 Demand $l/mo $15.37 $16.2 $20.37 $16.67 $11.81 $11.56 $9.97 $21.86
7 Custor $/stmo $14.4 $11.85 $18.2 $38.90 $8.16 $92.30 $17.53 $1.128.01
Co Classificas at Unifor Curr Retum
8 Ener 95.026,54 32.381,930 8,933.769 20,06.820 7,106.46 24.496.345 1.65.928 38,292
9 Dean 113,709.88 48.138.461 12.63,178 27,05.99 6.496.373 15.867.241 2.617.100 897,54
10 Custor 20.961.56 14,95.72 3,461.712 59.559 89,287 11,495 29.25 1.555.5
11 Tola Unif Currt Cot 229,69,00 95.475,116 25.028,659 47,721,374 13,692.124 40.375.081 4,56,284 2.841,361
Exse as Unit Cot
12 En $/$0.02787 $0.02810 $0.02810 $0.0280 $0.02747 $0.02745 $0.02810 $0.02810
13 Deand $l/mo $15.34 $17.19 $16.83 $15.45 $13.42 $11.91 $10.45 $19.97
14 Custr $/st/mo $14.35 $12.51 $14.99 $3.23 $930.08 $97.88 $18.43 $1,053.88
15 Reue to Cos Ra at Cur Ra 1.00 0.95 1.17 1.06 0.91 0.98 0.96 1.07
Cost Classifcaon at Prpose Retm by SCule
16 Ener 102.451.394 34,002.99 10.525.63 22.44.649 7.224,205 26,06,148 1.76.45 422,311
17 Dend 134.842,071 53,78.519 17.90,670 34,69.722 6,701,405 17.496,707 3.097,96 1,159,08
18 Cust 24.518,53 16,327,48 4.95.693 890.629 90.390 12.145 347,587 1.891,60
19 Tola Proed Rate Revue 261.812.00 104.119.00 33.390,00 58.024,00 14.016.00 43.578,00 5,212.00 3,473.00
Ex as Unit Co
20 Ener $/Wh $0.0305 $0.02951 $0.03311 $0.03136 $0.02792 $0.02 $0.0299 $0.03057
21 Demand $l/mo $18.19 $19.20 $23.86 $19.81 $13.85 $13.13 $12.36 $25.78
22 Custo $/usmo $16.79 $13.66 $21.7 $5.94 $941.56 $1.012.10 $22.07 $1.281.57
Cost Classicaon at Unifor Requeed Retum
23 Ener 102.792.720 35.028.387 9,66,83 21,702.481 7,687.249 26.498.342 1.792.34 420.025
24 Dend 134,53,100 57,361,305 15,051,703 32.323,55 7,507.116 17.941.293 3,211.618 1.141,513
25 Custo 24,481.180 17.195.80 4.148.388 799,975 94,729 12,323 361,137 1.869.025
26 Total Unif Cot 261.812.00 109,585,295 28,86.98 54,82.00 15,28.09 44,451.95 5.36.09 3.43.56
Ex as Unit Cot
27 Ener $/$0.0315 $0.030 $0.03 $0.03033 $0.02971 $0.0270 $0.030 $0.030
28 Deand $l/mo $18.15 $20.48 $2.05 $18.46 $15.51 $13.47 $12.82 $2.39
29 Cust SlCustmo $16.76 $14.39 $17.96 $4.75 $98.76 $1.026.89 $2.94 $1.2628
30 Re to Co Rao al Pred Ra 1.00 0.95 1.16 1.06 0.92 0.98 0.97 1.01
31 Curm Revue to Proped Cos Rati 0.88 0.83 1.01 0.92 0.81 0.89 0.82 0.89
Exibit No. 13
case No. AVU-E-1Q.l
T. Knox. Avlsta
Schedule 3. p. 3 of 4
Sumc AVISTA UTLITS Idaho Juriic
Scri: Copany Base Cas Cust Co Analys Ele Utit 0310
Rev Peak CrK & Trans by Ded w 7CP Fo II Twe Mo En Debe 31, 20
PROPOSED METODOOGY
(b)(e) (d) (e)(f)(g)(h)(ij OJ (k)(~(m)
Reentil Geera La Ge Ex La Ex La Pumping Slr&Sys Seice Se Se GeSe Serv CP Se ArUghts
Deptin Totl SC1 SC 11.12 SC21.22 SC25 SC25P Sch 31-3 SC4149
Meter, Sees Mete Reading Bi Biling Cost by SCedle at Reqst Rate of Return
Rate Ba
1 Ses 43,010,00 35,231,923 6,80,94 50,88 0 0 46,251 0
2 Servce Acm. Depr.(15,85,00)(12,98,90)(2,50,859)(186,105)0 0 (17,128 0
3 Totl Sece 27,156,00 22,245,015 4,29,087 318,77 0 0 293,123 0
4 Meters 28,49,00 15,03,787 8,398,39 3,878,77 78,316 12,99 1,09,731 0
5 Me Acm. De.(1,938,00)(1,02,53n (571,111)(26,766)(5,32)(88)(74,376)0
6 Tot Met 26,561,00 14,014,249 7,827,287 3,615,00 72,99 12,112 1,019,35 0
7 Tot Rate Base 53,71,00 38,259,265 12,128,374 3,93,78 72,99 12,112 1,312,4n 0
8 Retum on Rate Ba ~ 8.55%4,592,80 3,100,167 1,036,805 33,33 6,241 1,036 112,217 0
9 Renue Convers Fact 0.6376 0.6376 0.636 0.636 0.6376 0.636 0.6376 0.6366
10 Ra Ba Revene Reireent 7,22,nO 4.86,69 1.628.251 528.203 9,80 1.626 176,21 0
Ex
11 Se Depr Ex 670,00 54,835 106,68 7,86 0 0 7,232 0
12 Meters Depr Exp 38,00 205,246 114,63 52,94 1,069 m 14,92 0
13 Sece Optis Ex 418,00 342,407 66,174 4,907 0 0 4,512 0
14 Mete Opg Ex 141,00 74,395 41,551 19,190 387 64 5,411 0
15 Me Maintanc Exp 39,00 2O,5n 11,493 5,38 107 18 1,497 0
16 Met Reaing 36,00 274.231 52,99 4,012 29,46 3,68 3,614 0
17 BOring 2,553,00 2,067,63 399,593 30,253 22,859 2,857 27,245 2,554
18 Totl Expeses 4,578,000 3,53,33 792,513 124,479 53,86 6,80 64,44 2,55
19 Revenue Coversn Fact 0.9984 0.9938 0.9938 0.99 0.9938 0.9938 0.99 0.9938
20 Ex Revenu Reqrem 4,60.375 3,555,231 797.425 125,250 54,219 6,82 64.83 2,570
21 Totl Me. Seivce. Meer Reading an 11,819,145 8,42,889 2,425,675 653,4 64,020 8,468 241,070 2,570
22 Total Custoer BOis 1,46,714 1,194,961 230,939 17,48 96 12 15,746 1,476
23 Aver Unit Cost pe Mo $8.9 $7.05 $10.50 $37.37 $6.87 $705.67 $15.1 $1.74
Distibon Fbied Costs per Custmer
24 Tota Custo Relate Co 24,481,180 17,195,603 4,148,38 799,975 94,729 12,323 361,137 1,86,025
25 Customr Relate Unit Co pe Molh $16.76 $14.39 $17.96 $4.75 $98.76 $1,02.89 $2.94 $1,26.28
26 Tot Dilrbu Ded Relte Cost 46,175,332 22,02,54 5,89,85 13,40,248 1,40,515 43,749 1,959,916 1,047,50
27 Dist Deand Relat Unit Co pe Monlh $31.61 $18.43 $25.53 $766.n $14,64.78 $3,395.71 $124.47 $709.69
28 Totl Distbuton Uni Co pe Moit $4.37 $32.82 $4.50 $812.53 $15,627.54 $37,422.61 $147.41 $1,975.97
exibit No. 13
Cas No. AVU-E-1o-1
T. Knox, Avist
Schedle 3, p. 4 of 4
KEMA~
..c.,,-
System Loa'd Research Project
Examining the components of the Avista system load
Avista Corp., Spokane, Washington, March 2010
Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 1 of 89
Experience yo can trt.
Exhibit No. 13
Case No. AVU-E-10-D1
T. Knox, Avista
Schedule 4, Page 2 of 89
exrienc you can trst.
KEMA~
Table of Contents
1. Executive Summary...... ........... ............. ...... ..... ... ....... .... ......... .... ... ..... ...... ..... ... ........ ...... ..1-1
1.1 Project Overview........... ... ..... ......... ..................... ............. ... .................................. ...1-1
1.2 Key Statistics.. ..... ......... ....... ........ ........... ... ....................... .... .............. ...... .............. .1-2
2. Management Report .........................................................................................................2-7
2.1 Introduction..............................................................................................................2-7
2.1.1 Background...... ..... .... ............... ............... ............ ... ...... ....... ...... .................. .2-7
2.1.2 Project Deliverables ............ ... ............ ..... .......... ...... ... ........ ..... .... .......... .......2-8
2.1.3 Data Provided by Avista ...............................................................................2-9
2.1.4 Avista System Load Characteristics ...........................................................2-10
2.1.5 Annual kWh Sales by Rate Class...............................................................2-13
2.1.6 Sample Design...........................................................................................2-13
2.2 Analysis Approach .................................................................................................2-15
2.2.1 Overvew of Class Load Profile Development.............................................2-15
2.2.2 Verification and Editing of the Class Interval Data ......................................2-16
2.2.3 Statistical Methodology ..............................................................................2-20
2.3 Class Load Profiles - Washington State .................................................................2-23
2.3.1 Residential (Y A) ...... ................ ... ............ .... ..... ... ......... ........................ ..... .2-23
2.3.2 General Servce.. ... ....... ....... .... ... .............. ................................. .... ..... .... ...2-28
2.3.3 Large General Service .... ..... ..... ....... ...... ... ... ............ ............. ...... .............. .2-33
2.3.4 Exra Large General Servce................... ... ...... ..... .... ... ......... ... ..... ......... ....2-38
2.3.5 Pumping ............................................................................ .........................2-42
2.3.6 Street and Area Lights................................................................................2-47
2.4 Class Load Profiles - Idaho ...................................................................................2-51
2.4.1 Residential ...................... ...................... .....................................................2-51
2.4.2 General Service .........................................................................................2-56
2.4.3 Large General Service ...............................................................................2-61
2.4.4 Extra Large General Service.. ................. .............. ... .............. .... .............. ..2-66
2.4.5 Extra Large General Service - CP .............................................................2-70
2.4.6 Pumping.....................................................................................................2-74
2.4.7 Street and Area Lights................................................................................2-79
Av.,ii,
Co",.
Exibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4, Page 3 of 89
KEMA~
List of Tables
Table 1 - Number of Customers and Annual Usage ............................................................... 1-3
Table 2 - Class Demand at Annual System Peak .................................................................. 1-3
Table 3 -Annual Class Peak Demand.....................................................................................1-4
Table 4 - Annual Non-coincident Peak Demand ..................................................................... 1-5
Table 5 - Average 12-Month Class Peak Demand and 12-Month System Peak Demand ....... 1-5
Table 6 - Average 4-Month Winter Class Peak Demand and 7 -Month SummerlWinter Peak
Demand...........................................................................................................................1-6
Table 7 - Summary of Top System Hours...............................................................................1-6
Table 8 - Rate Classes Analyzed ........................................................................................... 2-7
Table 9 - System Load Summary Statistics .......................................................................... 2-11
Table 10 - "Books and Records" Population Counts and Consumption Data ..... .............. ..... 2-13
Table 11 - Sample Design Expected Relative Precision ....................................................... 2-14
Table 12 - Edit Proceure Summary Table...........................................................................2-20
Table 13 - Residential (WA) Post-Stratification.....................................................................2-23
Table 14 - Residential (WA) Summary Statistics (Totals - MW) ........................................... 2-27
Table 15 - Residential (WA) Summary Statistics (Means - kW) ........................................... 2-27
Table 16 - General Service (WA) Post-Stratifcation .............................................................2-28
Table 17 - General Service (WA) Summary Statistics (Totals - MW) ...................................2-32
Table 18 - General Servce NiA) Summary Statistics (Means - kW) ................................... 2-32
Table 19 - Large General Service Ni A) Post-Strtification .......... ........ ................... .............. 2-33
Table 20 - Large General Service NiA) Summary Statistics (Totals - MW) .........................2-37
Table 21 - Large General Service NiA) Summary Statistics (Means - kW) ......................... 2-37
Table 22 - Exra Large General Service NiA) Summary Statistics (Totals - MW)................ 2-41
Table 23 - Exra Large General Service (WA) Summary Statistics (Means - kW) ................2-41
Table 24 - Pumping NiA) Post-Stratifcation ........................................................................2-42
Table 25 - Pumping NiA) Summary Statistics (Totals - MW)............................................... 2-46
Table 26 - Pumping NiA) Summary Statistics (Means - kW)............................................... 2-46
Table 27 - Street and Area Lights NiA) Summary Statistics (Totals - MW) ......................... 2-50
Table 28 - Residential (ID) Post-Stratification.......................................................................2-51
Table 29 - Residential (lD) Summary Statistics (Totals - MW) .............................................2-55
Table 30 - Residential (lD) Summary Statistics (Means - kW) ............................................. 2-55
AvISA'
Clip.
Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avist
Schedule 4, Page 4 of 89
KEMA~
List of Tables
Table 31 - General Service (10) Post-Strtifcation ...............................................................2-56
Table 32 - General Service (10) Summary Statistics (Totals - MW) .................................... 2-60
Table 33 - General Service (10) Summary Statistics (Means - kW)...................................... 2-60
Table 34 - Large General Service (10) Post-Stratifcation ..................................................... 2-61
Table 35 - Large General Service (10) Summary Statistics (Totals - MW) ........................... 2-65
Table 36 - Large General Service (10) Summary Statistics (Means - kW)............................ 2-65
Table 37 - Extra Large General Service (10) Summary Statistics (Totals - MW) ..................2-69
Table 38 - Exra Large General Service (10) Summary Statistics (Means - kW) .................. 2-69
Table 39 - Extra Large General Service - CP (10) Summary Statistics (Totals - MW) ......... 2-73
Table 40 - Pumping (10) Post-Stratication ..........................................................................2-74
Table 41 - Pumping (10) Summary Statistics (Totals - MW)................................................. 2-78
Table 42 - Pumping (10) Summary Statistics (Means - kW)................................................. 2-78
Table 43 - Street and Area Lights (10) Summary Statistics (Totals - MW).................... ........ 2-82
Av...
Co",
ii Exibit No. 13
Case No. AVU-E-10-01
T. Knox, Avista
Schedule 4, Page 5 of 89
KEMA=I
List of Figures
Figure 1 - System Load......... ..... ... ......... ................... ... ... .... .... ..... ... ....... ....... ... ................. ..... 1-2
Figure 2 - Avista System Load Characteristics. .................................................................... 2-10
Figure 3 - Monthly Summary Statistics ................................................................................. 2-11
Figure 4 - System Summer and Winter Peaks......................................................................2-12
Figure 5 - Example of an Anomalous Spike..........................................................................2-16
Figure 6 - Load Shape with the Spike Corrected .................................................................2-17
Figure 7 -- Comparison of Original and Filed Load Shape....................................................2-19
Figure 8 - The MBSS Model................ ................................................................................. 2-22
Figure 9 - Residential (WA) Class Load.......................................................................... ...... 2-24
Figure 10 - Residential NVA) Winter vs. Summer ..........................................:......................2-25
Figure 11 - Residential NVA) Achieved Relative Precision ................................................... 2-26
Figure 12 - General Service NVA) Class Load .................................................. .................... 2-29
Figure 13 - General Service NVA) Winter vs. Summer ......................................................... 2-30
Figure 14 - General Service NVA) Achieved Relative Precision............................................ 2-31
Figure 15 - Large General Service NVA) Class Load... ....... ......... ........... .......... ..... .......... ..... 2-34
Figure 16 - Large General Service NVA) Winter vs. Summer ............................................... 2-35
Figure 17 - Large General Service (WA) Achieved Relative Precision.... ......................... ..... 2-36
Figure 18 - Exra Large General Service NVA) Class Load .................................................. 2-39
Figure 19 - Extra Large General Service NVA) Winter vs. Summer .....................................2-40
Figure 20 - Pumping NVA) Class Load ................................................................................. 2-43
Figure 21 - Pumping NVA) Wintervs. Summer.....................................................................2-44
Figure 22 - Pumping (WA) Achieved Relative Precision ....................................................... 2-45
Figure 23 - Street and Area Lights NVA) Class Load.......... .......... ........ .... ........................... 2-48
Figure 24 - Street and Area Lights NVA) Winter vs. Summer................................................ 2-49
Figure 25 - Residential (10) Class Load................................................................................2-52
Figure 26 - Residential (10) Winter vs. Summer ................................................................... 2-53
Figure 27 - Residential (10) Achieved Relative Precision......................................................2-54
Figure 28 - General Service (10) Class Load ........................................................................ 2-57
Figure 29 - General Service (10) Winter vs. Summer............................................................ 2-58
Figure 30 - General Service (10) Achieved Relative Precision .............................................. 2-59
Figure 31 - Large General Service (10) Class Load..............................................................2-62
At...
Co",
Exibi No. 13
Case No. AVU-E-1D-1
T. Knox; Avista
Schedule 4, Page 6 of 89
KEMA~
List of Figures
Figure 32 - Large General Service (10) Winter vs. Summer.................................................. 2-63
Figure 33 - Large General Service (10) Achieved Relative Precision.................................... 2-64
Figure 34 - Exra Large General Service (10) Class Load..................................................... 2-67
Figure 35 - Extra Large General Service (10) Winter vs. Summer ........................................ 2-68
Figure 36 - Exra Large General Service - CP (10) Class Load............................................. 2-71
Figure 37 - Extra Large General Servce - CP (10) Winter vs. Summer ............................... 2-72
Figure 38 - Pumping (10) Class Load ................................................................................... 2-75
Figure 39 - Pumping (10) Winter vs. Summer ....................................................................... 2-76
Figure 40 - Pumping (10) Achieved Relative Precision ......................................................... 2-77
Figure 41 - Street and Area Lights (10) Class Load .............................................................. 2-80
Figure 42 - Street and Area Lights (10) Winter vs. Summer.................................................. 2-81
AvISll'
eo".
ii Exibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 7 of 89
KEMAt:
1. Executive Summary
1.1 Project Overview
In this project KEMA provided assistance to Avista in developing hourly load estimates for
Avista rate classes. The analysis detailed in this report focuses on data collected for the 12-
month period January 1, 2009 through December 31, 2009. The primary objective of the overall
analysis is to develop hourly class load estimates for use in cost allocation, i.e., to develop
factors to allocate generation, transmission, and distnbution costs to each rate class for cost-of-
service purposes.
In order to perform the analysis, Avista provided aD-minute interval load profile data for each
customer class. Some customer class loads were estimated using load study samples (when it
is not practical to collect load profile data for every customer within the class). The aO-minute
load profie load data for these schedules were for specific customers who were randomly
selected to be part of a load study.
The load study samples were designed with KEMA's assistance to be representative of Avista's
customer classes throughout Avista's service terrtory (both Washington and Idaho) at a
generally-accepted level of statistical precision (confidence that the demand estimates
calculated using samples are within ten percent of the "true" population demand for a majonty of
hours). These samples were used to conduct the load research expansion analysis (that is,
estimate the population loads from the sample loads). This project provided statistically reliable
data allowing the researchers to develop independent estimates for each class within each
jurisdiction.
In addition to the load study samples, some customer classes have hourly load data for all
customers in the class (these tend to be large customers, and their load profile data is used for
biling purposes). Finally, the project team estimated total class hourly loads for the lighting
class based on lighting inventones, daylight hours and sunrise/sunset schedules.
Avista also provided hourly total system load data. Figure 1 shows a vertical EnergyPrint and a
two-dimensional time series plot of the Avista system load during the 12-month penod ending
December 31, 2009. In a vertical energy print, the days are measured on the y-axis and hours
of the day on the x-axis. The load is displayed using the color scale shown to the left of the plot.
The energy pnnt provides an overview of a load profile. In this case the energy pnnt shows that
the Avista system load is winter peaking with the highest demands in the morning (Le., a AM to
At....
Co",.
1-1 EXibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avlst
Schedule 4, Page 8 of 89
KEMA~
11 AM) and evening periods (i.e., 5 PM to 10 PM) dunng the winter months. The system
peaked at 1,763 MW on Tuesday, December 8,2009 at hour ending 7 PM.
Avista System Load
20
MN
1700
~~~.~~~~-~~~~
Lo nne
Figure 1 - System Load
The results of this analysis include each customer class's contribution (delivered load plus
losses) to Avista's total system hourly demands for the penod January 1,2009 to December 31,
2009. From these results, various energy- and demand-related statistics can be calculated
reliably for cost allocation purposes.
1.2 Key Statistics
Table 1 presents a summary of population and energy characteristics for the aggregate classes
within the Washington and Idaho junsdictions. The table includes the total number of customers
and annual energy consumption by rate class. In addition, the table includes each rate
schedule's contnbution to the total for each jurisdiction (Washington and Idaho) and each rate
schedule's contribution to the overall Avista total.
Avll
Co",.
1-2 EXibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avist
Schedule 4, Page 9 of 89
KEMA~
001 Re ent 5.45.0%27.8%
011/012 Geerl seice 11.6%7.6%4.7%
021/022 Large Geral 5e 1.4%28.5%17.6%
025 Ex Large Gel serv 0.0%15.8%9.7%
031/032 Pumping 1.0%2.5%1.6%
LGT St and Ar U ht 0.0%0.5%0.3%
fUN 3 ~':f.:~;;,:1001 \100 ,1';
i aho 001 Res 99,580 81.9%34.9%1.4%
Idaho 011/012 Genel 5e 19,245 15.8%9.5%3.7%
Idaho 021/022 Large Gel Sece 1,458 1.2%20.8%8.0%
Idaho 25 Ex Large Geerl 5e 8 0.0%7.5%2.9%
Idaho 25P Ex Large Gel Sece - CP 1 0.0%25.2%9.7%
Idaho 031/032 Pumping 1,312 1.%1.7%0.7%
Idaho LGT St and Ar U hts 0.0%0.4%0.2%
TOAL IDA 12160 100.%100.0%38.%
¡.;
*No: St an are lit custer cont are not Inud sice ling cu are conte In a äif ma thn th re of th cl n.e., ai and/or
numbe of light).
Table 1 - Number of Customers and Annual Usage
Table 2 presents the class demand at the time of the annual system peak which occurred on
Tuesday, December 8, 2009, at hour ending 7 PM. The dominance of the residential class is
evident accounting for nearly 1 ,000 wr of the 1,763 wr Avista system peak demand. The
large general service class is next in order of magnitude of load with nearly 350 MW at the time
of the Avista peak.
Washington 001 Residential
Washington 011/012 General 5erviæ
Washington 021/022 Large General 5erviæ
Washington 025 Exa Large General 5ervæ
Washington 031/032 Pumping
Washln n LGT Stre and Area U hts
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
, 001 Residential
011/012 Gel 5erviæ
021/022 Large General 5erviæ
25 Ex Large General 5ervæ
25P Exa Large General 5erviæ - CP
031/032 Pumping
LGT Street and Ar U ht
46.6%
10.1%
18.9%
6.5%
16.6%
0.6%
0.6%
100.0%
16.0%
3.5%
6.5%
2.2%
5.7%
0.2%
0.2%
34.4%
Table 2 - Class Demand at Annual System Peak
AvISA'
CO".
1~3 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4, Page 10 of 89
KEMA~
Table 3 presents the annual class peak demands including the date and time of the class peak.
In addition, the table includes each rate schedule's contribution to the total of the class peak
demands for each jurisdiction (Washington and Idaho) and each rate schedule's contribution to
the overall Avista total1.
Washingto
Washingtn
Washingtn
Washingtn
Washingtn
Wasl on
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
001 Resential Tue De 8, 200 7:00PM
011/012 General seice Moo Aug 3, 200 4:00PM
021/022 Large General seice Wed sep 16, 2009 4:00PM
025 Ex Large General Servce Tue De 8, 2009 12:00M031/032 Pumping Fi Jun 5, 2009 6:00PM
LGT Str and Ar . hts Wed Jan 7 2009 9:00PM,c:~"j(¡~10TAhW HINGION
001 Resideal Sun De 6, 200 8:00PM
011/012 General seice Wed De 9, 2009 5:00PM
021/022 Large General service Tue Aug 4, 200 3:00PM
25 Ex Large Generl servce Wed sep 2, 2009 1:00PM
25P Ex Large Geeral serv - CP Wed De 16, 2009 1:00A031/032 Pumping Fri Jul 24, 200 8:00AM
LGT Street and Ara U hts Wed Jan 7 2009 9:00PM
TOTAL IDAHO.T::.~A
33.8%
4.6%
15.4%
6.9%
2.3%0.6% 0.4%
OØitl% 1';§:;:';cKB¡;.l61'¡S%
41.7% 15.2%10.0% 3.6%21.3% 7.8%5.5% 2.0%
14.7% 5.4%6.3% 2.3%
0.5% 0.2%100.% 36.5%
00)11
Table 3 -Annual Class Peak Demand
1 The sum of the class peak demands is not a demand that actually occurred on the system, however, each class's
contribution to the total of the class peak demands is used for cost allocation purposes so is included as a key
statistic.
Avis.'
Corp
1-4 EXhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 11 of 89
KEMA~
Table 4 presents the annual maximum non-coincident class peak demand which is the
"theoretical" or potential maximum demand of the class if all individual customers peaked at the
same time.
Washingtn 001 Residential
Washingtn 011/012 General 5ervæ
Washington 021/022 Large General Seiviæ
Washingn 025 Exa Large General Seiviæ
Washingtn 031/032 Pumping
Washin n LGT Street and Ar U hts
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
001 Residential
011/012 General Seiviæ
021/022 Large General 5eiviæ
25 Exa Large General 5eiviæ
25P Ex Large General 5eiviæ - CP
031/032 Pumping
LGT Stret and Ar U hts
42.9%
5.2%
10.70Æi
4.0%
1.6%
0.2%
57.9%
10.1%
14.3%
3.0%
10.9%
3.6%
0.2%
100.0%
20.6%
3.6%
5.1%
1.1%
3.9%
1.3%
0.1%
35.5%
Table 4 - Annual Non-coincident Peak Demand
Table 5 and Table 6 present selected alloctors (kW and %) for each class by jurisdiction and
total system. The allocators included in Table 5 are the average 12-month class peak demand
and the average 12-month system peak demand.
GT
506,175
88,013
287,992
131,145
27,84
7189
,8
233,419
62,54
145,915
40,327
111,01520,8
3746
61784
204
Idaho
Idaho
IdahoId
Idaho
Idaho
Idaho
001 Reential
011/012 General 5ece
021/022 Large Geerl seic
25 Ex Large Genel 5ece25P Ex Large General 5e - CP
031/032 PumpingLGT Strt and Ar U hts
TOAL IDAHO
37.
10.1%
23.6%
6.5%
18.%
3.4%
0.6%
100.0%
30.%
5.3%
17.3%
7.9%
1.7%
0.%
i2',,;; ;;;;62'1
14.0%
3.8%
8.8%
2.4%
6.7%
1.3%
0.2%
37.1%;9" ,
46,575
75,348
252,577
118,99
18,891138 0.1% 0.1%
~, ~q;;,SWi, ¡09 Rit;!':~'i;;:)63¡8!'
207,604 39.3% 14.2%
54,72 10.4% 3.8%113,66 21.5% 7.8%36,919 7.0% 2.5%
106,611 20.2% 7.3%7,721 1.5% 0.5%64 0.1% 0.0%
527 893 100.0% 36.2%1458:411 iOO;%
Table 5 - Average 12-Month Class Peak Demand and 12-Month System Peak Demand
Av....
CD",
1-5 EXibit No. 13
Case No. AVU-E-10-Q1
, T. Knox, Avista
Schedule 4, Page 12 of 89
KEMA~
Table 6 includes the average of the four winter peaks and the average of the four winter peaks
and the three summer peaks.
TOAl IDAHO
589,872
73,162
242,353
122,613
8,134170
:;:1' Oi'ii¡
254,637
59,30
113,771
37,554
104,7934,8104
575908
i750,
.
44.2
10.3%
19.8%
6.5%
18.2%
0.8%
0.2%
100.%
36.6%
4.5%
15.0%
7.6%
0.5%
0.1%
'/".;,&4;3, ii):
15.8%
3.7%
7.1%
23%
6.5%
0.3%
0.1%
35.7%
100;
'/,1'
230,523
57,190
115,905
37,299
106,4777,0
600
555062
1 9
52.1%
7.9%
26.0%
12.2%
1.8%
0.1%
" :,':,,; OOL09
41.5%
10.3%
20.9%
6.7%
19.2%
1.3%
0.1%
100.0%
. hisTALW NN.,
ho
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
001 Res ena
011/012 Geerl 5ervæ021/022 larg Gel 5e25 Ex large Geerl 5eæ
25P Ex large Gel 5eæ - CP
031/032 PumpingLG St and Ar . ht
Table 6 - Average 4-Month Winter Class Peak Demand and 7 -Month SummerlWinter Peak
Demand
Table 7 presents additional allocators based on the performance of the class at selected system
peak hours. The first allocator is based on the top 25 system load hours followed by the top 75
and the top 200 hours.
Reen011/012 GeI5elæ021/22 La Ge 5eæ25 Ex La Gel 5e25P Ex La Gel 5e . CP031/2 PumpLG St and Ar hl
TOTALJDA
AL
J
Table 7 - Summary of Top System Hours
Av.
Co",
1-6 EXibit No. 13
Case No. AVU-E-10-01
T. Knox. Avista
Schedule 4, Page 13 of 89
KEMA:!
2. Management Report
2.1 Introduction
2.1.1 Background
In this project KlEMA provided assistance to Avista in developing hourly load estimates
for vanous customer classes. The primary goal is to use the results of this load research
analysis in the Company's upcoming cost-of-service (COS) analysis. Table 8 presents
the customer classes included in the analysis.
Idaho 001 Reidental
Idaho 011/012 General service
Idaho 021/022 Large General servceIdaho 25 Exa large General seice
Idaho 25P Ex Large General Service - CP
Idaho 031/032 Pumping
Idaho LGT Str and Area U hts
Table 8 - Rate Classes Analyzed
The Company collects 15-minute load profile data for residential, commercial and
industrial customers. Primarily, the data are collected by the Company's conventional
metering following a statistically stratifed sample design. These data are assembled,
edited and stored by the Company in the MV90 system and transferred to KEMA for
analysis. KEMA conducts a secondary review of the data and transfers the information
into Statistical Analysis System (SAS) fies.
The analysis detailed in this report focuses on data collected for the 12-month period
January 1, 2009 through December 31, 2009. The primary objective of the overall
analysis is to develop hourly class load estimates for use in cost allocation, I.e., to
Av.'
ea",
2-7 Exibit No. 13
case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 14 of 89
KEMA~
develop factors to allocate generation, transmission, and distribution costs to each rate
schedule for cost-of-service purposes.
2.1.2 Project Deliverables
The project deliverables include the following:
. An analysis-ready (i.e., validated and edited) dataset suitable for use in the load
research expansion analysis.
. A dataset containing class total hourly loads calculated for each class and sector
specified in Table 8 either using load study sample data or hourly data for the
entire customer class, when available, for the following scenarios:
- Class hourly loads (before losses and not reconciled to hourly system
load);
- Class hourly loads with losses (not renciled to hourly system load); and
- Class hourly loads with losses and reconciled to hourly system load.
. Documentation of load research expansion analysis including:
- General class statistics;
Post-stratification statistics;
Comparison of winter and summer average load profiles;
Comparison of weekday, weekend, and peak day average profiles;
Relative precision of load data used to calculate class estimates; and
Class peak (coincident and non-coincident with system) statistics
including kW demand, load factor, and coincident factor.
. A series of tables depicting the class contributions for specific cost-of-service
calculations including:
- Class peak at the time of the annual system peak (i.e., coincident peak);
Annual class peak (peak times vary, not necessarily coincident with
system peak);
Annual non-coincident class peak (i.e., hypothetical total class peak if all
customers within the class peaked at the same time);
Average 12-month class peak;
Average 12-month system peak;
Average of the four winter peaks;
2-8 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
SCedule 4, Page 15 of 89
AvISII'
Cii",.
KEMA:1
- Average of the four winter peaks and the three summer peaks;
- Average of the class peaks for the top 25, 75, and 200 system hours;
- Monthly coincident peaks;
- Monthly non-cincident peaks;
- Monthly load factors; and
- On-peak and off-peak energy by month.
2.1.3 Data Provided by Avista
In order to perform our analysis, Avista provided 60-minute interval load profile data for
each customer class. Some customer class loads were estimated using load study
samples (when it is not practical to collect load profile data for every customer within the
class). The 60-minute load profile load data for these schedules were for specifc
customers who were selected to be part of a load study. These load study samples
were used to conduct our load research expansion analysis.
Some customer classes have load profile data for all customers (these tend to be large
customers, and their load profile data is used for billng purposes). Examples include a
number of the large power classes including Extra Large General Service. The project
team estimated total class hourly loads for their lighting schedules based on lighting
inventories, daylight hours and sunrise/sunset schedules.
In addition to customer-level or class-level interval data, Avista provided hourly total
system load data. All load profile data provided was for the period January 1, 2009 to
December 31,2009.
Avista also provided additional supporting information such as total monthly and annual
energy by schedule, customer counts, and annual loss factors by voltage leveL.
Av.,.
eøip
2-9 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 16 of 89
KEMA~
2.1.4 Avista System Load Characteristics
Figure 2 shows a vertical EnergyPrint and a two-dimensional time series plot of the
Avista system load during the 12-month period ending December 31,2009. In a vertcal
energy print, the days are measured on the y-axis and hours of the day on the x-axis.
The load is displayed using the color scale shown to the left of the plot. The energy print
provides an overview of a load profile. In this case the energy print shows that the
Avista system load is winter peaking with the highest demands in the morning (i.e., 6 AM
to 11 AM) and evening periods (i.e., 5 PM to 10 PM) during the winter months. The
system peaked at 1,763 MW on Tuesday, December 8, 2009 at hour ending 7 PM.
Avista System Load
2I!I
1700 '
~~~-~~~~-~~~~
Lo TI
Figure 2 - Avista System Load Characteristics
Table 9 summarizes the monthly statistics from the system load for the 12 months
ending December 31,2009. The total monthly peak demand varied from a low of 1,258
MW in May to the high of 1,763 MW in December. The annual system peak occurred on
Tuesday, December 8 at hour ending 7 PM. The monthly load factor of the system
varied from 66.8% to 83.0%.
Av.,.
Clip.
2-10 Exibit No. 13
Case No. AVU-E-10-01
T. Knox, Avista
Schedule 4. Page 17 of 89
KEMA:J
Jan-09 946,653 Mon Jan 26, 2009 8:00AM 1,678 1,272 75.8%
Feb-09 796,895 Tue Feb 10, 2009 8:00AM 1,429 1,186 83.0%
Mar-09 834,847 Wed Mar 11, 2009 8:00AM 1,585 1,122 70.8%
Apr-09 705,751 Wed Apr 1, 2009 11:00AM 1,295 980 75.7%
May-09 708,039 Fri May 29,2009 4:00PM 1,258 952 75.7%
Jun-09 704,569 Thu Jun 4, 2009 6:00PM 1,286 979 76.1%
Jul-09 786,248 Mon Jul 27, 2009 5:00PM 1,502 1,057 70.4%
Aug-09 769,272 Mon Aug 3, 2009 5:00PM 1,522 1,034 67.9%
5ep-09 697,311 Wed Sep 2,2009 5:00PM 1,451 968 66.8%
Oc-09 754,475 Mon Oct 12, 2009 8:00AM 1,332 1,014 76.1%
Nov-09 795,840 Mon Nov 30, 2009 6:00PM 1,400 1,105 79.0%
oe-09 982507 Tue De 8 2009 7:00PM 1763 1321 74.9%
Annual 9482407 Tue Dec 8 2009 7:00PM 1763 1082 61.4%
Table 9 - System Load Summary Statistics
Figure 3 shows these results graphically. Please note that the scale is not set at zero on
the load factor plot so this graph exaggerates the variation from month to month.
Avista System Load
T__n --LoF_...om fA
18
'7l
soJaIl ApIl ,u1l 0C1l-.2lJa09 ""ai .... 0C09-""ai ,u09 Od09-
Figure 3 - Monthly Summary Statistics
Avis.efl.
2-11 Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 18 of 89
KEMA~
Figure 4 shows the 24-hour profile of the total system load on the August and December
peak days. The summer peak shows a gradually increasing load throughout the day with
a late afternoon peak. The winter peak is slightly bi-modal with an early morning and
late evening peak. The base winter load is nearly as high as the peak summer load.
Summer and Winter Peaks
MoAu_ø:l2Ð Tu-._"'_lI IA
170 ..
160
80 ..
700 ,
01110
130 ..
120 ..
1100
100
90
80
70 '
0711 131~Tk 191 0000 06 121 181..Tk 0011
Figure 4 - System Summer and Winter Peaks
Avisll
COlp.
2-12 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4. Page 19 of 89
KEMA~
2.1.5 Annual kWh Sales by Rate Class
In this section, we wil discuss information developed from the current biling data. Table
10 shows the number of accounts, total annual sales in kWh, and the average kWh
sales per account in each rate class from the Avista "books and records." In addition,
the table includes each rate schedule's contribution to the total load for each jurisdiction
(Washington and Idaho) and each rate schedule's contribution to the overall total Avista
system load.
001 Redentla
011/012 Geerl 5ece
021/022 Large Geeral servce025 Ex Large Genel 5ece
031/032 Pumping
LGT Str and Ar U
2,447,261,373
418,437,869
1,574,380,056
889,056,291
136,399,767
26610041
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
Idaho
001 Residentil
011/012 General servce
021/022 Large Generl seic
25 Exa Larg Geerl 5ece
25P Ex Large Geral servce - CP
031/032 Pumping
LGT Str and Area U hts
ÎlII.lti 'tò/ .~ lJ ~
99,827
19,288
1.426
10
1
1,316
, :; : Sl- . . ~ ~gl\~n~r .
*Not: St and are light cume count are no incuded sinc lightng cu are co in a diff manner than th re of the
clss (i.e., coct and/or numbe of light), therore th av annual en use is not meningl In th co
Table 10 - "Books and Records" Population Counts and Consumption Data
2.1.6 Sample Design
For some customer classes, i.e., residential, small general service, large general service
and pumping, it is not practical to collect load profile data for every customer within the
class. For these classes, load study samples were designed with KEMA's assistance to
be representative of Avista's customer classes throughout Avista's service territory (both
Washington and Idaho) at a generally-accepted level of statistical precision (confidence
that the demand estimates calculated using samples are within ten percent of the "true"
population demand for a majority of hours). For these classes, customers were
randomly selected to be part of a load study following a stratifed sample design using
the annual use of the customer as the primary stratifcation variable. Afer selection,
Avista installed recording device on the statistically selected samples of customers,
AvISI'.
Cør
2-13 Exibit No. 13
Case No. AVU-E-10-D1
T. Knox, Avista
Schedule 4, Page 20 of 89
KEMAt(
periodically collected data from the load recording devices, routinely conducted quality
assurance, stored the data from the sample and transferred the data to KEMA for
analysis. KEMA used the resultant data to conduct the load research expansion
analysis (that is, estimate the population loads from the sample loads).
At the sample design phase, population billng data were provided to KEMA by Avista for
use in constructing effcient sample designs for the following rate classes:
· Residential
· General Service
· Large General Service
· Public Pumping
The objective of sampling is to provide a statistically reliable estimate of the total
demand in a particular class of customers. The analysis KEMA performed for Avista is
grounded on the theory of Model Based Statistical Sampling (MBSS) which is discussed
in more detail in the "Statistical Methodology" section of this report. Using the ratio
model, stratifed samples were constructed for each rate class and expected relative
precisions were calculated.
Washington 0.900 168 :I 11.60%
Idaho 0.900 82 :I 16.69%
Total 0.900 250 :19.52%
Washingtn 0.810 115 :I 13.05%
Idaho 0.787 85 :I 14.68%
Total 0.800 200 :19.75%
Washington 0.498 52 :I 11.47%
Idaho 0.505 23 :I 17.56%
Total 0.500 75 :19.61%
Washingtn 0.985 50 :123.72%
Idaho 1.034 25 :135.82%
Totl 1.000 75 :I 19.78%
Table 11 - Sample Design Expected Relative Precision
The anticipated relative precisions for each of the samples at the time of the sample
design are presented in Table 11, including the overall rate class precision, and the
precision by rate class and jurisdiction. The Residential, General Service, and Large
General Service classes overall were expected to achieve precision within ten percent,
and the classes broken out by jurisdiction follow closely with slightly higher precision
percentages (as expected given their smaller sample sizes). Higher relative precision
AvIS.
Cørp.
2-14 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 21 of 89
KEMA~
percentages are common for irrigation or pumping customers given the high variabilty of
customer loads within the class.
The results of this project were in line with the anticipated precisions presented above
ensuring that the project has provided statistically reliable data for developing
independent estimates for each class within each jurisdiction.
2.2 Analysis Approach
2.2.1 Overview of Class Load Profile Development
KEMA performed the following steps to conduct the analysis presented in this report:
1) Load profile data validation and estimation,
2) Identified the monthly system peak days, hours and collection of hours using the
Avista system load data,
3) Post stratifed the available hourly load data using the current billing data to
calculate case weights for use in the expansion analysis,
4) Using the case weights expanded the 2009 load data to estimate the class load
contributions for the various schedules of interest. The expansions yielded
estimates of totals, means, error bounds for the totals, error bounds for the
means, achieved relative precision and error ratios for each target variable of
interest,
5) Applied loss factors provided by Avista to the load research class expansions,
6) The revised hourly expansions for each rate class were summed and compared
to the actual system load (this results in a residual load known as unaccounted
for energr, or UUFE", and
7) Finally, the UFE was applied to each rate class based on lle proportion of the
rate class's contribution to the individual hour yielding the reconciled class load.
Several classes had hourly data available for all the customers within the rate class, so
the total class loads were simply calculated by adding together the individual customer
loads. Rate classes with data available for all customers included the Exra Large
2 Unaccunted for energy (UFE) refers to the difference between the total of the class estimates and the
actual system load data which can result from sampling errr. UFE is not referrng to unaccunted for
energ that results from theft or "Iosl meters.
AvISI'.'
eo".
2-15 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 22 of 89
KEMA=!
General Service (WA), Extra Large General Service (10), and Exa Large General
Service - CP (10).
In addition, certin class loads were estimated using "deemed" profiles which provides
an estimate or calculation of the total class load and is carried into the raw analysis
without adjustment. That is, no post-straUfication or expansion occurs for deemed
profiles, as they are the total class load profie. Street and Area Lights class loads are
deemed profiles in this analysis.
2.2.2 Verification and Editing of the Class Interval Data
One of the first tasks undertaken was to systematically and thoroughly examine each
available interval load point for the schedules with load study sample data. The
objective of the examination was to identify and correct anomalous points and missing
data. Where appropriate, the accptable data was used to derive an estimate for this
data. The first step in this task was to review each site using KEMA's proprietary
Visualize-IT softare program. The purpose of this examination was to identify
anomalous data points, such as spikes, or changes in multipliers.
For example, Figure 5 shows the load shape for an individual site. For a brief number of
intervals, this site exhibited a spike in demand 10 times larger than the typical demand.
Accordingly, it was deemed anomalous, and eliminated from the individual customer
profile. Figure 6 shows the same site with the anomalous data omitted.
No..
..
...... ..I..T_....
Figure 5 - Example of an Anomalous Spike
Av.,.c""
2-16 Exibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schdule 4, Page 23 of 89
KEMA:t
-No,
'- ..1""T1_....
Figure 6 - Load Shape with the Spike Corrected
The second step was to correct the anomalies and fill in the missing intervals. For the
classes that showed weather sensitive load we developed temperature response models
for use in fillng in the missing intervals. Using the valid, non missing data for a site,
models were developed by day-of-week for each hour of,the day. The development of
the temperature demand models follow a seven-step procedure:
1. Identify Holidays: After reading in the hourly load data and checking for
anomalous data, holidays are identifed and reassigned. Since holidays tend to
have a unique load pattern similar to a weekend these were reclassifed as
Sundays for this analysis. The holidays include New Years Day, Memorial Day,
July 4th, Labor Day, Thanksgiving, and Christmas.
2. Determine the Base Load: The next step determines the base loads. The
demands for each customer are calculated by day of the week and time of day.
The median of the lowest five non-zero loads by day of the week and time are
designated as the base load of the customer.
3. Determine the Variable Load: The third step determines the variable load. For
each customer the base load is matched to the total load by day of the week and
time. The variable load is calculated as the diference between the total load and
the base load. If the variable load is less than zero, the variable load is set equal
to zero.
4. Merge Load Information with Temperature Data: The next step matches the
customer loads to the temperature file. Temperature data from the Spokane
NOAA weather station was used.
5. Initial Regression Analysis: For each customer an initial regression analysis
wil be performed. Using the model shown below:
VL1rid,dow,time=ßO + ß1 * HOD + ß2*CDD
Where:
Avis".
Carp.
2-17 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4, Page 24 of 89
KEMAt:
VL1rld,dOw,time is the Variable Load for customer 'LRID', on day of the
week 'DOW' at hour ending 'Time'.
HOD are the heating degree-days (varying temperature base
based on optimal customer response)
COD are the cooling degree-days (varying temperature base
based on optimal customer response)
The results of this model are used to identif outliers. Any observation with a
studentized residual of greater than 3 wil be trimmed from the analysis data set.
6. Final Regression Analysis: Using the analysis trimmed data set, the final
regression analysis was performed. For each day of the week and hour of the
day, a model is developed.
A family of models is examined for each customer by day of the week and time of
day. These models include only cooling degree-days, models that include heating
degree-days and models that include both heating and coling degree-days.
To further optimize the selection of the models, a range of degree-day set points
are considered for each test group modeL. For heating degree-ays the
considered set points wil range frm 500 to 700. For coling degree-days the
considered set points will range frm 640 to 780. Mathematically, the models
under consideration can be expressed as follows:
VL1rld,dow.time=ßo + 131 * HDD('t1) + ß2*CDD('t2)
Where
VL1ri,dow,lIme is the same as above
HDD('t1) are the heating degree-days with a 't1 base
CDD( 't2) are the cooling degree-days with a 't2 base
For each test group, for each' day of the week for each hour 840 models are
considered. The optimal model amongst the 840 alternatives is determined based
on the minimization of the mean squared errr of the residuals (MSE)3. Using this
selection method, 168 optimal models are chosen for each customer.
3 A1temative models, with different numbers of independent variables, introduce a challenge to choosing an
optimal modeL. One approch would rely on the maximization of R2 to indicate the optimal modeL. Howver, in
building mathematical regreion models, the R2 statistic has a tendency to incrase as the number of
independent variables increases. Therefore, when comparing models with difrent numbers of regressors, the
maxmum R2 criteria may not lead to choosing the optimal moel betwen altematie models. To avoid this
possibility, an altemative method to determine the optimal model was used, the minimiztion of the mean
squared errr of the reiduals (MSe). The MSe accunts for the decrease in the degrees of fredom when an2-18 Exhibit No. 13
Case No. AVU-E-1o-01
T. Knox, Avista
Schedule 4, Page 25 of 89
AtIA'
COrp.
KEMA~
7. Prediction of Missing Data: After the models are verified, demands for missing
period are determined using the hourly temperature of the specific period.
For classes that appeared to have distinct patterns of consumption depending on time of
day and day of week, we used data for similar hours for similar days of the week within
season.
The third editing step was to reexamine each individual site using Visualize-IT. This
examination compared the original and filled data for the site. Figure 7 shows an
example of an original and filled load shape. As evidence, the "corrected" profie
provides a very good estimate of what the original profile was likely to have done during
the missing data periods.
Non 0
Figure 7 - Comparison of Original and Filed Load Shape
Table 12 presents a recapitulation of the editing procedure. This table shows that there
were over 5.4 millon intervals examined. Of these, 5.2 milion (97%) were accpted as
valid. About 2.7% of the intervals were filled due to missing data or they were deemed
anomalous and corrected. Only 0.87% of the intervals were left missing.
additinal regressor is added to the equation. Therefore, the model that minimized the MSE was chosen as the
optimal moel to represent the temperature versus demand relationship.
AvIS'Fll
e"".
2-19 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4. Page 26 of 89
KEMA~
i to ot
1,527,562
896,598
43,491
181,74535313
'11 ;,' ,,'
6 ,272
710,185
242,265
64,097
17,520
197518
188857
o
18,269
o
o
15329
,33'598
Ö
o
7.018
o
o
69881400
Idaho
Idaho
Idho
Idaho
Idaho
Idaho
001 Redena
011/012 Geeral 5eiæ
021/022 Large Gel 5e
25 Ex Large Geerl 5eæ
25P Ex Large Gel 5eæ - CP
031 032 Pum in
Idaho Totls
5
Table 12 - Edit Procedure Summary Table
2.2.3 Statistical Methodology
22,958
31,213
8,269
2,215
22558l
16,248
25,655
4,757
5,983
o
5734583n
4
This analysis is grounded on the theory of Model Based Statistical Sampling (MBSS).
Most of the pnnciples and methods of MBSS theory are discussed in Sarndal, Swensson
and Wretman, Model Assisted Survey Sampling and Wright, Methods and Tools of Load
Research. The methods are also taught in the AEIC's Advanced Application of Load
Research seminar.
The objective of sampling is to provide a statistically reliable estimate of the total
demand in a particular class of customers. The MBSS methodology improves the
statistical precision by taking advantage of the correlation between the measure of
demand of interest, called the target vanable, and the auxilary information available
from the biling data. We usually use pnor load data or general expenence to estimate a
model between a particular target variable y, e.g., the kW in an individual hour or the
average kW in the 12 monthly system peak hours, and a supporting vanable x, such as
annual kWh, that is known in the population. Once the parameters of the model have
been estimated, we can apply the model to the values of x in the population to assess
the expected statistical precision for the target vanable, and to develop effciently
stratifed sample designs.
y¡ = ßx¡ +8¡
We assume the MBSS ratio model relating y to x. The pnmary equation of the model is:
(1)
AvIS.
Co",
2.20 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 27 of 89
KEMA~
This is similar to a zero-intercept regression model, except that we assume that the
standard deviation of the random term E¡ vanes from one customer i to another,
depending on the value of x¡, according to the secondary equation:
sdl¡ I x¡ = = sdt¡ == 0"0 (¥¡ 3 (2)
Here p , U 0 and r are parameters that are assumed to be constant from customer to
customer in a given class of N customers labeled i = 1, 2, ..., N. We denote
O"¡ = sdl¡ :andp¡ = p x¡.
Then we define the error ratio as:
N
LU¡er =.lN
L,u¡
¡=I
(3)
A model-based design suitable for stratifed ratio or regression estimators can usually be
developed from just two parameters: the error ratio, er and the parameter, r, wnten as
gamma.
The error ratio measures the total residual standard deviation in the population. Given
the error ratio, the expected relative precision at the 90% level of confidence can be
estimated using the following equation:
~errp=1.64Vl-li ~
(4)
Here N is the number of units in the population and n is the planned sample size. This
assumes the use of an effciently stratified sample design and a combined ratio
estimator. Gamma, r, charactenzes the degree of heteroscedasticity in the secondary
equation (2) and is used to develop the effciently stratifed sample design.
Ai
CD.
2-21 Exibit No. 13
case No. AVU-E-10-D1
T. Knox, Avista
Schedule 4, Page 28 of 89
KEMA~
1
8
7
6
5
! 4
3
2
500 1.000 1,500
monthly kWh
2,000 2,500
Figure 8 - The MBSS Model
Figure 8 ilustrates these ideas. The figure shows a typical scatter plot of sample data.
The variable (x) plotted on the horizontal axis is the average monthly kWh energy use of
each sample customer, known from biling data. The variable (y) plotted on the vertical
axis is the customets kW demand coincident with the hour of the system peak. The
dark trend line is the expected demand of each customer as a function of the monthly
kWh of the customer. The lighter lines are the expected demand plus and minus one
standard deviation. These three lines reflect the parameters of the estimated modeL.
The key parameter is the error ratio, which in this case is 0.63. This indicates that one
standard deviation is equal to about 0.63 times the expected value of demand for this
population in this hour. In this particular case, gamma was found to be approximately
equal to one, but 0.8 is more typical and can be used in most applications.
We used the following data to inform our MBSS analysis:
. Hourly load data for each sample customer in the current load study for each of
the rate classes and domains of interest,
. System load data for the 12-month period ending December 31, 2009, and
. Current billng data for each customer in each class, especially annual kWh
consumption.
Avis".'
COlp.
2-22 Exibit No. 13
case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 29 of 89
KEMA~
2.3 Class Load Profiles · Washington State
The following sections present the results of the reconciled class load for each of the
rate classes in Washington State.
2.3.1 Residential (WA)
The sample data was expanded by post-stratifying the Residential NVA) class. Table 13
presents the post-stratification used in the sample expansion analysis. The table
presents the jurisdiction, schedule, rate class, strata, maximum annual use4 in each
stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample. Please note that
these statistics vary slightly from Table 10 due to slight timing diferences between data
in the population biling file and those used as the accounting "books and records." The
data in Table 13 was used to construct appropriate weights, whereas the data in Table
10 was used in the preliminary expansion analysis.
R tiaReal 2Reenl 3Redential 4Regdental 5
Clss Totls
Table 13 - Residential (WA) Post-Stratification
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
4 There were a handful of accounts with extreme usage values associated with them. Their
inclusion wil not materially affect the results of the analysis.
Avr.'
Co",
2-23 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 30 of 89
KEMA:l
hour. The residential class in Washington represents approximately 33% of the total
system load and therefore received about one-third ofthe UFE5.
Figure 9 presents the results of the reconciled hourly expansion analysis for the
Residential NV A) rate class. The figure displays the EnergyPrint to the left of the more
standard two-dimensional x-y plot. As a reminder, the vertical form of the EnergyPrint
displays time on the x-axis, day of the year on the y-axis and the magnitude of load on
the z-axis. The magnitude of load is displayed as a color gradient with low levels of load
in the black-blue spectrum and high levels of load in the yellow-white spectrum. The
dominance of the winter load is clearly evident with bi-modal peaks occurrng in the
morning and early evening periods. The Residential NVA) class peaks on Tuesday,
December 8, 2009 at 7 PM. The peak demand was 710 MN.
Residential
Washington State
Figure 9 - Residential (WA) Class Load
5 The UFE varied on an interval by interval basis.
2-24Av..I.-
Ci".
Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 31 of 89
KEMA~
Figure 10 highlights the diferences between the winter and summer by displaying the
average weekday, average weekend day, and pek days. Winter is defined as the
October through March period and summer is defined as April through September. The
winter bi-modal peak is clearly evident in the weekday and peak day profiles. The
weekend profiles display a similar level of magnitude with a slightly higher load factor
(Le., flatter load shape) when compared to the weekday profiles.
Winter vs. Summer
A_WN Anr..Wl _io.
..'..
MW
70 ....
MW
7D .'
....
..
0& 12: 1&:00 0l
tburEnc
06 12: 18:00 00.0
HourEnd
0811 12: 18: 0000
HoiwEnd
- W. RI, w.- ie_,Wæ
Figure 10 - Residential (WA) Winter vs. Summer
Avis.
Corp
2-25 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4, Page 32 of 89
KEMA~
Figure 11 presents a summary of the achieved relative precision6 associated with the
Residential NV A) class analysis. The figure presents the percentage of time the
achieved precision was at or below the specific leveL. For example, 65% of all hours are
at or below a precision of :t10%. The majority of hours (Le., 95% of all hours) were at or
below :t11.9%.
Achieved Relative Precision
_..-..,.
I.
.. .
.1009O1KM1m1I4O3O2OtDKPtrln.Dnn~BI
Figure 11 - Residential (WA) Achieved Relative Precision
Table 14 presents summary statistics for the Residential NV A) class load after applying
losses and reconcilation to the system load. The table displays class totals and
includes the monthly energy use, the timing of the class peak demand, the magnitude of
the class peak demand, the average demand, the load factor based on the class peak
demand, the timing of the system peak demand, the class demand at the time of system
peak (Le., coincident), and the coincidence factor calculated as the coincident peak
divided by the class peak.
6 Statistical precision is a measure of how much customer-ta-customer variation there is in the
data and is used to construct boundaries around our estimates. In load research applications we
typically target precision levels of :110% for the majority of hours in the analysis period.11. . 2-26 Exhibit No. 13..w'..ji Case No. AVU-E-10-Q1Clip. T. Knx, Avist
Schedule 4, Page 33 of 89
KEMAE(
Monthly load factors ranged from a low of 50% in August and September to a high of
69% in February. The Residential ()A) class load is very coincident with the system
peak displaying a system peak coincidence factor of over 80% for 11 of the 12 months.
Jan-30,37 SUn Jan 4, 2009 7:00PM 62 414 66%Man Jan 26, 200 8:00 607 97%Fe 249,433 SUn Fe 1, 20 11:O 54 371 69%Tue Fe 10, 20 8:00 478 89
Mar-l 251,920 Wed Mar 11, 200 9:00 565 33 60%Wed Ma 11, 20 9:00 565 100
Ap-l 184,101 Wed Ap 1, 20 9:00M 425 25 60%Wed Ap 1, 20 12:00 359 85%Ma 166,56 Sa Ma 30, 20 7:00PM 412 224 54 Fr Ma 29, 200 5:00 293 71%
Jun-161,445 Thu Jun 4, 200 8:00 403 224 56%Th Jun 4, 200 7:00M 38 94%
Jul-D 195,859 Mon Ju127, 20 7:00 494 26 S3 MOI Jul 27, 200 6:00M 455 92%
Aug-187,439 sat Aug 1, 200 7:00PM 50 252 50 Mon Au 3, 200 6:00PM 450 88
Sep-15,475 Tue 5e 1, 20 7:00 437 217 50 Wed 5e 2, 200 6:00P 40 92%
Oc-D 199,612 Th oc 29, 200 8:00PM 44 268 60 Mo OC 12, 20 9:00 40 91%
Nov 23,520 SUn Nov 15, 20 6:00 50 331 66%Mo No 30, 20 6:00PM 455 90
De-D 332019 Tue De 8 2009 7:00M 710 44 63%Tue De 8 200 7:00 710 100Anl2631721Annu Cl Pe 710 30 42%AnualS Pek 710 100%
Table 14 - Residential (WA) Summary Statistics (Totals - MW)
Table 15 presents the same information as Table 14 but on a per-accunt basis. The
average Residential () A) customer uses 13,150 kWh with an average demand of 3.6
kW at the time of the class peak.
Jan-1,541 SUn Jan 4, 200 7:00M 3.1 2.1 66 Mo Jan 26, 200 8:00 3.0 96Fe1,246 SUn Fe 1, 2009 11:00 2.7 1.9 69 Tue Fe 10, 200 8:00 2.4 89%
Mar-l 1,29 Wed Mar 11, 200 9:00 2.8 1.7 60%Wed Mar 11, 200 9:00 2.8 100
Ap-l 920 Wed Ap 1, 20 9:00 2.1 13 60 Wed Ap 1, 20 12:00 1.8 84%
May-D 83 sat Ma 30, 200 7:00 2.1 1.1 54%Fr Ma 29, 200 5:00 1.5 71%
Jun-807 Th Jun 4, 20 8:00 2.0 1.1 56%Thu Jun 4, 20 7:00 1.9 95%
Jul-97 Mo Jul '1, 200 7:00M 2.5 1.3 53%MOI Jul 27, 20 6:00PM 2.3 92%
Aug-937 sat Au 1, 200 7:00PM 2.5 13 50 MOI Au 3, 200 6:00 2.3 89%
Sep-78 Tue 5e 1, 20 7:00 2.2 1.1 50%Wed 5e 2, 20 6:00PM 2.0 92%
Oc-D 997 Th oc 29, 200 8:00 2.2 1.3 60 Mo oc 12 20 9:00 2.0 91%No 1,192 SUn Nov 15, 20 6:00 2.5 1.7 66%Man No 30, 20 6:00 2.3 90De1659Tue De 8 20 7:00 3.6 2.2 63%Tue De 8 20 7:00 3.6 100%Anl 13150 Anual Cl Pek 3.6 1.5 42%Annul Pek 3.6 100
Table 15 - Residential (WA) Summary Statistics (Means - kW)
Avis.'
Cøt.
2-27 Exhibit No. 13
case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 34 of 89
KEMAE(
2.3.2 General Service
The sample data was expanded by post-stratifying the General Service (WA) rate class.
Table 16 presents the post-stratification used in the sample expansion analysis. The
table presents the jurisdiction, schedule, rate class, strata, maximum annual use in each
stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample.
WA Gei Se 1
WA Gel 5e 2
WA Gen 5e 3
WA Gel 5eæ 4
WA Gel 5ervlæ 5
in:Ob
WA 12 Gea Se 1 34,554 22,517,332 1,333 222.2
WA 12 Gel 5e 2 49,535 26,121,79 616 4 154.0
WA 12 Gene 5e 3 64,796 27,707,369 48 4 121.5
WA 12 Gel 5eæ 4 79,46 29,067,085 40 7 'S.7
WA 12 Gel 5e 5 504364 30976908 323 8 40.4
e
ssToia 414 ö6418 2536 105
Table 16 - General Service (WA) Post-5tratification
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
AtsrA'
eølJ.
2-28 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4. Page 35 of 89
KEMA~
Figure 12 presents the results of the reconciled hourly expansion analysis for the
General Service lNA) class in Washington State. The figure displays the EnergyPrint to
the left of the more standard two-dimensional x-y plot. As a reminder, the vertical form
of the EnergyPrint displays time on the x-axs, day of the year on the y-axis and the
magnitude of load on the z-axis. The magnitude of load is displayed as a color gradient
with low levels of load in the black-blue spectrum and high levels of load in the yellow-
white spectm. Daytimes loads are consistent throughout the year with a higher load
factor during the winter months. The General Service lNA) class peaks on Monday,
August 3, 2009 at 4 PM. The class peak demand was 97 MW.
..~w;
MT,.,,,..~-i:i~:J
General Service
Washington State
'" ....--..
Figure 12 - General Service (WA) Class Load
An.
eo",
2-29 Exhibit No. 13
Case No. AVU-E-10-01
T. Knx, Avist
SCedule 4, Page 36 of 89
KEMA ::,
Figure 13 highlights the diferences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March penod and summer is defined as April through September. The
winter and summer load shapes are similar with summer peaks occurnng later in the
day. The winter and summer weekend profiles display a lower and flatter load shape
when compared to the weekday profiles with winter weekend loads lower than summer.
Winter vs. Summer
A_W8 A..__Day
MW MW MW
.. .....
80 '80 ..
70 '
80 ..
0100 12:00 18: ~~
t1urEnd
06 12:00 18:00 0000
tlurEhd
OIDO 12:00 18:00 0000
llurEn~
- PCSGl1W_rø- AD:SG_,W8
Figure 13 - General Service (WA) Winter vs. Summer
Av.
Co",.
2-30 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 37 of 89
KEMA::"'
Figure 14 presents a summary of the achieved relative precision7 associated with the
General Service NVA) class analysis. The figure presents the percentage of time the
achieved precision was at or below the specic leveL. For example, 75% of all hours are
at or below a precision of :112.8%. The majonty of hours (i.e., 95% of all hours) were at
or below :115.6%.
Achieved Relative Precision..-"
24
, 22
.1D1 90 80 70 en 50 40 30 2O 11J 0%PedTlDø8lllØE
Figure 14 - General Service (WA) Achieved Relative Precision
Table 17 presents summary statistics for the General Service NVA) class load after
applying losses and reconcilation to the system load. The table displays class totals
and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (i.e., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
7 Statistical precision is a measure of how much customer-ta-customer vanation there is in the
data and is used to construct boundanes around our estimates. In load research applications we
tyically target precision levels of :f1 0% for the majonty of hours in the analysis period.2-31 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4, Page 38 of 89
Av.,.,
Clrp
KEMA~
Monthly load factors ranged from a low of 50% in September to a high of 67% in
February and November. The General Service NVA) class load is very coincident with
the system peak displaying a system peak coincidence factor of over 80% for ten of the
12 months.
Ja 45,636 Tue Jan 27, 200 12:ooPM 95 61 65%MOI Ja 26, 20 8:00 82 86%Fe 38,419 Moo Fe 9, 2009 11:00 86 57 670 Tue Fe 10, 20 8:00 71 83%
Mar-0 39,665 Wed Mar 11, 20 12:ooPM 88 53 61%Wed Mar 11, 20 9:00 76 86%
Ap-0 33,868 Fn Apr 3, 20 1:00 S4 47 56 Wed Ap 1, 20 U:OO 81 96%Ma 33,05 Thu May 28, 20 5:00PM 83 44 54%Fn May 29, 200 5:00PM 79 96Jun-33,96 Thu Jun 4, 200 4:00 87 47 54 Th lun 4, 20 7:00PM 62 71%
Jul-0 37,298 Wed Jul 22 20 4:00 92 50 54%MO Jul 27, 20 6:00 90 98
Au-0 36,64 MO Aug 3, 20 4:00PM 97 49 51%Man Au 3, 20 6:00PM 89 92%5e 32,817 Wed Se 2, 20 4:00 92 46 50 Wed Se 2, 20 6:00 82 89
Oc-0 35,801 Thu oc 29, 20 12:00 81 48 60 MOI oc 12, 200 9:00 68 85No36,55 MO No 23, 200 5:00 76 51 670 MO No 30, 20 6:00PM 61 80De4250Thu De 10 20 12:00 95 57 60%Tue De 8 20 7:00PM 64 670
Annul 44,214 Annua aa Pek 97 51 52%Annul Pe 64 66
Table 17 - General Service (WA) Summary Statistics (Totals - MW)
Table 18 presents the same information as Table 17 but on a per-accunt basis. The
average General Service NI A) customer uses 16,440 kWh with an average demand of
3.6 kW at the time of the class peak.
Jan-1,681 Tue Jan 27, 200 U:OO 3.5 2.3 65 Ma Ja 26, 20 8:00 3.0 86%Fe 1,416 Ma Fe 9, 200 11:00 3.2 2.1 670 Tue Fe 10, 200 8:00 2.6 83%Ma 1,461 Wed Mar 11, 200 U:OO 3.3 2.61%Wed Ma 11, 200 9:00 2.8 86%
Ap-0 1,248 Fn Ap 3, 200 1:00 3.1 1.7 56 Wed Ap 1, 200 12:ooPM 3.0 96%
Ma-l 1,218 Th May 28, 200 5:00PM 3.0 1.6 54%Fri Ma 29, 20 5:00 2.9 96%
Jun-1,251 Th Jun 4, 200 4:00 3.2 1.7 54%Th Jun 4, 20 7:00M 2.3 70
Jul-l 1,374 Wed lu 22 200 4:00 3.4 1.9 54%Moo lui 27, 2009 6:00 3.3 98%
Aug-0 1,350 MOI Au 3, 200 4:00 3.6 1.8 51%Moo Aug 3, 20 6:00M 3.3 91%
Se09 1,20 We Se 2, 20 4:00 3.4 1.7 50%Wed Se 2, 200 6:00 3.0 89%
Oc-0 1,319 Th oc 29, 200 12:00M 3.0 1.8 60 Moo oc U, 20 9:00 2.5 85%
Nov-l 1,34 Man Nov 23, 200 5:00 2.8 1.9 670 MOI No 30, 200 6:0PM 2.2 80%
De-l 156 Th De 10 200 U:ooPM 3.5 2.1 60%TueDe 2O7:00 2.4 670
Anniil 1644 Anal Oass Pek 3.6 1.9 52%Anl Pek 2.4 66%
Table 18 - General Service (WA) Summary Statistics (Means - kW)
AvISll'
CO".
2-32 Exhibit No. 13
Cas No. AVU-E-10-Q1
T. Knx, Avista
Schedule 4, Page 39 of 89
KEMA~
2.3.3 Large General Service
The sample data was expanded by post-stratifying the Large General Service lN A) rate
class. Table 19 presents the post-stratification used in the sample expansion analysis.
The table presents the junsdiction, schedule, rate class, strata, maximum annual use in
each stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the histoncal sample and the case weight calculated
as the population count divided by the minimum available sample.
WA 21 Larg er Se 1 ,304 20,,6
WA 21 Larg Geerl Se 39,922 237,591,246 13
WA 21 Larg Geerl 5e 864,930 273,920,5 9
WA 21 Larg Gel 5e 2,173,94 325,204,764 9
WA 21 Larg Gel Sece 8,D08 396,8,097 11
WA 21 La e Gel SecePrma 16109 06 127395037 1
oassTotls 1565036 52
Table 19 - Large General Service (WA) Post-5tratifcation
In the second stage of the analysis, loss factors of 1.079 and 1.054 (provided by Avista)
were applied to the hourly Large General Service (WA) and Large General Service-
Primary lN A) rate class expansions, respectively.
Finally, in the third stage of the analysis, the unaccounted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
Av".
Clip
2-33 Exhibit No. 13
Case No. AVU-E-10-01
T. Knox, Avista
Schedule 4, Page 40 of 89
KEMA~
Figure 15 presents the results of the reconciled hourly expansion analysis for the Large
General Service NI A) rate class. The figure displays the EnergyPnnt to the left of the
more standard two-dimensional x-y plot. As a reminder, the vertical form of the
EnergyPrint displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum.
The summer load tends to be higher than the winter load. The Large General Service
NlA) class peaks on Wednesday, September 16, 2009 at 4 PM. The peak demand was
just under 324 MW.
Large General Service
Washington State
Figure 15- Large General Service (WA) Class Load
AvlS'lll
Corp
2-3 Exhibit No. 13
case No. AVU-E-1D-1
T. Knox. Avlsta
Schedule 4, Page 41 of 89
KEMA~
Figure 16 highlights the differences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
winter and summer load shapes are very similar in both magnitude and shape. The
weekend profiles are substantially lower than their weekday counterparts.
Winter vs. Summer
A....A__-Da
MW MW MW
'00
30'30 ..
2l-
..
08 12;00 18:00 0000
Ho..End
06:00 12: 18: 0000...."-0600 12:00 18:li OO
Htn.-End
- el..-rv- F:l..Vi
Figure 16 - Large General Service (WA) Winter vs. Summer
Av...
Corp
2-35 Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
SCedule 4, Page 42 of 89
KEMA~
Figure 17 presents a summary of the achieved relative precisions associated with the
Large General Service ('A) class analysis. The figure presents the percentage of time
the achieved precision was at or below the specifc leveL. For example, 60% of all hours
are at or below a precision of :110%. The majority of hours (Le., 95% of all hours) were
at or below :112.4%.
Achieved Relative Precision
""-
'"
11
,.
, .
3100 ØO 8D '1 ØO 50 40 30 20 10% 0%Ped1bDt......
Figure 17 - Large General Service (WA) Achieved Relative Precision
Table 20 presents summary statistics for the Large General Service ('A) class load
after applying losses and reconcilation to the system load. The table displays class
totals and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (Le., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
8 Statistical precision is a measure of how much customer-ta-customer variation there is in the
data and is used to construct boundaries around our estimates. In load research applications we
typically target precision levels of :110% for the majority of hours in the analysis period.2-36 Exhibit No. 13
case No. AVU-E-1Q-01
T. Knx, Avista
SCedule 4, Page 43 of 89
Av.,.
Corp.
KEMA::"'
Monthly load factors ranged from a low of 60% in September to a high of 71 % in
February. The Large General Service NVA) class load is very coincident with the system
peak displaying a system peak coincidence factor of over 80% for all 12 months.
Jan-l 148,99 Tue Ja 27, 20 12:00M 291 20 69%Mo Jan 26, 200 8:00 249 85%Fe 132,324 Mo Fe 9, 20 10:00 279 197 71%Tue Fe 10, 200 8:00 242 87
Mar-l 1"1,758 10 Mar 5, 20 11:00 2B 189 67%Wed Mar 11, 20 9:00 247 87%
Apr-09 126,590 Tue Ap 21, 200 3:00PM 262 176 67%we Ap 1, 20 12:00 232 B9
Ma-l 134,243 Thu Ma 28, 200 2:00M 297 18 61%Fr May 29, 200 5:00PM 288 97Jun136,995 Thu Jun 4, 20 4:00 30 190 63%Thu Jun 4, 200 7:00 241 BO
Jul-147,965 Tue Jul 28, 20 5:00 295 199 68%Mo Jul27, 200 6:00M 28 98%
Au-l 148,70 Thu Au 20, 20 2:00M 30 200 65%Mo Au 3, 20 6:00 276 89%Se 1"1,810 Wed Se 16, 200 4:00 324 196 60 Wed Se 2, 2009 6:00 301 93%
Oc-l 13,235 10 Oc 29, 200 U:ooPM 25 179 70%Mo Oc 12, 20 9:00 213 83%No 132,86 Thu No 12, 200 11:0DA 271 184 68%Mo No 30, 20 6:00 221 82%De 144 Tue De 15 20 12:00 28 194 68%Tue De 8 20 7:00 232 81%
Anual 16604 An Oas Pek 324 190 59%Anll Pek 232 72
Table 20 - Large General Service (WA) Summary Statistics (Totals - MW)
Table 21 presents the same information as Table 20 but on a per-account basis. The
average Large General Service NVA) customer uses 497,700 kWh with an average
demand of 96.6 kW at the time of the class peak.
Jan-l 44,457 Tue Jan V, 20 U:OO 86.59.8 69%Mo Jan 26, 20 8:00 74.2 85
Feb-39,48 Mon Fe 9, 200 10:00 83.3 58.8 71%Tue Fe 10, 20 8:00 72.1 87%
Mar-41,99 10 Mar 5, 20 11:00 84.6 56.5 67%we Mar 11, 20 9:00 73.6 87
Ap-G9 37,771 Tue Ap 21, 2009 3:00 78.2 52.5 67%Wed Ap 1, 200 12:ooPM 69.3 89%
Ma "1,055 Thu Ma 28, 20 2:00 88.7 53.8 61%Fr Ma 29, 200 5:00 86.1 97
Jun-l "1,876 Thu Jun 4, 200 4:00M 90.2 56.8 63%10 Jun 4, 20 7:00PM 720 BO
Jul-l 44,149 Tue lu 28, 200 5:00 87.9 59.3 68 Mo Jul 27, 200 6:00 86.0 98
Aug-G 44,36 Thu Au 20, 20 2:00 92.0 59.6 65%Mo Au 3, 20 6:00 82.2 B9Se42,014 Wed Se 16, 20 4:00 96.6 58.4 60%Wed Se 2, 20 6:00 8g.9 93%
Oc-G 39,754 10 Oc 29, 200 12:00 76.5 53.4 70%Mon Oc U, 200 9:00 63.7 83
Nov-l 39,643 Thu No 12, 200 11:00 8M 55.0 68 Mon No 30, 20 6:00M 66.0 82%De 43133 Tue De 15 200 12:0OP 85.4 58.0 68 Tue De 8 200 7:00 69.3 81%
Annul 497,70 Annu Oa Pek 96.6 56.8 59 Anual Pek 69.3 72%
Table 21 - Large General Service (WA) Summary Statistics (Means - kW)
Av,..'
CØI.
2-37 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox, Avista
Schedule 4, Page 44 of 89
KEMAt(
2.3.4 Extra Large General Service
Data for all customers in the Extra Large General Servce lN A) were available, so the
population count and sample size are the same, and each site's case weight is one.
In the second stage of the analysis, loss factors of 1.05675 and 1.038 (provided by
Avista) were applied to the hourly Extra Large General Servce and Exra Large General
Service (IEP) loads, respectively.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
Avisii
Cøt.
2-38 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 45 of 89
KEMA~
Figure 18 presents the results of the reconciled hourly expansion analysis for the Extra
Large General Service (WA) rate class. The figure displays the EnergyPnnt to the left of
the more standard two-dimensional x-y plot. As a reminder, the vertical form of the
EnergyPnnt displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum. The Extra Large General Service NVA) class peaks on Tuesday, December
8, 2009 at noon. The peak demand was 146 MW.
Extra Large General Service
Washington State
Figure 18 - Extra Large General Service (WA) Class Load
Av.
Cørp
2-39 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avist
Schedule 4, Page 46 of 89
KEMAt(
Figure 19 highlights the difference between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
Exra Large General Service NI A) class displays similar average weekday and weekend
profiles by season with the winter load slightly higher than the summer load. The peak
day is quite distinct when compared to the average weekday or weekend day.
Winter vs. Summer
A_-'-".
MW MW
""
..
130 '
OI '
ÐI 12: 18:00 ÐO
HourEnd
0800 i2:OD 18: 00.0
HDurEnc
0800 12: 18:00 ~~
HD.End -..:_---~-
Figure 19 - Exta Large General Service (WA) Winter vs. Summer
The relative precision was perfect since the data for all of the customers in the class
were available for the full 12 month period examined.
Table 22 presents summary statistics for the Exra Large General Service NI A) class
load after applying losses and recncilation to the system load. The table displays class
totals and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (Le., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
AvISI'ii
Co",
2-40 Exibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 47 of 89
KEMA~
Monthly load factors ranged from a low of 72% in March to a high of 83% in April, May
and October. The Extra Large General Servce NVA) load is very coincident with the
system peak displaying a system peak coincidence factor of over 80% for all 12 months.
Jan-82,427 Tue Jan 2:, 200 1:00 139 111 80 Ma Ja 26, 20 8:00 122 88%Fe 71,581 Tue Fe 10, 200 3:00M 130 107 82%Tii Fe 10, 20 8:00 116 90Mar75,413 Wed Mar 11, 20 2:00PM 140 102 72 Wed Mar 11, 20 9:00 118 84%
Ap-l 74,68 Wed Ap 29, 200 3:00 124 104 83%Wed Ap 1, 2009 12:ooPM 111 90May76,2 MOI Ma 18, 20 2:00 124 102 83%Ft Ma 29, 20 5:00 118 96Jun-74,555 Thu Jun 4, 20 3:00PM 126 104 82%Thu Jun 4, 20 7:00 114 90Jul76,263 Ma lu 27, 20 2:00PM 126 103 81%Ma Jul 27, 20 6:00 123 97%Au 78,82 Th Au 20, 20 2:00M 135 106 79 Ma Au 3, 200 6:00 121 90Se76,51 Tu Se I, 20 3:00M 136 106 78%Wed Se 2, 20 6:00 123 91%
Oc-l n,438 Ma Oc 26, 20 2:0 125 104 83 Ma Oc 12, 20 9:0 11 90Nov73,22 Tue No 3, 20 10:00 123 102 82%Ma Nov 30, 20 6:00 114 92%
De-l 86032 Tue De 8 20 12:00 146 116 79 Tue De 8 20 7:00PM 134 92%
Anua 92322 Anl Oa Pek 146 ios n%An Pek 134 92%
Table 22 - Exra Large General Service (WA) Summary Statistics (Totals - MW)
Table 23 presents the same information as Table 22 but on a per.accunt basis. The
average Extra Large General Servce NVA) customer uses 41,964,560 kWh with an
average demand of 6,624 kW at the time of the class peak.
Jan-l 3,746,70 Tue Ja 27, 20 1:00M 6,3OS 5,l 80 Ma Ja 26, 20 8:00 5,5 88%Fe 3,2,698 Tii Fe 10, 20 3:00 5,83 4,82 82 Tue Fe 10, 200 8:00 5,279 90
Mar-l 3,427,8 Wed Ma 11, 20 2:00M 6,374 4,614 n%We Mar 11, 20 9:00 5,3 84%
Ap-l 3,394,68 Wed Ap 29, 20 3:00PM 5,647 4,715 83%We Ap 1, 20 12:ooPM 5,067 90%Ma 3,465,99 Ma Ma 18, 20 2:00 5,625 4,659 83 Ft Ma 29, 200 5:00PM 5,381 96Jun-3,3,871 Thu Jun 4, 20 3:00PM 5,747 4,7a 82%Th Jun 4, 20 7:00M 5,175 90
Jul-l 3,46,48 Ma Jul 2:, 200 2:00 5,740 4,65 81%Ma Jul27, 200 6:00 5,51 97%
Au-l 3,58954 Th Aug 20, 20 2:00 6,123 4,816 79%MO Au 3, 20 6:00PM 5,49 90Se3,478,22 Tue Se I, 200 3:00PM 6,164 4,81 78%Wed Se 2, 20 6:00 5,60 91%
Oc-l 3,519,924 MOI Oc 26, 20 2:00PM 5,69 4,731 83%Ma Oc 12, 20 9:00 5,15 90No3,328,60 Tue No 3, 200 10:00 5,597 4,617 82%Moo No 30, 200 6:00 5,166 92%De 3910535 Tue De 8 20 12:00 6624 5 79 TueDe 2O7:00 6Gn 92%Anl 419656 Annul Oa Pek 6624 479 n%Annul Pek 6,On 92%
Table 23 - Extra Large General Service (WA) Summary Statistics (Means - kW
AI,..'
eo",.
2-41 Exhibit No. 13
case No. AVU-E-10-01
T. Knox, Avist
Schedule 4, Page 48 of 89
KEMA~
2.3.5 Pumping
The sample data was expanded by post-stratifying the Pumping NVA) rate class. Table
24 presents the post-stratifcation used in the sample expansion analysis. The table
presents the jurisdiction, schedule, rate class, strata, maximum annual use in each
stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample.
1
2
3
4
5
15,415,874
21,06,758
25,96,49
31,624,84
42589679
13665655
Table 24 - Pumping (WA) Post-Stratification
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
AvIST.'
Corp.
2-42 Exibit No. 13
case No. AVU-E-10-01
T. Knox, Avista
Schedule 4. Page 49 of 89
KEMA~
Figure 20 presents the results of the recnciled hourly expansion analysis for the
Pumping NVA) rate class in Washington State. The figure displays the EnergyPrint to
the left of the more standard two-dimensional x-y plot. As a reminder, the vertical form
of the EnergyPrint displays time on the x-axis, day of the year on the y-axis and the
magnitude of load on the z-axis. The magnitude of load is displayed as a color gradient
with low levels of load in the black-blue spectrum and high levels of load in the yellow-
white spectrum. The dominance of the summer load is clearly evident with only minimal
load in the winter months. The Pumping NVA) class peaks on Friday, June 5,2009 at 6
PM. The peak demand was about 49 MN.
Pumping
Washington State
Figure 20 - Pumping (WA) Class Load
Avis.'
C.",.
2-43 Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 50 of 89
KEMA~
Figure 21 highlights the diferences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
pumping load is highest during the summer period. The average weekday and weekend
load shapes are very similar by season and difer dramatically from the class peak load.
Winter VS. Summer
A__..A__-/JMWMWMW
30~30 ..
,.
....
20 20
I. ',. '
06 12: 18:00 0000
HciiIIEnd
0600 12:00 11 ~~_e_0800 t2 18:0 0&.0_e_
- a_,Wi- R:FPWi
Figure 21 - Pumping (WA) Winter vs. Summer
AvISf'll
CD.
2-44 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Scedule 4, Page 51 of 89
KEMA~
Figure 22 presents a summary of the achieved relative precision9 associated with the
Pumping NVA) class analysis. The figure presents the percentage of time the achieved
precision was at or below the specifc leveL. The precision for this class reflects the high
volatility of the load.
Achieved Relative Precision.--"
10
eo
, 50
to100 9D øm 10 60 50 ~ 30 20 10% D%i:dTlDcIl8e
Figure 22 - Pumping (WA) Achieved Relative Precision
Table 25 presents summary statistics for the Pumping NVA) class load after applying
losses and reconcilation to the system load. The table displays class totals and
includes the monthly energy use, the timing of the class peak demand, the magnitude of
the class peak demand, the average demand, the load factor based on the class peak
demand, the timing of the system peak demand, the class demand at the time of system
peak (Le., coincident), and the coincidence factor calculated as the coincident peak
divided by the class peak.
9 Statistical precision is a measure of how much customer-to-customer variation there is in the
data and is used to construct boundaries around our estimates. In load research applications we
typically target precision levels of :11 0% for the majority of hours in the analysis period.11. . 2-45 Exhibit No. 13...,151'. Case No. AVU-E-10-Q1C." T. Knox, Avista
Schedule 4, Page 52 of 89
KEMA:!
Monthly load factors ranged from a low of 49% in May to a high of 73% in July. The
Pumping N/A) load is not coincident with the system peak displaying a system peak
coincidence factor of over 80% for only two of the 12 months.
Jan-5,3 Fr Jan 30, 200 8:00 14.4 7.2 50 Ma Jan 26, 20 8:00 10.0 69%Fe 4,84 Sa Fe 21, 20 12:00 12.7 7.2 57 Tu Fe 10, 20 8:00 5.1 40
Mar-0 5,654 Sat Mar 21, 20 U:OO 13.7 7.6 56 Wed Ma 11, 200 9:00 7.6 55%
Ap9 7,38 Ma Ap 27, 20 8:00 17.10.3 57 Wed Ap 1, 20 12ooPM 11.8 66%Ma 17,104 Su May 31, 20 7:00 467 23.0 49%Fr Ma 29, 20 5:00PM 39.1 84%Jun 23,39 Fr JUI 5, 20 6:00 49.1 32.5 66 Th Jun 4, 200 7:00M 31.7 64%JuI 25,329 Fr Ju 3, 20 7:00 46.7 34.0 73%Ma Jul 27, 20 6:00PM 26.7 57
Aug-0 21.49 Sa Au 1, 20 11:ooPM 43.2 28.67%Ma Au 3, 20 6:00 37.8 885e15,04 Wed Se 2, 20 10:00 36.20.9 57 Wed Se 2, 200 6:00 27.0 740
Oc-0 8,431 Fr Oc 2, 200 9:00 228 11.3 50 Ma Oc 12 200 9:00 9.9 43%
Nov-5,811 Sa Nov 14, 200 2:00 14.7 8.1 55%Man No 30, 200 6:00 10.2 69%De 7170 Sat De 12 20 3:00 15.8 9.6 61%Tue De 8 20 7:00 9.9 63%
Annu 147045 Anl aa Pe 49.1 16.8 34%Anl Pe 9.9 20
Table 25 - Pumping (WA) Summary Statistics (Totals - MW)
Table 26 presents the same information as Table 25 but on a per-accunt basis. The
average Pumping N/A) customer uses 62,287 kWh with an average demand of 20.8 kW
at the time of the class peak.
Jan-2,28 Fr Jan 30, 20 8:00 6.1 3.1 50 Ma Ja 26, 20 8:00 4.2 69Fe2,05 Sa Fe 21, 20 12:00 5.4 3.1 57 Tue Fe 10, 20 8:00 2.2 40
Mar-0 2,395 Sa Mar 21, 200 12:00 5.8 3.2 56%Wed Mar 11, 200 9:00 3.2 56
Ap-0 3,128 MOI Ap 27, 20 8:00A 7.6 4.3 57 Wed Ap 1, 20 12:ooPM 5.0 66%
May-7,245 Su Ma 31, 200 7:00 19.8 9.7 49 Fr May 29, 20 5:00 16.5 84%
Jun-9,908 Fr Jun 5, 20 6:00PM 20.8 13.8 66%1lu Jun 4, 20 7:00 13.64%
JuI-0 10,729 Fr Jul 3, 20 7:00 19.8 14.4 73 Ma Ju 27, 20 6:00 11.3 57%Au 9,103 Sa Au 1, 20 11:00 18.3 12.2 67%Ma Aug 3, 200 6:00M 16.88%5e 6,375 Wed Se 2, 20 10:00 15.4 8.9 57 We Se 2, 200 6:00 11.4 74%
Oc-0 3,571 Fr Oc 2, 200 9:00 9.7 4.8 50 MOI Oc 12 200 9:00 4.2 43No2,461 Sa Nov 14, 20 2:00 6.2 3.4 55 Ma No 30, 200 6:00 4.3 69
De-0 303 Sa De 1 200 3:00 6.7 4.1 61%Tue De 8 200 7:00PM 4.2 63%Anl W Anual aa Pek 20.8 7.1 34%Anl Pe 4.2 20%
Table 26 - Pumping (WA) Summary Statistics (Means - kW)
Avis."..
Co",
2-46 Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 53 of 89
KEMA~
2.3.6 Street and Area Lights
In the first stage analysis, the lighting classes were represented by "deemed profiles."
The deemed profile provides an estimate of the load based on billng data and daylight
hours.
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
Av".
Corp.
2-47 Exhibit No. 13
Cas No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 54 of 89
KEMA~
Figure 23 presents the results of the reconciled hourly expansion analysis for the Street
and Area Lights NV A) rate class. The figure displays the EnergyPrint to the left of the
more standard two-imensional x-y plot. As a reminder, the vertical form of the
EnergyPrint displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum. The lighting loads track the nighttime hours. The Street and Area Lights
NVA) class peaks on Wednesday, January 7,2009 at 9 PM. The peak demand was 7.5
MW.
~
Street and Area Lights
Washington State
.. ~..--
Figure 23 - Street and Area Lights (WA) Class Load
Av..
Co.
2-48 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4. Page 55 of 89
KEMA~
Figure 24 highlights the differences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March penod and sum!Ter is defined as Apnl through September. The
lighting class displays similar average weekday and weekend profiles by season. The
longer winter hours are evident.
Winter VS. Summer
A___A.._-..lO
.. ..._.-.. ,.._.-.. ..._.--..""-- ~1G_
Figure 24 - Street and Area lights (WA) Winter vs. Summer
The relative precision was not calculated for the Street and Area Lights NiA) rate class
since the total class load is a deemed profie.
Table 27 presents summary statistics for the Street and Area Lights NiA) class load
after applying losses and reconcilation to the system load. The table displays class
totals and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (i.e., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
Av...
Cøtp
2-49 Exibit No. 13
Case No. AVU-E-1D-1
T. Knox. Avista
Schedule 4, Page 66 of 89
KEMA~
Monthly load factors ranged from a low of 32% in June and July to a high of 60% in
December. The Street and Area Lights NýA) class load is only coincident with the
system peak during the winter months of November and December with coincident
factors of 96% and 94%, respectively. The class peak load is not at all coincident with
the system peak during all other months.
Jan-3,06 Wed Jan 7, 200 9:00M 7.5 4.1 55%Man Jan 26, 20 8:00 0%Fe 2,516 Th Fe 12 20 6:00 6.9 3.7 54%Tue Fe 10, 200 8:00 0%
Mar-l 2,478 SUn Ma 8, 20 4:00 7.3 3.3 46 We Mar 11, 20 9:00 0%
Ap-l 2,02D sat Ap 25, 20 3:00 7.1 2.8 39%Wed Ap 1, 20 12:00M 0%
Mav-1,845 Ma Ma 25, 200 2:00 7.3 2.5 34%Fr Ma 29, 20 5:00 0%
Jun-1,63 Wed Jun 10, 20 4:00 7.2 2.3 32%Th Jun 4, 20 7:00 0%
JuI-I 1,760 Fr lui 3, 20 10:00 7.3 2.4 32%Ma lu 'D, 20 6:00 0%
Au-l 2,041 SUn Au 16, 200 9:00 7.2 2.7 38%Ma Au 3, 20 6:00 0%5e 2,sat 5e 12, 21 l1:DD 7.1 3.2 45%We 5e 2, 21 6:00 0%
Oc-l 2.6'!Man oc 5, 2D 12:00 7.0 3.6 51%Ma oc 12, 2D 9:00 0%
Nov-l 2,951 sa No 28, 200 1:00 7.1 4.1 57 Ma No 3D, 21 6:00M 6.8 96%De 3204 Ma De 7 200 3:00 7.2 4.3 6D Tue De 8 20 7:00 6.8 94%
Annual 28458 Annua aa Pe 7.5 3.2 43%An Pe 6.8 91%
Table 27 - Street and Area Lights (WA) Summary Statistics (Totals - MW)
Av
eo".
2-50 Exhibit No. 13
Cas No. AVU-E-10-01
T. Knox, Avista
Schedule 4, Page 57 of 89
KEMA~
2.4 Class Load Profiles - Idaho
The following sections present the results of the reconciled class load for each of the
rate classes in Idaho.
2.4.1 Residential
The sample data was expanded by post-stratifying the Residential (10) rate class. Table
28 presents the post-stratifcation used in the sample expansion analysis. The table
presents the jurisdiction, schedule, rate class, strata, maximum annual use in each
stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample.
Resntal 1Rental 2Redeal 3Reidetil 4Redel 5
Cl Totls
1,48.3
3,6~.7
1,557.5
850.5
507.1
Table 28 - Residential (ID) Post-Stratification
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contnbution to the system demand for that particular
hour.
AvISIl'
Clip.
2-51 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avist
Schedule 4, Page 58 of 89
KEMA~
Figure 25 presents the results of the reconciled hourly expansion analysis for the
Residential (ID) rate class. The figure displays the EnergyPrint to the left of the more
standard two.dimensional x.y plot. As a reminder, the vertical form of the EnergyPrint
displays time on the x.axis, day of the year on the y-axis and the magnitude of load on
the z.axis. The magnitude of load is displayed as a color gradient with low levels of load
in the black-blue spectrum and high levels of load in the yellow.white spectrum. The
dominance of the winter load is clearly evident with bi-modal peaks occurrng in the
morning and early evening periods. The Residential (ID) class peaks on Sunday,
December 6,2009 at 8 PM. The class peak demand was 319 MW.
Residential
Idaho
Figure 25 - Residential (i D) Class Load
AvisrA'
Corp.
2-52 Exhibit No. 13
case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 59 of 89
KEMA~
Figure 26 highlights the differences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
winter bi-modal peak is clearly evident in the weekday and peak day profiles. The
weekend profiles display a similar level of magnitude with a higher load factor (i.e., flatter
load shape) when compared to the weekday profiles.
Winter vs. Summer
A_-"A....W&1'".
MW MW MW
30 '30 .
.......
06 12: 18:00 ODÐD
Ho..End
0600 12;00 18:li lI
Il_End
0800 12: 18.1J 0D
HowEnc
- T:RE._-U:_._
Figure 26 - Residential (10) Winter vs. Summer
Av....
Cørp
2-53 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 60 of 89
KEMA=!
Figure 27 presents a summary of the achieved relative precision 10 associated with the
Residential (10) class analysis. The figure presents the percentage of time the achieved
precision was at or below the specific level. For example, 60% of all hours are at or
below a precision of :i15.9%. The majority of hours (i.e., 90% of all hours) were at or
below :i20.1 %.
Achieved Relative Precision..-"..
..
, ..
30
20'~,.
.100 90 8D 10 60 SO 40 30 20 10 0%P8dTlDlønlsBe
Figure 27 - Residential (10) Achieved Relative Precision
Table 29 presents summary statistics for the Residential (ID) class load after applying
losses and reconcilation to the system load. The table displays class totals and
includes the monthly energy use, the timing of the class peak demand, the magnitude of
the class peak demand, the average demand, the load factor based on the class peak
demand, the timing of the system peak demand, the class demand at the time of system
peak (i.e., coincident), and the coincidence factor calculated as the coincident peak
divided by the class peak.
10 Statistical precision is a measure of how much customer-to-customer vanation there is in the
data and is used to construct boundaries around our estimates. In load research applications we
typically target precision levels of :110% for the majonty of hours in the analysis period.IL. . 2-54 Exhibit No. 13...,... Case No. AVU-E-1Q-1COrp T. Knox, Avista
Schedule 4, Page 61 of 89
KEMA~
Monthly load factors ranged from a low of 53% in August to a high of 70% in February.
The Residential (ID) load is very coincident with the system peak displaying a system
peak coincidence factor of over 80% for 11 of the 12 months.
Jan-148,8 Sun Ja 4, 20 6:00PM 30 20 66 Man Ja 26, 200 8:00 281 93%Fe 113,92 Sii Fe 15, 20 12:00 242 170 70%Tue Fe 10, 20 8:00 212 88
Mar-09 116,336 we Ma 11, 20 9:00M 243 157 65 Wed Ma 11, 20 9:00 243 100%
Ap 89,131 we Ar 1, 200 9:00 193 124 64%we Ar 1, 200 12:00 172 89
May 85,79 sat Ma 30, 200 2:00 190 115 61%Fr May 29, 20 5:00M 122 64
lun-0 79,102 Su lll 28, 20 9:00M 180 110 61%lhu lun 4, 20 7:00 153 85
lul-94,974 Wed lui 22 20 7:00 22 12 57 Ma iu Xl, 20 6:00 190 86
Au-0 93,48 sa Aug 1, 20 8:00PM 23 126 53%Ma Au 3, 200 6:0 217 92%Se 80,48 Tue 5e 1, 20 8:00M 20 112 54%Wed 5e2, 20 6:00 189 90
Oc-0 101,3 Ma Oc 26, 200 9:00 22 136 60 Ma Oc 12, 200 9:00 215 95%
Nov 110,692 Sun No 22, 20 5:00 m 15 65%Ma No 30, 200 6:00 214 90De15517Sun De 6 20 8:00 319 20 65%Tu De 8 200 7:00 28 89An126868Anal aass Pe 319 145 45%AnlS 28 89
Table 29 - Residential (ID) Summary Statistics (Totals - MW)
Table 30 presents the same information as Table 29 but on a per-accunt basis. The
average Residential (ID) customer uses 12,740 kWh with an average demand of 3.2 kW
at the time of the class peak.
Jaii 1,495 Su Jan 4, 20 6:00 3.0 2.0 66 Ma Jan 26, 200 8:00 2.8 93%Fe 1,144 Su Feb 15, 20 12:00 2.4 1.7 70%Tue Fe 10, 20 8:00 2.1 88
Mar-0 1,168 Wed Mar 11, 20 9:00 2.4 1.6 65%Wed Mar 11, 20 9:00 2.4 100
Ap9 895 Wed Ar 1, 200 9:00 1.9 L2 64%Wed Ar 1, 20 12:00 1.7 89
Ma 86 sa Ma 30, 200 2:00 1.9 1.2 61%Fr Ma 29, 20 5:00PM 1.2 64%
lun-0 79 Su lll 28, 20 9:00M 1.8 1.61%lhu lu 4, 20 7:00 1.5 85%
lul-954 Wed lui 22 200 7:00 2.2 1.3 57 Ma lui 27, 200 6:00 1.9 86%
Au9 939 sa Au 1, 20 8:00PM 2.4 1.3 53 Ma Au 3, 20 6:00 2.2 92%Se 80 Tue 5e 1, 200 8:00 2.1 1.1 54%we 5e 2, 20 6:00 1.9 90
Oc-Ð9 1,018 Ma Oc 26, 200 9:00M 2.3 1.4 60 Man Oc 12, 20 9:00 2.2 94%
Nov-0 1,112 Sun No 22 20 5:00PM 2.4 1.5 65%Ma No 30, 200 6:00PM 2.90
De09 1552 SIiDe 2008:00 3.2 2.1 65%Tue De 8 200 7:0 2.8 88
Annua 12740 Anl Oa Pe 3.2 1.5 45%Annual Pek 2.8 88%
Table 30 - Residential (ID) Summary Statistics (Means - kW)
Avis..
CII.
2-55 Exhibit No. 13
Case No. AVU-E-10-01
T. Knox, Avista
Schedule 4, Page 62 of 89
KEMA=!
2.4.2 General Service
The sample data was expanded by post-stratifing the General Service (10) rate class.
Table 31 presents the post-stratifcation used in the sample expansion analysis. The
table presents the jurisdiction, schedule, rate class, strata, maximum annual use in each
stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample.
'cl
ID 12 Generl ce 1 9, 11
10 12 Genel 5ece 2 60,733
10 12 Geerl 5ece 3 81,247
ID 12 Geerl Se 4 104,838
10 12 Gel 5e 5 3S0SO
Toí 3 38330
8 163.4
5 113.0
5 84.8
9 38.0
90.7
Table 31 - General Service (10) Post-8tratification
In the secnd stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contrbution to the system demand for that particular
hour.
Av.."
Co.
2-56 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 63 of 89
KEMA~
Figure 28 presents the results of the reconciled hourly expansion analysis for the
General Service (10) rate class. The figure displays the EnergyPrint to the left of the
more standard two-dimensional x-y plot. As a reminder, the vertcal form of the
EnergyPrint displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum. Daytimes loads are dominant throughout the year with higher load and load
factor during the winter months. The General Service (10) class peaks on Wednesday,
December 9, 2009 at 5 PM. The class peak demand was 77 MW.
General Service
Idaho
Figure 28 - General Service (10) Class Load
AvlSll
C.tp
2-57 Exhibit No. 13
Case No. AVU-E-10-01
T. Knox. Avlsta
Schedule 4, Page 64 of 89
KEMA~
Figure 29 highlights the diferences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined' as the
October through March period and summer is defined as April through September.
Winter loads are clearly higher than summer loads with a flatter load shape on both
weekdays and weekends. The summer weekday load almost reaches the magnitude of
the winter weekday load, but for fewer hours during the day.
Winter vs. Summer
A_-'A.._Pe""
MW MW MW
70 ..70 '
..-...
.. '
0&00 12: t8 (100
HDurEni
08"' 12: 18".0 lI
Hi_End
0I '1 18:0 00
ll:nirEni
- Z:SG__- M:SGl1_._
Figure 29 - General Service (10) Winter vs. Summer
AvIS.c""
2-58 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 65 of 89
KEMA~
Figure 30 presents a summary of the achieved relative precision 11 associated with the
General Service (10) rate class analysis. The figure presents the percentage of time the
achieved precision was at or below the specific leveL. For example, 60% of all hours are
at or below a precision of :113%. The majority of hours (i.e., 90% of all hours) were at or
below :i15.07%.
Achieved Relative Precision
..",-....
, ..
22
..
18
.10m Ø( 80 70 80 5K 4D 3D 20 10% D'PedTiDlIiBi
Figure 30 - General Service (10) Achieved Relative Precision
Table 32 presents summary statistics for the General Service (10) class load after
applying losses and reconcilation to the system load. The table displays class totals
and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (Le., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
11 Statistical precision is a measure of how much customer-to-ustomer vanation there is in the
data and is used to construct boundanes around our estimates. In load research applications we
tyically target precision levels of :11 0% for the majonty of hours in the analysis period.2.59 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schdule 4, Page 66 of 89
Avis.
Cør.
KEMA~
Monthly load factors ranged from a low of 57% in August and September to a high of
73% in February. The General Service (10) load is very coincident with the system peak
displaying a system peak coincidence factor of over 80% for ten of the 12 months.
Jan-l 35,78 Tue Jan 27, 200 5:00PM 73 48 66 Ma Jan 26, 200 8:00 64 87Fe31,00 Tue Fe 10, 2l 11:00 64 46 73%Tue Fe 10, 200 8:00 52 82%
Ma-l 32467 Wed Mar 11, 2l l200 69 44 64 We Ma 11, 2l 9:00 60 88%
Apr-Q9 26,48 We Ap 1, 2l 1:00PM 60 37 61%We Ap 1, 200 12:00M 59 9l
May 25,129 Fr Ma 29, 2l 5:00PM 58 34 58 Fr Ma 29, 20 5:00 58 100Jun24,553 Wed Jun 24, 20 5:00 56 34 61%lhu Jun 4, 2l 7:00 43 78%Ju 27,126 1l Ju 30, 200 5:00 62 36 59 Ma Jul 27, 2l 6:00PM 56 91%
Aug-l 26,50 Wed Au 19, 200 4:00PM 63 36 57 Ma Au 3, 2l 6:00 'S 90
Se9 23,28 Wed 5e 2, 200 3:00 56 32 57 Wed 5e 2, 2l 6:00 50 lI
0C-l 26,56 lhu OC 29, 20 12:00 54 36 66%Ma OC 12, 200 9:0 42 78
Nov 29,48 1l Nov 19, 2l 12:00M 59 41 69 Ma No 30, 2l 6:00 54 92%~3773 Wed De 9 2l 5:00PM 77 51 66 Tue De 2l 7:00PM 61 80An34191Annul Cl Pe 77 40 52 An Pe 61 80
Table 32 - General Service (10) Summary Statistics (Totals - MW)
Table 33 presents the same information as Table 32 but on a per-account basis. The
average General Service (10) customer uses 17,989 kWh with an average demand of
4.0 kW at the time of the class peak.
Jan-1,8 Tue Jan 27, 2l 5:00 3.8 2.5 66 Ma Jan 26, 20 8:00 33 87Fe1,611 Tue Fe 10, 2l 11:00 3.3 2.4 73%Tue Fe 10, 2l 8:00 2.7 82%
Mar-l 1,687 Wed Mar 11, 2l 12:ooPM 3.6 2.3 64%Wed Mar 11, 2l 9:00M 3.1 8I
Ap-l 1,37 Wed Ap 1, 200 1:00 3.1 1.61%Wed Ap 1, 2l 12:00 3.1 9l
Ma-l 1,3 Fr May 29, 2l 5:00PM 3.0 1.8 58%Fr Ma 29, 2l 5:00PM 3.0 100
Jun-1,276 Wed Jun 24, 2l 5:00M 2.9 1.8 61%1l Jun 4, 20 7:00 2.3 77
Jul-1,410 1l Ju 30, 20 5:00 3.2 1.9 59 Ma Jul 27, 2l 6:00 2.9 90Au1,381 Wed Au 19, 2l 4:00 3.3 1.9 57 MOI Au 3, 2l 6:00PM 2.9 90
5e09 1,210 Wed 5e 2, 200 3:00 2.9 1.7 'S%Wed 5e 2, 200 6:00 2.6 89
0C-l 1,3 1l OC 29, 2l 12:00 2.8 1.9"66%Mo OC 12 2l 9:00 2.2 77
No-l 1,532 1l No 19, 2l 12:00 3.1 2.1 69 Ma No 30, 2l 6:00 2.8 92%~1961 Wed De 9 200 5:00M 4.0 2.6 66%Tue De 8 2l 7:00PM 3.2 80%
Anua 17,989 Annul Cl Pek 4.0 2.1 52 Annua Pek 3.2 80
Table 33 - General Service (10) Summary Statistics (Means - kW)
AvISII
eo",.
2-60 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 67 of 89
KEMAk
2.4.3 Large General Service
The sample data was expanded by post-stratifng the Large General Service (10) rate
class. Table 34 presents the post-stratification used in the sample expansion analysis.
The table presents the jurisdiction, schedule, rate class, strata, maximum annual use in
each stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample.
10
10
10
10
10
10
Table 34 - Large General Service (10) PostoStratification
In the second stage of the analysis, loss factors of 1.079 and 1.054 (provided by Avista)
were applied to the hourly Large General Servce (10) and Large General Service-
Primary (10) rate class expansions, respectively.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
Avis".
Co",.
2-61 Exhibit No. 13
Case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 68 of 89
KEMAdI,
Figure 31 presents the results of the reconciled hourly expansion analysis for the Large
General Service (10) rate class. The figure displays the EnergyPrint to the left of the
more standard two-dimensional x-y plot. As a reminder, the vertical form of the
EnergyPrint displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum. The summer load tends to be slightly higher than the winter load. The Large
General Service (10) class peaks on Tuesday, August 4, 2009 at 3 PM. The peak
demand was just under 163 MW.
Large General Service
IdahoL_..T..'-
Figure 31 - Large General Service (ID) Class Load
Av".
etn.
2-62 Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox. Avista
Schedule 4. Page 69 of 89
KEMA~
Figure 32 highlights the differences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
winter and summer load shapes are very similar in both magnitude and shape. The
weekend profiles are substantially lower than their weekday counterparts.
Winter vs. Summer
A....-.A.._FuDo
MW MW -
..
160 -~---_..._-_._--.- 180 -'~. ..140 140
120
100
0600 12: 18:00 0000
HowEnd
.. .,;;; : : ~
0600 12 11:00 0000_E_OBOD 12:DD 1800 OD
HDurEnd
-luæl21_._-C~._
Figure 32 - Large General Service (ID) Winter vs. Summer
Av..,
CI".
2-63 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 70 of 89
KEMA~,
Figure 33 presents a summary of the achieved relative precision 12 associated with the
Large General Serviæ (10) class analysis. The figure presents the peræntage of time
the achieved precision was at or below the specifc leveL. For example, 60% of all hours
are at or below a precision of ::15.5%. The majonty of hours (Le., 90% of all hours) were
at or below ::19.3%.
Achieved Relative Precision..-"..
, 30
, ..
.... 10
o1t 80 80 70 fm 50 40 30 20 10% 0%PwrlTlDBnll 8e
Figure 33 - Large General Service (10) Achieved Relative Precision
Table 35 presents summary statistics for the Large General Service (10) class load after
applying losses and reconcilation to the system load. The table displays class totals
and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (i.e., coincident), and the coincidenæ factor calculated as the
coincident peak divided by the class peak.
12 Statistical precision is a measure of how much customer-to-customer variation there is in the
data and is used to construct boundaries around our estimates. In load research applications we
typically target precision levels of :t1 0% for the majority of hours in the anal)!is period.IL.. 2-64 Exhibit No. 13...IS. Case No. AVU-E-1Q-1e"". T. Knox, AvistaSChedule 4, Page 71 of 89
KEMA~
Monthly load factors ranged from a low of 53% in August to a high of 65% in January
and February. The Large General ServCe (10) class load is somewhat coincident with
the system peak displaying a system peak coincidence factor of over 80% for five of the
12 months.
Jan-l 63,217 Tue Jan 20, 20 10:00 13 85 65 Ma Jan 26, 20 8:00 113 87%Fe 57,532 l1 Fe 26, 20 10:00 131 86 65%Tue Fe 10, 200 8:00 106 81%
Ma-l 64,06 Thu Mar 12, 20 11:00 138 86 63%Wed Mar 11, 20 9:00 121 88
Ap-l 59,66 Tue Ap 28, 20 11:00 141 83 S9 Wed Ap 1, 20 12:00 118 84Ma61,320 Th May 14, 200 1:0 141 82 59%Fr Ma 29, 200 5:00PM 114 81%Jii 62,0 We Jun 24, 200 2:00 151 87 57%lI Jun 4, 200 7:00 104 68
JuI-l 67,317 Wed Jul 22 20 3:00 159 90 57 Ma Jul V, 20 6:00 117 74%
Aug-l 64,717 Tue Aug 4, 20 3:00 163 If 53%Ma Au 3, 200 6:00 119 735e63,378 Wed 5e 16, 200 3:00 159 88 55%Wed 5e 2, 200 6:00 120 76%
0C-l 61,88 Thu OC 29, 200 2:00 140 83 60 Mo OC 12, 200 9:00 107 77
Nov-l 64,15 Th No 5, 20 10:00 151 89 59%MOI Nov 30, 200 6:00M 110 73De663æTu De 1 20 1:00 148 89 60 Tue De 8 20 7:00M 115 77
Anual 755 816 Annul Oa Pek 163 86 53 AnI Pe 115 71%
Table 35 - Large General Service (ID) Summary Statistics (Totals - MW)
Table 36 presents the same information as Table 35 but on a per-aeçount basis. The
average Large General Service (10) customer uses 518,570 kWh with an average
demand of 118.8 kW at the time of the class peak.
Jan-43,374 Tue Jan 20, 20 10:O 89.4 58.3 65%Moo Jan 26, 200 8:00 77.4 87Fe39,473 Thu Fe 26, 200 10:00 89.8 58.7 65%Tue Fe 10, 200 8:00 n.9 81%
Mar-43,952 Th Ma 12 20 11:00 94.6 59.2 63%Wed Ma 11, 20 9:00 83.1 88
Ap-l 40,934 Tue Ap 28, 20 11:00 966 56.9 S9 Wed Ap 1, 200 12:00 81.2 84
Ma 42,on Thu Ma 14, 200 1:00 96.5 56.6 59%Fr Ma 29, 20 5:00 78.1 81%
Jun-42,75 Wed Jun 24, 200 2:00M 103.9 59.4 57 l1 Jun 4, io 7:00 71.0 68
JuJ 46,187 Wed lu 22 20 3:00PM 109.1 621 57 Ma lu 27, 20 6:00 80.2 74%Au 44,40 Tue Aug 4, 20 3:00 111.8 59.7 53%Mo Au 3, 20 6:00 81.7 73
Sep-43,48 Wed 5e 16, 200 3:00PM 109.0 60.4 55%Wed 5e 2, 200 6:00 825 76%
0C-l 42,463 l1 OC 29, 20 2:00PM 95.7 57.1 60 Ma OC 12 200 9:00 73.4 77
No-l 43,976 Thu No 5, 20 10:00 103.3 61.0 59%Mo Nov 30, 200 6:00 75.5 73De4549Tue De 1 200 1:00 101.7 61.2 60 Tue De 8 20 7:00 78.8 77
AnI 518 570 Annual Oa Pe 111.8 59.2 53%Annual Pek 78.8 71%
Table 36 - Large General Service (ID) Summary Statistics (Means - kW)
Av.,.
C.",
2-65 Exhibit No. 13
Case No. A VU-E-1 0-01
T. Knox, Avista
Schedule 4, Page 72 of 89
KEMA~
2.4.4 Extra Large General Service
Data for all customers in the Extra Large General Service (10) were available, so the
population count and sample size are the same, and each site's case weight is one.
In the second stage of the analysis, a loss factor of 1.054 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccounted for energy was allocated to
each class based on the class's contribution to the' system demand for that partcular
hour.
At.Ce
2-66 Exhibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 73 of 89
KEMA~
Figure 34 presents the results of the reconciled hourly expansion analysis for the Exra
Large General Service (ID) rate class. The figure displays the EnergyPrint to the left of
the more standard two-dimensional x-y plot. As a reminder, the vertical form of the
EnergyPrint displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum. The Exra Large General Service (ID) class peaks on Wednesday,
September 2, 2009 at 1 PM. The peak demand was just under 42 MW.
ITl:..T..-
Extra Large General Service
Idaho
""., .u....--
Figure 34 - Extra Large General Service (10) Class Load
Av
Clip.
2-67 Exhibit No. 13
case No. AVU-E-10-01
T. Knox, Avita
Schedule 4, Page 74 of 89
KEMA~
Figure 35 highlights the difference between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
summer and winter load shapes are similar in magnitude displaying a lower and flatter
load shape on weekends when compared to weekends.
Winter vs. Summer
A_-'Awr....-/J
uw MW MW
....
35 .
3D
25 '25
~
,-
08 12:08 18:00 øo
Hc..End
..
06 12:00 18;00 0000
Hi....End
08 1200 18ll oc_E_-1'_--10-.-
Figure 35 - Exra Large General Service (10) Winter vs. Summer
The relative precision was perfect since the data for all of the customers in the class
were available for the full 12 month period examined.
Table 37 presents summary statistics for the Exra Large General Service (10) class load
after applying losses and reconcilation to the system load. The table displays class
totals and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (i.e., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
Av..c,,,
2-68 Exibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avist
Schedule 4, Page 75 of 89
KEMA~
Monthly load factors ranged from a low of 74% in January to a high of 81% in December.
The Exra Large General Service (10) class load is very coincident with the system peak
displaying a system peak coincidence factor of over 80% for all 12 months.
Jan-0 22,054 Tue Jan 27, 20 10:00 40.2 29.6 74%Mo Jan 26, 20 8:0 31.7 94%Fe 20,590 Tue Fe 17, 20 1:00PM 39.8 30.77 Tu Fe 10, 200 8:00 35.9 90
Mar-0 22501 Tue Mar 31, 20 2:00 40.4 30.3 75%Wed Mar 11, 20 9:00 31.0 92%Ap 21,98 Thu l( 2, 20 2:00 39.4 30.5 78 Wed Ar 1, 20 12:00 31.5 95'
Ma-0 22,401 Thu Ma 7, 200 U:OO 38.8 30.1 78 Fi Ma 29, 20 5:00 34.1 æ%
Jun-0 21,976 Th Jun 18, 20 2:00 39.5 30.5 77 Thu Jun 4, 200 7:00M 36.6 93%
Jul09 22.8 Thu Jull&. 20 2:00 40.1 30.7 77 Man Ju 27, 20 6:00PM 37.1 92%Au 22,771 Th Au 27, 20 2:00 405 30.6 76%Mo Au 3, 20 6:00 34.8 86%5e 2292 Wed 5e 2, 200 1:00 41.9 31.76 Wed 5e 2, 20 6:00 39.0 93%
0å-0 24,06 Th Oå 29, 20 1:00 40.8 324 79 Mo Oå 12, 20 9:00 36.8 90No23,498 Wed Nov 11. 200 11:00 41.0 32.80 Mo No 30, 20 6:0 31.0 90
De-0 25058 Th De 10 20 11:00 41.5 33.7 81%TueDe 200 7:00 39.6 95An27268Anl Ca f'41.9 31.74%AnS Pek 39ò6 94%
Table 37 - Extra Large General Service (10) Summary Statistics (Totals - MW)
Table 38 presents the same information as Table 37 but on a per-accunt basis. The
average Extra Large General Service (10) customer uses 34,085,693 kWh with an
average demand of 5,240 kW at the time of the class peak.
Jan-0 2,756,775 Tu Jan 27, 20 10:o 5,024 3,705 74%Man Ja 26, 20 8:00 4,711 94%Fe 2,57,810 Tue Fe 17, 200 1:00 4,974 3,8 77 Tue Fe 10, 20 8:00 4,492 90
Mar-0 2,812,651 Tue Ma 31, 200 2:00PM 5,05 3,78 75'Wed Mar 11, 200 9:00 4,623 91%
l(-0 2,748,44 Th l( 2, 200 2:00PM 4.92 3,817 78 Wed l( 1, 20 12:ooPM 4,68 95'
May 2,8,131 Th Ma 7, 200 U:OO 4,84 3,764 78%Fi May 29, 20 5:00 4,25 æ%
Jun-0 2,747,024 Th Jun 18, 20 2:00 4,93 3,815 77 1b Jun 4, 200 7:00 4,5 93%Jul-2,.296 1b Jul16, 20 2:0 5,014 3,8 77 Ma Ju 27, 20 6:00 4,631 92
Au-0 2,84,395 Th Au 27, 20 2:00PM 5.06 3,82 76%Ma Au 3, 200 6:00M 4,34 ll5e2,86,322 Wed 5e 2, 20 1:00 5.2 3,98 76%Wed 5e 2, 20 6:00 4,874 93
0å-0 3,00,.468 1b Oå 29, 20 1:00 5,106 4,04 79%Ma Oå 12, 200 9:00 4,60 90
Nov-0 2,937.153 Wed No 11, 20 11:00 5,118 4,074 80 Ma No 30, 20 6:00M 4,62 9ODe3132 219 Th De 10 20 11:00 5190 4 10 81%Tue De 8 20 7:0 4951 95
Anual 34,08.69 Anl Ca Pek 524 3891 74 Anl Pe 4,951 94
Table 38 - Extra Large General Service (10) Summary Statistics (Means - kW
Avis".'C.".
2-69 Exhibit No. 13
case No. AVU-E-10-o1
T. Knox, Avista
Schedule 4, Page 76 of 89
KEMA:b,
2.4.5 Extra large General Service - CP
One customer is included in the Extra Large General Service - CP (10) rate class. Since
the class is comprised of one customer, the population count and the sample size are
the same (that is, one), and the sample case weight is one.
In the second stage of the analysis, a loss factor of 1.054 (provided by Avista) was
applied to the non-generation portion of the Exra Large General Service - CP (10) load
served by Avista.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour. .
Av.,.
Co".
2-70 Exibit No. 13
Case No. AVU-E-10-Q1
T. Knox, Avita
Schedule 4, Page 77 of 89
KEMA~
Figure 36 presents the results of the reconciled hourly expansion analysis for the Exra
Large General Servce - CP (10) rate class. The figure displays the EnergyPrint to the
left of the more standard two-dimensional x-y plot. As a reminder, the vertical form of
the EnergyPrint displays time on the x-axs, day of the year on the y-axis and the
magnitude of load on the z-axis. The magnitude of load is displayed as a color gradient
with low levels of load in the black-blue spectrum and high levels of load in the yellow-
white spectrum. The Exra Large General Service - CP (10) rate class displays a
constant load throughout the year. The class peaks on Wednesday, December 16,
2009 at 1 AM. The peak demand was 112.7 MW.
Extra Large General Service - CP
Idaho
A!.-..,.~..".f~ '~z.~"i;:~~
-_.-,-
~
..
~.. .... .. ..--~
Figure 36 - Extra Large General Service. CP (10) Class Load
Av.,.,
Corp
2-71 Exibit No. 13
Case No. AVU-E-10-01
T. Knox, Avista
Schedule 4. Page 78 of 89
KEMA:b"'
Figure 37 highlights the diferences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
summer and winter load shapes are very similar in magnitude with a flatter load shape
on the weekends when compared to weekdays.
Winter vs. Summer
A_..-'A---De
MW MW lO
"2 112 .
".110 .
'08 ...
'08,..~, -,..
102 ..'02 102 ..0600 12:00 18.-0 li00,...,,-0100 12: 18:00 lIOG_E_06:00 12: '8.11 OD:ODib",_
-1l_._-1P-.._
Figure 37 - Exra Large General Service - CP (ID) Winter vs. Summer
The relative precision was perfect since the data for the one customer in the class were
available for the full 12 month period examined.
Table 39 presents summary statistics for the Exta Large General Service - CP (10) rate
class load after applying losses and reconcilation to the system load. The table displays
class totals and includes the monthly energy use, the timing of the class peak demand,
the magnitude of the class peak demand, the average demand, the load factor based on
the class peak demand, the timing of the system peak demand, the class demand at the
time of system peak (i.e., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
Av.
COIJ.
2-72 Exhibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avist
Schedule 4, Page 79 of 89
KEMA~
Monthly load factors ranged from a low of 92% in August to a high of 96% in January,
February, and March. The Exa Large General Servce - CP (10) class load is very
coincident with the system peak displaying a system peak coincidence factor of over
80% for all 12 months.
Jan-l 78,020 Fn Jan 2, 2O 2:00 109.0 104.9 96%MOI Ja 26 2O 8:00 107.0 98%Fe 70,44 Fn Fe 20, 200 2:00 109.1 104.8 96%Tue Fe 10, 20 8:00 105.9 97Ma77,837 Tu Mar 10, 20 9:00 109.7 104.8 96%Wed Ma 11, 20 9:00 105.7 96%
Ap-0 75,34 Th Ap 23, 2O 3:00 110.9 104.7 94%Wed Ap 1, 2O 12:ooPM 107.8 97Ma77,501 Wed Ma 20, 2O 9:00M 109.4 104.2 95%Fn Ma 29, 20 5:00 102.6 94%lun-75.281 Tu lun 2, 2O 1:00 111.5 104.6 94%Th Jun 4, 2O 7:00PM 106.6 96Ju-l 78,i7 Th lui 30, 200 3:00 111.9 105.2 94%Ma lui 27, 20 6:00 107.2 96
Au9-0 76,978 Ma Au 31, 2O 5:00 112.7 103.5 92%Ma Au 3, 20 6:00PM 110.3 98
Sep-75,532 Th Se 17, 20 7:00 111.104.9 94%Wed 5e 2, 2O 6:00 108.7 97
00-0 78,055 Wed 00 7, 20 2:00 112.1 104.9 94%Moo 00 12 200 9:00 108.6 97%No 74,no Ma No 30, 20 10:00 111.5 103.6 93%Ma No 30, 20 6:00 108.4 97%
De-0 7806 Wed De 1 2O1:00 112.7 104.93%Tu De 8 2O 7:00 100.7 89
Annu 91605 Annul aa Pek 112.7 104.6 93%An Pe 100.7 89
Table 39 - Exra Large General Service - CP (ID) Summary Statistics (Totals - MW)
Avis.,.,eo
2-73 Exhibit No. 13
Case No. AVU-E-10-01
T. Knox, Avist
SCedule 4, Page 80 of 89
KEMA=1
2.4.6 Pumping
The sample data was expanded by post-stratifng the Pumping (10) rate class. Table
40 presents the post-stratification used in the sample expansion analysis. The table
presents the jurisdicton, schedule, rate class, strata, maximum annual use in each
stratum, the population total annual use in the stratum, the population count, the
minimum available sample points in the historical sample and the case weight calculated
as the population count divided by the minimum available sample.
Pumping 5e
Pumping seice
Pumpng serv
Pumping serv
Pum In serv
OassTotls
Table 40 - Pumping (10) Post-Stratification
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly expansions.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contribution to the system demand for that particular
hour.
AvISI'.
eo",
2-74 Exhibit No. 13
Case No. AVU-E-10-01
T. Knx, Avista
Schedule 4, Page 81 of 89
KEMA~
Figure 38 presents the results of the reconciled hourly expansion analysis for the
Pumping (10) rate class. The figure displays the EnergyPrint to the left of the more
standard two-dimensional x-y plot. As a reminder, the vertical form of the EnergyPrint
displays time on the x-axis, day of the year on the y-axis and the magnitude of load on
the z-axis. The magnitude of load is displayed as a color gradient with low levels of load
in the black-blue spectrum and high levels of load in the yellow-white spectrum. The
dominance of the summer load is clearly evident with only minimal load in the winter
months. The Pumping (10) class peaks on Friday, July 24, 2009 at 8 AM. The peak
demand was about 48 MW.
Pumping
Idaho
Figure 38 - Pumping (10) Class Load
Avis.,.,
eorp.
2-75 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knx, Avista
Schedule 4, Page 82 of 89
KEMA~
Figure 39 highlights the differences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
seasonal pumping load is highest during the summer period. The average weekday and
weekend load shapes are very similar by season and differ dramatically from the class
peak load.
Winter vs.Summer
A...1M A.._-Da
MW MW MW
40'40 40 '\30 '3D 30 ..,
20 '20 ':&~,,',..-Li.-A,.~..-.lD~""':-,,: -:
0000 ,_18:00 ..00 ~~'''00 ,,,..~~0000 .-18:00 ..00....-.Ho..End Ho..End-Itmml&._-Q-.-
Figure 39 - Pumping (I D) Winter vs. Summer
Av..,.
Co",.
2-76 Exhibit No. 13
Case No. AVU-E-1Q.1
T. Knox, Avista
Schedule 4, Page 83 of 89
KEMA~
Figure 40 presents a summary of the achieved relative precision 13 associated with the
Pumping (10) class analysis. The figure presents the percentage of time the achieved
precision was at or below the specifc leveL. The precision for this class reflects the high
volatilty of the load.
Achieved Relative Precision
""-"
'20
'10
, 'DO
so
80
7Ð
, 80
, 20
,.'l9D 80 7O 8O 5D.... 2O 10% Ð%
PedTl Dc II Be
Figure 40 - Pumping (10) Achieved Relative Precision
Table 41 presents summary statistics for the Pumping (10) class load after applying
losses and reconcilation to the system load. The table displays class totals and
includes the monthly energy use, the timing of the class peak demand, the magnitude of
the class peak demand, the average demand, the load factor based on the class peak
demand, the timing of the system peak demand, the class demand at the time of system
peak (i.e., coincident), and the coincidence factor calculated as the coincident peak
divided by the class peak.
13 Statistical precision is a measure of how much customer-to-customer vanation there is in the
data and is used to construct boundaries around our estimates. In load research applications we
tyically target precision levels of :110% for the majority of hours in the analysis period.
A.__ . 2-77 Exibit No. 13......... Case No. AVU-E-1Q-1e.". T. Knox, AvistaSchule 4, Page 84 of 89
KEMA:!
Monthly load factors ranged from a low of 24% in August to a high of 50% in September.
The Pumping (10) class load is not coincident with the system peak displaying a system
peak coincidence factor of 80% or greater for none of the 12 months.
Jan-3,315 Ma Jan 19, 2001:00 9.2 4.5 48 Ma Ja 26, 2O 8:00 5.6 60Fe2,98 sat Fe 28, 2O 11:00 10.0 4.4 44%Tue Fe 10, 2O 8:00 5.2 51%
Mar 3,467 Tue Mar 24. 2O 11:O 11.3 4.7 41%Wed Ma 11, 2O 9:00 4.6 41%
Ap-l 3,553 Ft Ap 17, 200 12:00 10.1 4.9 49%Wed Ap 1, 20 12:00 5.4 54%
Ma-l 5,787 Ft Ma 29, 20 8:00 18.1 7.8 43%Ft May 29, 2O 5:00 9.5 52
Jun-8,44 Ft lun 12, 2O 8:00 45.4 11.7 26 11 Jun 4, 2O 7:00 14.32
Jul-l 10,153 Ft Jul 24. 200 8:00 48.2 13.7 28 Ma Jul 27, 2O 6:00 11.2 23%Au 8,591 Ma Au 3, 2O 9:00 47.9 11.6'24 Ma Au 3, 2O 6:00 11.7 24%5e 6.667 Wed 5e 2, 200 7:00 18.5 9.3 50 Wed 5e 2, 20 6:00 7.3 40
Oc-l 3,96 Th Oc 1, 2O 10:00 12.4 5.3 43%Ma Oc 12, 200 9:00 9.2 74%
Nov-l 2,774 Ma No 23, 2O 10:00 8.4 3.9 46 Ma Nov 30, 200 6:0 4.7 56%
De-l 3m 11u De 24 2O 10:00 11.0 5.0 45%Tue De 8 20 7:00 3.9 35
Annii 63428 Anl Oa Pek 48.2 7.2 15%AnmJ S Pe 3.9 8%
Table 41 - Pumping (ID) Summary Statistics (Totals - MW)
Table 42 presents the same information as Table 41 but on a per-accunt basis. The
average Pumping NVA) customer uses 48,339 kWh with an average demand of 36.7 kW
at the time of the class peak.
Jan-2,526 Moo Jan 19, 200 1:00 7.0 3.4 48 Ma Ja 26, 20 8:00 4.3 60%Fe 2,275 sat Fe 28, 200 11:00 7.7 3.4 44%Tue Fe 10, 20 8:00 3.9 51%
Ma9 2,642 Tue Mar 24, 200 11:00 8.6 3.6 41%Wed Mar 11, 200 9:00 3.5 41%Ap 2.70 Ft Ap 17, 200 12:OOPM 7.7 3.8 49%Wed Ap 1, 200 12:00 4.1 54%
May-l 4,411 Ft May 29, 200 8:00 13.8 5.9 430 Ft Ma 29, 2O 5:00M 7.2 52%
Jun-6,432 Ft Jun 12, 200 8:00 34.6 8.9 26 11u Ju 4. 200 7:00M 11.0 32%JuI 7,73 Ft lu 24, 20 8:00 36.7 10.4 28 Ma lui 27, 2O 6:00 8.5 23%Au 6,547 Ma Aug 3, 2O 9:00 36.5 8.8 24%Ma Aug 3, 20 6:00 8.9 25%5e 5,081 Wed 5e 2, 2O 7:00 14.1 7.1 50 We 5e 2, 200 6:00 5.6 40
Oc-l 3,024 11u Oc 1, 2O 10:00 9.5 4.1 43%Ma Oc 12 200 9:00 7.0 74%
Nov-l 2,115 Ma Nov 23, 200 10:00 6.4 2.9 46 Ma No 30, 2O 6:00 3.6 56De28411u De 24 200 10:ooAM 8.4 3.8 45%Tue De 8 2O7:00 2.9 35%Anl 48339 Annual Oa Pek 36.7 5.5 15%Anual Pe 2.9 8%
Table 42 - Pumping (ID) Summary Statistics (Means - kW)
Avis.,.,
Corp
2-78 Exhibit No. 13
Case No. AVU-E-1D-1
T. Knox. Avista
Schedule 4. Page 85 of 89
KEMA~
2.4.7 Street and Area Lights
In the first stage analysis, the lighting classes were represented by "deemed profiles."
The deemed profile provides an estimate of the load based on biling data and daylight
hours.
In the second stage of the analysis, a loss factor of 1.079 (provided by Avista) was
applied to the hourly loads.
Finally, in the third stage of the analysis, the unaccunted for energy was allocated to
each class based on the class's contnbution to the system demand for that particular
hour.
AvIS.'Cfi
2-79 Exhibit No. 13
case No. AVU-E-10-01
T. Knox, Avist
Schedule 4, Page 86 of 89
KEMA~
Figure 41 presents the results of the reconciled hourly expansion analysis for the Street
and Area Lights (10) rate class. The figure displays the EnergyPrint to the left of the
more standard two-dimensional x-y plot. As a reminder, the vertical form of the
EnergyPrint displays time on the x-axis, day of the year on the y-axis and the magnitude
of load on the z-axis. The magnitude of load is displayed as a color gradient with low
levels of load in the black-blue spectrum and high levels of load in the yellow-white
spectrum. The lighting loads track the nighttime hours. The Street and Area Lights (10)
class peaks on Wednesday, January 7,2009 at 9 PM. The peak demand was 3.9 MW.
~Nj"'-~;.tv:l~:a4
"
D
Street and Area Lights
Idaho
.. .... .. ..--
Figure 41 - Street and Area Lights (10) Class Load
Av.,.c.",
2-80 Exibit No. 13
Case No. AVU-E-1Q-1
T. Knox, Avist
Schedule 4, Page 87 of 89
KEMAt(
Figure 42 highlights the differences between the winter and summer by displaying the
average weekday, average weekend day, and peak days. Winter is defined as the
October through March period and summer is defined as April through September. The
lighting class displays similar average weekday and weekend profiles by season. The
longer winter hours are evident.
Winter vs. Summer
A_~A__-Da
MW MW MW
,-
2 '
0S 12: 1B: DD
tburEnd
06:00 12:00 18:00 0000
.l:uIlEnd
06:0 1200 18 0800
Ho..End
- 1tLG._- tLGI._
Figure 42 - Street and Area Lights (10) Winter vs. Summer
The relative precision was not calculated for the Street and Area Lights (10) rate class
since the total class load is a deemed profle.
Av...Ci
2-81 Exhibit No. 13
case No. AVU-E-1Q-1
T. Knox, Avista
Schedule 4, Page 88 of 89
KEMAt(
Table 43 presents summary statistics for the Street and Area Lights (10) class load after
applying losses and reconcilation to the system load. The table displays class totals
and includes the monthly energy use, the timing of the class peak demand, the
magnitude of the class peak demand, the average demand, the load factor based on the
class peak demand; the timing of the system peak demand, the class demand at the
time of system peak (Le., coincident), and the coincidence factor calculated as the
coincident peak divided by the class peak.
Monthly load factors ranged from a low of 33% in June to a high of 57% in December.
The Street and Area Lights (10) class load is only coincident with the system peak during
the winter months of November and December with coincident factors of 96% and 93%,
respectively. The class peak load is not at all coincident with the system peak during
most other months.
Jan-1,545 Wed Jan 7, 20 9:00 3.9 2.1 53%Ma Jan 26 20 8:00 0.4 11%Fe 1,28 St Fe 1, 20 7:00 3.7 1.9 52%Tue Fe 10, 20 8:00 0%Mar-1,28 St Mar 8, 20 4:00 3.8 1.7 46 We Mar 11, 20 9:00 0.2 6%Ap-l 1,074 Sa Ap 25. 20 3:00 3.7 1.5 40 Wed Ap I, 20 12:00 0%May 1.010 Tue Ma 26, 200 6:00 3.8 1.4 36%Fr Ma 29, 20 5:00 0%Jun-913 Sa Jim 20, 20 6:00 3.9 1.3 33%11 Jun 4, 200 7:00 0%Ju 96 Ma Jul 6, 200 4:00 3.7 1.3 35%Ma lu 27, 20 6:00 0%Au 1,08 Ma Au 3, 20 1:00 3.7 1.5 40 Ma Au 3, 20 6:00 0%5e 1,193 Sa 5e 12, 200 11:00 3.7 1.7 45%Wed 5e 2, 20 6:00 0%Oc-l 1,362 Ma Oc 5, 20 12:00 3.7 1.8 50 Ma Oc 12 20 9:00 0%No 1,49 Sa Nov 28, 20 1:00 3.7 2.1 56%Mo No 30, 200 6:00 3.6 96De1612St De 6 20 7:00 3.8 2.2 57 TI De 8 20 7:00M 3.6 93%Ail 14,833 Ail aa Pek 3.9 1.7 43%Anal Pek 3.6 91%
Table 43 - Street and Area Lights (10) Summary Statistics (Totals - MW)
Avisll'
Ciirp.
2-82 Exhibit No. 13
case No. AVU-E-10-Q1
T. Knox, Avista
Schedule 4, Page 89 of 89
NATU GAS COST OF SERVICE STUY
2 A cost of servce study is an engieerig-economic stuy, which apportions the revenue,
3 expenses, and rate base associated with providing natul gas service to designated groups of
4 customers. It indicates whether the revenue provided by the customers recovers the cost to serve
5 those customers. The study results are used as a gude in determining the appropriate rate sprea
6 among the grups of customer.
7 There are thee basic steps involved in a cost of servce study: fuctionalization,
8 classifcation, and allocation. See flow char
9 First, the expenes' and rate base associated with the natual gas system under study are
10 assigned to fuctional categories. The uniform system of accounts provides the basic segregation
11 into production, underground storage, and distrbution. Traitionally customer accounting,
12 customer information, and sales expenses are included in the distrbution fuction and
13 admnistrtive and general expenses and general plant rate base are allocated to all fuctions. In
14 this study I have created a separate fuctonal category for common costs. Admstrtive and
15 general costs that canot be directly assigned to the other fuctions have been placed in this
16 category.
17 Second, the expenses and rate base item ar classified into thee primar cost components:
18 Demd, commodity or customer related. Demad (capacity) related costs are allocated to rate
19 schedules on the basis of each schedule's contrbution to system peak demand. Commodity
20 (energy) related costs are allocated based on each rate schedule's share of commodity
21 consumption. Customer related ites are allocated to rate schedules based on the number of
22 customers within each schedule. The number of customers may be weighted by appropriate
23 factors such as relative cost of metering equipment. In addition to these thee cost components,
24 any revenue related expense is allocated based on the proporton of revenues by rate schedule.
Exhibit No. 13
Case No. AVU-G-I0-Ol
T. Knox, Avista
Schedule 5, p. 1 of9
NATURAL GAS COST OF SERVICE STUDY FLOWCHART
Prction I
Purchaed Gas
Cos
unerundStora Distrbuton an
Customr Relons Commn
Energ IComnitRelat
Demand I
capait Relat
Cusr Relate
Residentil Interrptible
Pro Forma Results of Operations by Customer Group
Exbit No. 13
Case No. AVU-G-I0-0l
T. Knox, A vista
Schedule 5, p. 2 of9
The fial step is allocation of the costs to the varous rate schedules utilizig the alocation
2 factors selected for each specific cost item. These factors are derved from usage and customer
3 information associated with the test period results of operations.
4 BASE CASE COST OF SERVICE STUY
5 Production - Purchased Gas Costs
6 The Company has no natual gas production facilties serving the Idao jursdiction. The
7 natual gas costs included in the production fuction include the cost of gas purchased to serve
8 sales customers, pipeline tranorttion to get it to our system, and expenses of the gas supply
9 deparent.
10 The demand and commodity components of account 804 have been determined directly
1 i from the weighted average cost of gas (W ACOG) approved in the most recent purhased gas
12 adjustment (pGA) filig effective November 1,2009. The November 1, 2009 gas cost reduction
13 to customer charges was accomplished though Schedule 155 which is excluded from base
14 revenues. The allocation of these costs agrees with the gas costs computation used to determine
15 pro forma results of operations.
16 The expenses of the gas supply deparent recorded in account 813 are classified as
17 commodity related costs. The gas scheduling process includes trsporttion customer, so
18 estimate scheduling dispatch labor expenses are allocated by thoughput. The remaining gas
19 supply deparent expenses are allocated by sales volumes.
20 Underground Storage
2 i Underground storage rate base, operatig and maintence expenses ar classified as
22 commodity related and allocated to customer groups by witer thoughput. This approach was
23 proposed by commission Staff and accepted by the Idaho Public Utilties Commission in Case No.
24 A VU-G-04-0 1.
Exhbit No. 13
Case No. AVU-G-I0-Ol
T. Knox, Avista
Schedule 5, p. 3 of9
Distnbution Facilties Classifcation (peak and Average)
2 Distrbution mains and regulator station equipment (both general use and city gate stations)
3 are classified Demand and Commodty using the peak and average ratio for the distrbution
4 system. Peak demand is defied as the average of the five-day sustained pea from the most
5 recent thee year. Average daily load is calculated by dividing anual thoughput by 365 (days in
6 the year). The average daily load is divided by peak load to arve at the system load factor of
7 33.68%. This proporton is classified as commodity relate. The reaiing 66.32% is classified
8 as demand related. Meters, serces and industral measurng & reguating equipment are
9 classified as customer related distbution plant. Distrbution operatig and maintenace expenes
10 are classified (and allocated) in relation to the plant accounts they are associated with.
11 Customer Relations Distnbution Cost Classifcation
12 Customer service, customer inormation and sales expenses ar the core of the customer
13 relations fuctional unt which is included with the distrbution cost category. For the most par
14 these costs are classified as customer related. Exceptions include uncollectible accounts expense,
15 which is considered separtely as a revenue conversion item, and Demand Side Management
16 amortization expense recorded in Account 908. The demand side mangement investment costs
17 and amortzation expense are included with the distrbution fucton and classified to demad and
18 commodity by the peak and average ratio.
19 Distnbution Cost Allocation
20 Demand related distrbution costs are allocated to customer groups (rate schedules) by each
21 groups' contrbution to the thee year average five-day sustained peak Commodity relate
22 distrbution costs are allocated to customer groups by anual thoughput. Distrbution main
23 investment has been segregated into large and small mains. Small mains are defined as less than
24 four inches, with large main being four inches or greater. The small main costs use the same
Exhbit No. 13
Case No. AVU-G-IO-OI
T. Knox, Avist
Schedule 5, p. 40f9
demand and coinodity data, but large usage customers (Schedules 131, and 146) that connect to
2 large system main have been excluded from the allocations.
3 Most customer related costs are allocated by the anualized number of customers biled
4 durng the test period. Meter investment costs are allocated using the number of customers
5 weighted by the relative curent cost of meters in service at December 31, 2009. Servces
6 investment costs are allocated using the number of customers weighte by the relative curent cost
7 of tyical servce installations. Industral measng and regulatig equipment investment costs
8 are allocated by number of tubine meters which effectively excludes small usage cutomers.
9 Admiistrative and General Costs
i 0 General and intagible rate base items are allocated by the sum of Undergrund Storage
11 and Distrbution plant. Administrative and general expenes are segregated into plant related,
12 labor related, revenue related and other. The plant related items are allocated based on tota plant
13 in service. Labor related items are allocated by operating and maintenance labor expene.
14 Revenue related items are allocate by pro forma revenue. Oter adstrtive and general
15 expenses are allocated 50% by anual thoughput (classified coinodity related) and 50% by the
16 sum of operatig and maintenance expenses not including purchased gas cost or adnistrative &
17 general expenses. Whenever costs are allocated by sum of other items within the study,
18 classifications are imputed from the relationship embedded in the sumed items.
i 9 Special Contract Customer Revenue
20 Thee special contract customer receive tranporttion service from the Company. Rates
21 for these customers were individually negotiated to cover any incremental costs and retain some
22 contrbution to margi. The rates for these customers are not being adjusted in ths case. The
23 revenue from these special contrt customers has been segregated from generl rate revenue and
Exhbit No. 13
Case No. AVU-G-I0-0l
T. Knox, Avista
Schedue 5, p. 5 of9
allocated back to all the other rate classes by relative rate base. In treatig these revenues lie
2 other operatig revenues their system contrbution reduces costs for all rate schedules.
3 Revenue Conversion Items
4 In this study uncollectible accounts and commission fees have been classified as revenue
5 related and are allocated by pro fonna revenue. These items var with revenue and are included in
6 the calculation of the revenue conversion factor. Income ta expense items are allocated to
7 schedules by net income before income ta less interest expense.
8 For the fuctional sumares on pages 2 and 3 of the cost of serice study, these ites are
9 assigned to the component cost categories. The revenue related expense items have been reduce
10 to a percent of all other costs and loaded onto each cost category b that ratio. Similarly, income
11 ta items have been assigned to cost categories by relative rate base (as is net income).
12 The followig matrx outlines the methodology applied in the Company Base Case natul
13 gas cost of servce study.
Exhbit No. 13
Case No. AVU-G-I0-0l
T. Knox, A vista
Schedule 5, p. 60f9
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Sumcost AVISTA UTILITIES Natura Gas Utilit
Copany Base Case Cos of Servce General Summary Idaho Jurisdicon 15-Mar-10
AVU-G1 Method For the Year Ended Decembe 31, 2009
(b)(e)(d)(e)(I)(g)(h)0)(k)
Residental Large Firm Interpt Transport
Sysem Serv Serv Servic Serce
Line Desption Total Soh 101 Sc 111 Sc 131 Soh 146
Plant In Service
1 Proucton Plant
2 Underground Storage Plant 9,012,000 6,697,142 2,019,026 38,802 257,030
3 Distrbution Plant 145,902,000 123,149,194 21,127,047 35,203 1,269,555
4 Intangible Plant 2,070,000 1,736,108 308,445 5,258 20,189
5 General Plant 14,846,000 12,443,670 2,218,177 37,855 146,299
6 Total Plant In Servce 171,830,000 144,026,114 25,672,694 438,118 1,693,073
Accm Depreaton
7 Proucton Plant
8 Underground Storage Plant (3,522,000)(2,617,325)(789,60)(15,184)(100,451)
9 Distrbution Plant (50,348,000)(43,188,768)(6,846,574)(111,165)(401,492)
10 Intangible Plant (953,000)(798.959)(142,256)(2,427)(9,358)
11 General Plant (4,703.00)(3,941,976)(702,687)(11,992)(46,345)
12 Totl Accmulate Depreciation (59,526,000)(50,547,029)(8,280,577)(140,748)(557,646)
13 Net Plant 112,304,000 93,479,08 17,392,117 297,370 1,135,427
14 Acmlulate Deferr FIT (20,027,000)(16,786,423)(2,992,184)(51,063)(197,330)
15 Miscellaneous Rate Base 9,092,000 6,894,202 1,929,679 36,573 231,546
16 Total Rate Base 101,369,000 83,586,865 16,329,612 282,880 1,169,64
17 Revenue From Retail Rates 70,695,00 54,454,987 15,559,532 285,437 395,044
18 Oter Operating Revenues 135,00 111,630 21,487 371 1,512
19 Total Revenues 70,830,00 54,566,617 15,581,019 285,808 396,556
Operang Exnss
20 Purchase Gas Cos 43,739,00 32,350,162 11,167,655 216,750 4,433
21 Underground Storge Expenses 218,000 162,004 48,84 939 6,218
22 Distrbuton Expeses 3,767,00 3,187,444 517,030 6,392 56.134
23 Customer Acunting Expenses 2,147,000 2,04,741 96,933 1,337 1,990
24 Customer Infotion Expnses 242,00 214,749 23,478 425 3,348
25 Sales Exnse 190,000 187,330 2,649 3 18
26 Admin & General Exnses 5,083,000 4,066,188 879,177 17,415 120,220
27 Total O&M Exnss 55,386,000 42,214,618 12,735,761 243,261 192,360
28 Taxes Oter Than Income Taxes 922,000 771,509 138,775 2,375 9,340
29 Deprecaton Expense
30 Underground Storage Plant Depr 163,000 121,131 36,518 702 4,649
31 Distrbution Plant Depreciation 3,457,000 2,989,983 433,214 6,457 27.34
32 General Plant Depration 94,00 791,245 141,045 2,407 9,303
33 Amrtzation of Intangible Plant 369,00 309,313 55,115 94 3,632
34 Total Dep & Amort Expese 4,933,000 4,211,672 665,893 10,50 44,929
35 Incoe Tax 2,562,000 1,878.721 628,231 8,413 46,635
36 Total Operating Expenses 63,803,000 49,076,521 14,168,661 264,555 293,264
37 Net Income 7,027,000 5,490,096 1,412,35 21,253 103,292
38 Rate of Retum 6.93%6.57%8.65%7.51%8.83%
39 Retum Ratio 1.00 0.95 1.25 1.08 1.27
40 Interest Expense 3,694,000 3,045,999 595,069 10,308 42,623
Exibit No. 13
Ca No. AW-G1D-1
T. Knx, Avita
Scule 6, p. 1 of 4
Sumcost AVISTA UTLITIES Natural Gas Utlit
Copany Base case Summry by Funcn wi Margin Analys Idaho Juriic 15-ar-10
AVU-G-01 Method For the Year Ended Dember 31, 2009
(b)(e)(d)(e)(f)(g)(h)OJ (k)
Residentil Large Firm Intrrt Transpo
System Sø Servce Sece Serv
Lina Desption Totl Sc 101 Sc 111 Sch 131 Sch 146
Functal Cos Compoents at Currnt Ra
1 Prouclon 44,016,692 32,555,546 11,238,557 218,126 4,461
2 Underground Stoe 1,594,691 1,101,480 430,124 7,238 55,848
3 Dlslrbution 17,722,20 14,86,955 2,629,089 36,703 187,453
4 Comon 7,361,417 5,929,00 1.261,762 23,370 147,281
5 Totl Currnt Rate Revnue 70,695,000 54,45,987 15,559,53 285,437 395,04
6 Exclud Co of Gas wi Revnua Exp.43,60,089 32,25,929 11,134,434 215,725 0
7 Totl Margin Revenue at Currnt Ra 27,090,911 22,201,058 4,45,098 69,711 395,04
Margin per Therm at Currnt Rate
8 Proucon $0.00532 $0.00550 $0.0050 $0.00 $0.00134
9 Underground Strae $0.02056 $0.02 $0.02271 $0.01657 $0.01681
10 Dislrbutn $0.22853 $0.27106 $0.138 $0.08405 $0.0562
11 Commo $0.0992 $0.1089 $0.063 $0.05352 $0.043
12 Total Currnt Margin Melded Rate perTherm $0.3433 $0.4073 $0.2 $0.15965 $0.11891
Functnal Cos Components at Unlfmi Currnt Retrn
13 Proucn 44,016,692 32,55,548 11,238,557 218,126 4,461
14 Undergrond Storage 1,558,757 1,158,36 349,220 6,711 44,457
15 Dislutln 17,752,704 15,29,071 2,26,146 34,588 162.89
16 Common 7,36,847 5,987,497 1,212,572 23,086 143,693
17 Total Unifrm Currnt Cost 70,695,00 5499,485 15,06,49 282,511 355,510
18 Exclude Co of Gas w I Revenue Exp.43,60,089 32,253,929 11,134,434 215,725 0
19 Total Unif Currnt Margin 27,09,911 22,742,555 3,926,06 66,786 35,510
Margin per Therm at Uniform Currnt Retm
20 Proucon $0.00532 $0.00550 $0.005 $0.00 $0.00134
21 Underground Storae $0.02010 $0.2112 $0.0184 $0.01537 $0.1338
22 Dislbutlon $0.22892 $0.2768 $0.11935 $0.07921 $0.04903
23 Commo $0.0999 $0.10915 $0.063 $0.0587 $0.0425
24 Totl Currnt Unifrm Margin Melded Ra pe $0.333 $0.4146 $0.2073 $0.15295 $0.10701
25 Margin to Cost Raio at Currt Ra 1.0 0.98 1.13 1.04 1.11
Functional Cost Components at Propoed Rat26 Prouc 44,016,54 32,555,438 11,238,519 218,126 4,461
27 Underground Storage 1,875,805 1,354,429 455,201 8,227 57,949
28 Dlslrbutn 19,739,726 16,763,625 2,743,439 40,681 191,980
29 Common 7,637,925 6,189,073 1,277,005 23,90 147,943
30 Totl Propose Rate Revenue 73,270,00 58,862,56 15,714,164 290,938 40,333
31 Exclude Cost of Gas w I Revenue Exp.43,60,942 32,253,821 11,134,397 215,725 0
32 Totl Margin Revenue at Proos Ra 29,666,058 24,80,744 4,57,767 75,214 402,333
Margin per Therm at Propoed Ra
33 Proucn $0.0053 $0.0055 $0.0050 $0.00550 $0.00134
34 Undergrond Stge $0.02419 $0.02469 $0.02404 $0.0188 $0.01744
35 Dlslrbun $0.25454 $0.30560 $0.14468 $0.0917 $0.5779
36 Commo $0.099 $0.11283 $0.06744 $0.05474 $0.0453
37 Total Propo Margin Melded Rate per Therm $0.3854 $0.4462 $0.24185 $0.1725 $0.12110
Functnal Coat Components at Unlfomi Prpo Return
38 Pruct 44,016,54 32,555.438 11,238,519 218.126 4,461
39 Underground Strage 1,858,949 1,381,452 416,474 8,00 53,019
40 Dislbuton 19,754,017 16.96.041 2.56,83 39,784 181,353
41 Common 7,64,491 6,216,859 1,253,459 23,783 146,390
42 Totl Uniform Propo Co 73,270,00 57.119,79 15,475,290 289,697 385,223
43 Exclude Cost of Ga w I Revenue Ex.43,603.942 32.253,821 11,134,397 215,725 0
44 Totl Unifrm Propo Margn 29,66,058 24,86,969 4,3,894 73,972 385,223
Margin per Therm at Unifrm Prpo Retum
45 Prouclon $0.00532 $0.00550 $0.00550 $0.00550 $0.00134
46 Undergrond Storage $0.02397 $0.02518 $0.02199 $0.01833 $0.01596
47 Dislbutlo $0.25473 $0.30929 $0.13555 $0.09111 $0.0549
48 Common $0.09852 $0.11333 $0.0619 $0.0547 $0.0406
49 Total Propo Unifrm Margn Melded Rate P'$0.38254 $0.451 $0.292 $0.1691 $0.11595
50 Margin to Cost Rati at Proposed Rate 1.00 0.99 1.6 1.2 1.04
51 Currnt Margin to Propoed Cost Ratio 0.91 0.89 1,02 0.94 1.03
Exibit No. 13
case No. AW-G-10-1
T. Knx, Avist
Schedle 6, p. 2 of 4
Sumcost
Company Base Case
AVU-G-01 Metod
AVlSTA UTILITIES Natural Gas Utlit
Summary by Classbtl wit Unit Cost Analyis Idaho Jurlicn
For the VearEnde Damber31, 2009
(b)(e) (d) (e)
Line Desption
(f)
System
Total
Cost by Classlftl at Currnt Retrn by SCule1 Comoity 44,593.3592 Demand 13,596.7313 Customr 12,50,9104 Total Currnt Rate Revnue 70.69.00
Revenue per Therm at Currt Raes
5 Commoit
6 Demand
7 Customer
8 Total Revenue per Then at Currnt Rates
Co per Unit at Currnt Rate
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10 Demand Cost per Peak Day Therms
11 Customer Cot pe Customer per Month
Cost by Classlftlon at Unlfomi Curr Rern
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13 Demand
14 Customr
15 Total Unifrm Currnt Cost
Cot per Therm at Currnt Retum
16 Commit
17 Demand
18 Cusomr
19 Totl Co per Therm at Currnt Retum
Co per Unit at Unifor Currnt Retum
20 Commoit Co per Then
21 Demand Cost per Peak Day Therm
22 Customer Cos per Custome per Month
23 Revenue to Co Rato at Currnt Ra
$0.5750
$0.17533
$0.16125
$0.91161
$0.57503
$21.55
$14.18
44,492.354
13,54,115
12.656,531
70,695.00
$0.57373
$0.1746
$0.16320
$0.91161
$0.57373
$21.47
$14.36
1.00
(a)
Resid~ntllse~
Sc 101',
~
32.629.50 \
10.163.928
11.661,559
54.454.987
$0.59484
$0.18529
$0.21259
$0.99272
$0.59484
$20.89
$13.42
32,772.272
10.34,188
11.88,025
54,99.485
$0.59744
$0.18850
$0.21665
$1.00259
$0.59744
$21.25
$13.67
0.99
(h)
Large FinServ
Sc 111
11,474.728
3,317.232
767.572
15.559,532
$0.60596
$0.17518
$0.0453
$0.82167
$0.60596
$26.67
$62.45
11.254,58
3.104,716
701.192
15,06,494
$0.593
$0.16395
$0.03703
$0.79532
$0.59433
$24.96
$57.05
1.3
il
Intnupl
Servce
Sch 131
259,571
24.700
1.166
285.437
$0.5945
$0.0567
$0.00267
$0.653
$0.5945
$11.32
$97.16
257,96
23,428
1,119
28.511
$0.5977
$0.0535
$0.0056
$0.6499
$0.59077
$10.74
$93.25
1.1
15oar-10
(k)Transserv
Sch 146
22.561
90.871
74,612
395.44
$0.06910
$0.02735
$0.02246
$0.11891
$0.0610
$5.14
$888.24
207.532
77,783
70,195
355.510
$0.06247
$0.02341
$0.02113
$0.10701
$0.0647
$4.40
$835.65
1.11
Cost by Ctasslfcation at Propo Return by Schedule24 Comoit 45.303.36425 Demand 14,451,0926 Customr 13.515.53827 Totl Propo Rae Revenue 73.270,00
Revenue per Therm at Propo Rates
28 Commoit
29 Deand
30 Custmer
31 Totl Revenue pe Therm at Propoed Rates
Co per Unit at Pro Rates
32 Commoit Cost pe Therm
33 Demand Cost pe Peak Day Therm
34 Customer Co per Cusmer per Mon
Cost by Classiftion at Unlfmi Propo Return
35 Commoit
36 Demand
37 Custmer
38 Total Uniform Pro Cost
Cost per Therm at Propo Retm39 Comoit
40 Demand
41 Customr
42 Total Cost per Thrm at Prose Return
Cot per Unit at Uniform Propo Return
43 Commoit Cos per Therm
44 Demand Co pe Peak Day Ther
45 Custmer Co pe Custr per Mont
46 Revenue to Cost Ra at Proed Ras
47 Currnt Revenue to Propoed Cost Ratio
$0.5818
$0.1865
$0.17428
$0.9481
$0.5818
$22.91
$15.33
45.255.594
14.426.897
13,587,50
73,270.00
$0.5857
$0.186
$0.17521
$0.9481
$0.58357
$22.87
$15.41
1.00
0.96
33.264,224
10,947,630
12,650,712
56.862.565
$0.601
$0.19958
$0.23062
$1.03661
$0.601
$22.50
$14.55
33.332,04
11.031,358
12,756.388
57,119,790
$0.60764
$0.20110
$0.23255
$1.04129
$0.60764
$22.67
$14.68
1.0
0.5
11,542,926
3.383.093
788,145
15,714,164
$0.60
$0.1786
$0.04162
$0.8298
$0.6056
$27.20
$64.12
11.437.551
3,281,369
756.371
15.475,290
$0.60
$0.17328
$0.0399
$0.81722
$0.6000
$26.38
$61.54
1.2
1.1
262,593
27,091
1,254
29D,38
$0.60137
$0.0604
$0.0087
$0.6629
$0.60137
$12.42
$104.53
261,911
26,551
1,23
289.697
$0.5981
$0.0681
$0.00283$0.66
$0.59981
$12.17
$102.87
1.00
0.99
233.622
93,284
75,427
402,333
$0.07032
$0.02808
$0.0270
$õ.12110
$0.07032
$5.28
$897.94
224.088
87,620
73,515
385.223
$0.06745
$0.02637
$0.02213
$0.11595
$0.06745
$4.96
$875.18
1.4
1.03
Exit No. 13
Case No. AVU-G10.(1
T. Knx, Avis
Schedle 6, p. 3 of 4
Sumco AVISTA UTILITIES Natural Gas Utit
Copany Base Case Custome Cos Analysis Idaho Juricn 15-ar.10
AVU-G1 Method For th Year Ended Dember 31. 200
(b)(e)(d)(e)(I)(g)(h)Ol (k)
Residential Large Firm Interrpt Transport
SySem serv servce servic serv
Line Descrption Totl Sch 101 SCh 111 SC 131 Sch 146
Meter, Servces, Meter Readlng & Billng Cos by Schedule at Requestd Rat of Return
Rae Base
1 serv 45.320.00 44.664.982 631,58 1.850 21,582
2 Servces Accm. Depr.(20.150.00)(19.858.768)(280,813)(82)(9.59)
3 Total Services 25,170.00 24.80.213 350.773 1.027 11.986
4 Meters 18,678.00 16.221,340 2,351,127 5.032 100,501
5 Meters Ac. Depr.(4.476.00)(3.887.285)(563,425)(1.206)(24.08)
6 Total Meters 14,202,000 12.33.054 1.787,702 3,82 76.417
7 Total Rate Base 39.372.00 37.140.268 2.138.475 4.854 88.403
8 Retm on Rate Base ii 8.55%3,366.30 3.175.493 182.840 415 7.558
9 Revenue Conversion Fact 0.63676 0.63676 0.63676 0.636 0.63676
10 Ra Base Revenue Requirement 5,286,58 4,986,923 287,139 652 11,870
Exnses
11 Services Depr Exp 1.330,000 1.310.777 18.535 54 633
12 Meters Depr Exp 656,000 569.718 82.575 177 3.530
13 Servics Maintenance Exp 316,00 311.433 4,404 13 150
14 Meters Maintenance Exp 282.000 244,909 35.497 76 1.517
15 Meter Reading 174.00 171.555 2,426 2 17
16 Billing 1,480.00 1,459.205 20,634 20 141
17 Total Expense 4.238.00 4,067,598 164,071 342 5,989
18 Revenue Conversion Fact 0.9938 0.99384 0.99384 0.99384 0.9938
19 Expense Revenue Requireent 4,264268 4,092,810 165,088 34 6,026
20 Total Meter, Service, Mete Readlng, and 9,55,851 9,079,732 452,2 99 17,_
21 Total Customer Bills 881.591 869,2 12.291 12 84
22 Average Unit Cost per Month $10.83 $10.45 $36.79 $83.2 $213.05
Fixed Cos per Custoer
23 Total Custoer Related Cost 13,587,50 12,756,388 756.371 1.234 73,515
24 Customer Related Unit Cos per Month $15.41 $14.68 $61.54 $102.87 $875.18
25 Other Non-as Cos 16,078,549 12.109,561 3,584.522 72,738 311,708
26 Oter Non-as Unit Cot per Month,$18.24 $13.93 $291.64 $6.061.48 $3.710.81
27 Totl Fix Unit Cot per Month $33.65 $28.1 $353.18 $6,164.34 $4585.9
ExhIbi No. 13
Case No. AVU1Ð-1
T. Knox Avi
Schedle 6, p.4 of 4