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HomeMy WebLinkAbout20100323Kalich Di.pdfr~::: 1 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: (509) 495-4316 FACSIMILE: (509) 495-8851 !H~'1 -,f ...v /I: 04 BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION ) CASE NO. AVU-E-10-01 ) ) ) ) ) ) ) DIRECT TESTIMONY OF CLINT G. KALICH 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 ONLY) 1 2 I. INTODUCTION Q.Please state your nam, the nam of your 3 employer, and your business address. 4 5 A.My name is Clint Kalich. I am employed by Avista Corporation at 1411 East Mission Avenue,Spokane, 6 Washington. 7 8 Q.In what capacity are you emloyed? A.I am the Manager of Resource Planning & Power 9 Supply Analyses, in the Energy Resources Department of 10 Avista Utilities. 11 Q.Please state your educational background and 12 professional exprience. 13 A.I graduated from Central Washington University in 14 1991 with a Bachelor of Science Degree in Business 15 Economics. Shortly after graduation, I accepted an analyst 16 posi tion with Economic and Engineering Services, Inc. (now 17 EES Consulting, Inc.), a Northwest management-consulting 18 firm located in Bellevue, Washington.While employed by 19 EES, I worked primarily for municipalities, public utility 20 districts, and cooperatives in the area of electric utility 21 management.My specific areas of focus were economic 22 analyses of new resource development, rate case proceedings 23 involving the Bonneville Power Administration, integrated 24 (least-cost) resource planning, and demand-side management 25 program development. Kalich, Di i Avista Corporation 1 In late 1995,I left Economic and Engineering 2 Services, Inc. to join Tacoma Power in Tacoma, Washington. 3 i provided key analytical and policy support in the areas 4 of resource development, procurement, and optimization, 5 hydroelectric operations and re-licensing, unbundled power 6 7 supply rate-making,contract negotiations, and system operations.I helped develop, and ultimately managed, 8 Tacoma Power's industrial market access program serving 9 one-quarter of the company's retail load. 10 In mid-2000 I joined the Company and accepted my 11 current position assisting in resource analysis, dispatch 12 modeling,resource procurement,integrated resource 13 planning, and rate case proceedings. Much of my career has 14 invol ved resource dispatch modeling of the nature described 15 in this testimony. 16 Q.What is the scope of your testimony in this 17 proceeding? 18 A.My testimony will describe. the Company's use of 19 the AURORAXMP dispatch model, or "Dispatch Model."I will 20 explain the key assumptions driving the Dispatch Model's 21 market forecast of electricity prices.The discussion 22 includes the variables of natural gas, Western Interconnect 23 loads and resources, and hydroelectric conditions.I will 24 describe how the model dispatches our resources and Kalich, Di 2 Avista Corporation 1 contracts in a manner that maximizes benefits to customers 2 and tracks their values for use in pro forma calculations. 3 I will then present the modeling results provided to 4 Company witness Mr. Johnson for his power supply pro forma 5 adjustment calculations.Addi tionally, in support of 6 Company witness Ms. Knox, I detail the Company's demand 7 classification calculations. 8 Q.Are you sponsoring any exhibi ts in this 9 proceeding? 10 A.Yes. I am sponsoring ExhibitS, Schedules 1 and 11 2, as well Confidential Schedule 3. Schedule 1 provides a 12 forecast of Company load and resource positions from 2011 13 through 2020.Schedule 2 is the spreadsheet used to 14 calculate the demand classification. Confidential Schedule 15 3 provides summary output from the Dispatch Model.All 16 information contained in the exhibit was prepared by me or 17 prepared under my direction. 18 II. THE DISPATCH MODEL 19 Q.What model is the Comany using to dispatch its 20 portfolio of resources and obligations? 21 A.The Company uses EPIS, Inc.'s Dispatch Model for 22 determining power supply costs.The model optimizes 23 dispatch of Company-owned resources and contracts in each 24 25 hour of the pro forma year.The pro forma period is October 1, 2010 through September 30, 2011.It reflects Kalich, Di 3 Avista Corporation 1 true system operations by evaluating future resource 2 decisions on an hourly basis. 3 Q.What AURORA version and database is the Company 4 using for this case? 5 A.The Company is using AURORAxMP version 9.6.1033, 6 and its associated database (North_American_DB_2009-02). 7 8 9 Q.Please briefly describe the Dispatch Model. The Dispatch Model was developed by EPIS, Inc. ofA. Sandpoint,Idaho.It is a fundamentals-based tool 10 containing demand and resource data for the entire Western 11 Interconnect.It employs multi-area,transmission- 12 constrained dispatch logic to simulate real market 13 condi tions.Its true economic dispatch captures the 14 dynamics and economics of electricity markets--both short- 15 term (hourly, daily, monthly) and long-term. On an hourly 16 basis, the Dispatch Model develops an available resource 17 stack, sorting resources from lowest to highest cost.It 18 then compares this resource stack with load obligations in 19 the same hour to arrive at the least-cost market-clearing 20 price for the hour.Once resources are dispatched and 21 market prices are determined, the Dispatch Model singles 22 out Avista resources and loads and values them against the 23 marketplace. Kalich, Di 4 Avista Corporation 1 Q.What experience does the Comany have using 2 AUR0RA ? 3 4 A.The Company purchased a license to use the Dispatch Model in April 2002.AURORA~ has been used for 5 numerous studies, including all of our integrated resource 6 plans and rate filings after 2001. The tool is also used 7 for various resource evaluations, market forecasting, and 8 requests-for-proposal evaluations. 9 Q. Who else uses AUR0RA? 10 A. AURORAXMP is used all across North America and in 11 Europe. In the Northwest specifically, AURORAXMP is used by 12 the Bonneville Power Administration, the Northwest Power 13 and Conservation Council, Puget Sound Energy, Idaho Power, 14 Portland General Electric, Seattle City Light, Grant County 15 PUD, Snohomish County PUD, and Tacoma Power. 16 Q.What benefits does the Dispatch Model offer for 17 this type of analysis? 18 A.The Dispatch Model generates hourly electricity 19 prices across the Western Interconnect, accounting for its 20 specific mix of resources and loads.The Dispatch Model 21 reflects the impact of regions outside the Northwest on 22 23 Northwest market prices,limited by known transfer (transmission) capabilities.Ultimately, the Dispatch 24 Model allows the Company to generate price forecasts in- 25 house instead of relying on exogenous forecasts. Kalich, Di 5 Avista Corporation 1 The Company owns a number of resources, including 2 hydroelectric plants and natural gas-fired peaking units, 3 which serve customer loads during more valuable on-peak 4 hours.By optimizing resource operation on an hourly 5 basis, the Dispatch Model is able to appropriately value 6 the capabilities of these assets. For example, actual 2008 7 and 2009 on-peak prices were 23 percent higher than off- 8 peak prices.2007 on-peak prices were 25 percent higher. 9 Forward on-peak prices for 2011 were 27 percent higher than 10 off-peak prices at the time this case was prepared.For 11 comparison, Dispatch Model on-peak prices for the pro forma 12 period average 29 percent higher than off-peak prices. In 13 summary, the Dispatch Model appropriately values the energy 14 from Avista's resources during on-peak periods in a manner 15 similar to that recently experienced in the Northwest 16 region. 17 Q.On a broader scale, what calculations are being 18 performd by the Dispatch Model? 19 A.The Dispatch Model's goal is to minimize overall 20 system operating costs across the Western Interconnect, 21 including Avista's portfolio of loads and resources.The 22 dispatch model generates a wholesale electric market price 23 forecast by evaluating all Western Interconnect resources 24 simultaneously in a least-cost equation to meet regional 25 loads. As the Dispatch Model progresses from hour to hour, Kalich, Di 6 Avista Corporation 1 it "operates" those least-cost resources necessary to meet 2 load.With respect to the Company's portfolio, the 3 Dispatch Model tracks the hourly output and fuel costs 4 associated with portfolio generation.It also calculates 5 hourly energy quantities and values for the Company's 6 contractual rights and obligations.In every hour the 7 Company's loads and obligations are compared to available 8 resources to determine a net position.This position is 9 balanced using the simulated wholesale electricity market. 10 The cost of energy purchased from or sold into the market 11 is determined based on the electric market-clearing price 12 for the specified hour and the amount of energy necessary 13 to balance loads and resources. 14 Q.How does the Dispatch Model determne electric 15 market prices? 16 A.The Dispatch Model calculates electricity prices 17 for the entire Western Interconnect, separated into various 18 geographical areas such as the Northwest and Northern and 19 Southern California. The load in each area is compared to 20 available resources, including resources available from 21 other areas that are linked by transmission corridors, to 22 determine the electricity price in each hour. Ultimately, 23 the market price for an hour is set based on the last 24 resource in the stack to be dispatched.This resource is 25 referred to as the "marginal resource."Given the Kalich, Di 7 Avista Corporation 1 prominence of natural gas-fired resources on the margin, 2 this fuel is a key variable in the determination of 3 wholesale electricity prices. 4 Q.How does the Dispatch Model operate regional 5 hydroelectric projects? 6 A.The model begins by "peak shaving" loads using 7 system hydro resources.When peak shaving, the Dispatch 8 Model determines which hours contain the highest loads and 9 allocates to them as much hydroelectric energy as possible. 10 Remaining loads are then met wi th other available 11 resources. 12 Q.Has the Company made any modifications to the 13 dataase for this case? 14 A.Yes. Avista's portfolio of resources is modified 15 to reflect actual operating characteristics, natural gas 16 prices are modified to match projected forward prices over 17 the pro-forma period, regional resources are modified where 18 better information is known, and Northwest hydro data is 19 replaced with Northwest Power Pool data. 20 21 22 III . HYDRO MODELING ASSUMTIONS Q. How has the Company modeled hydroelectric 23 generation for this case? 24 A. As in the past, Avista uses historical stream flow 25 data from the Northwest Power Pool (NWPP) to determine Kalich, Di 8 Avista Corporation 1 hydroelectric generation for its Clark Fork and Spokane 2 Ri ver systems.Certain adjustments to the NWPP data are 3 necessary to yield a proper estimate of generation from the 4 model.These adjustments include changes to address the 5 NWPP's tendency to overstate generation in high-flow periods,to account for recent upgrades at our6 7 8 hydroelectric projects,to maintain year-to-year consistency in project operations,to account for 9 encroachment on our Mid-Columbia project shares, and to 10 allow for 2000 irrigation depletion levels. 11 Q. Why does the NWP overstate generation on the 12 Company's hydroelectric facilities? 13 A. The NWPP's regional hydroelectric model is in many 14 ways simplified and therefore does not account for various 15 project operating characteristics.The NWPP model is not 16 granular enough to account for intra-month flow changes. 17 This impact is most significant during the spring months. 18 For example, the Noxon Rapids project has a maximum turbine 19 flow capability of approximately 50,000 cubic feet per 20 second (cfs).The NWPP model will use all water up to 21 50,000 cfs in a given month to generate power. However, a 22 50,000 cfs month is not comprised of 28, 29, 30 or 31 days 23 of 50, OOO-cfs flows.Instead it is made up of flows that 24 range below and above 50,000 cfs. For example, where flows 25 are 20,000 cfs for the first half of the month and 80,000 Kalich, Di 9 Avista Corporation 1 cfs the second half, the average flow for the period is 2 3 50,000 cfs.The NWPP would assume all of this water went through the generation turbines and made power.In fact, 4 the project would in the first half of the month generate 5 with 20,000 cfs and in the second half of the month it 6 would generate with 50,000 cfs. The additional 30,000 cfs 7 in the second half of the month (80,000 - 50,000 = 30,000), 8 or nearly 30 percent of the monthly total, would be spilled 9 in the actual operation of the project. 10 Q. Does Noxon Rapids have storage capability to 11 account for such variations in flows? 12 A. Noxon does have some storage, but not near enough 13 to convert all of the intra-month variability of flows into 14 electric energy.A study completed by BorisMetrics 15 explained that on average our hydroelectric dams on the 16 Spokane and Clark Fork Rivers generate 3.7 aMW less than 17 the NWPP estimates.This study was reviewed and accepted 18 in previous cases before this Commission. 19 Q. Is the Company now experiencing an even greater 20 difference between actual hydroelectric generation and 21 generation from the NWP model, than that quantified by 22 BorisMetrics? 23 A. Yes.Relative to the NWPP data used in previous 24 cases, hydro generation on the Clark Fork projects has been 25 overstated by a significant amount on average.Over the Kalich, Di 10 Avista Corporation 1 past 20 years actual hydroelectric generation has been 2 319.72 aMW, 3.2 percent (10 aMW) below the NWPP model 3 resul ts for the 50-year period used in rate modeling. Over 4 the past 10 years generation has been 299.08 aMW, or 10.3 5 percent (31 aMW) below the NWPP modeled results.Lower 6 results in the past 10 years have been driven primarily by 7 lower-than-average stream flows; however, not all of the 8 reduction is driven by lower stream flows. A portion of 9 the overstatement is caused by the design limitations of 10 the model itself. 11 Q. Please provide additional detail as to why the 10- 12 and 20-year averages were below the 50-year NWP study 13 period average? 14 A. There are a number of reasons. Flows in the 1990s 15 were high relative to history, whereas flows in the most 16 recent 10 years have been low relative to average. Also, 17 half of the 20-year average is affected by the use of 18 operating assumptions from our old Clark Fork operating 19 license.New licensing requirements implemented in 2001 20 have negatively affected power production on the Clark Fork 21 projects. Poor hydroelectric conditions also have played a 22 role in a number of recent years.Additionally, the 23 Company continues to shift reserve obligations to the Clark 24 Fork as we lose Mid-Columbia generation capacity, and as we 25 respond to a marketplace greatly affected by new variable Kalich, Di 11 Avista Corporation 1 generation resources (i. e. , wind).Upgrades at Cabinet 2 Gorge and Noxon Rapids have helped to offset these losses, 3 but the statistics explain that generation levels continue 4 to fall over time. 5 Q. How is hydro generation calculated in this 6 proceeding? 7 8 A. For our Mid-Columbia shares, and for the Spokane River,there is no change from previous filings. 9 Generation data are taken from the NWPP Headwater Benefits 10 Study, adjusted downward by the results of the BorisMetrics 11 study for the Spokane River and Encroachment for the Mid- 12 Columbia projects.For the Clark Fork River projects we 13 continue to use NWPP data for the historical record (1929- 14 1978). However, instead of using energy levels calculated 15 by their model, and adjusted by the BorisMetrics study for 16 overstated generation, the NWPP flow data is used as an 17 input in a new model: the Clark Fork Optimization Package. 18 Q. Please describe. the Clark Fork Optimzation 19 Package. 20 A. The Clark Fork Optimization Package is a mixed- 21 integer linear programming-based system emulating the 22 operation of the Company's Clark Fork projects.It was 23 developed in support of the Company's system operations, 24 financial forecasting,and hydro upgrade efforts. 25 Operating on an hourly time-step, it accurately represents Kalich, Di 12 Avista Corporation 1 individual turbine and reservoir operations.License 2 constraints (e.g., minimum flows, elevation limits) are 3 honored in all periods.The Clark Fork Optimization 4 Package is comprised of four components which are described 5 below. 6 Q. In wha t programng language was the model 7 developed? 8 A. The Clark Fork Optimization Package is a suite of 9 database (Microsoft Access) and spreadsheet (Microsoft 10 Excel)programs.The Excel programs benefi t from 11 WhatsBEST!, an Excel Add-In for Linear, Nonlinear, and 12 Integer Modeling and Optimization.WhatsBEST!was 13 developed by Lindo Systems of Chicago, Illinois in 1979. 14 Q. What is the first component of the Clark Fork 15 Optimization Package? 16 A. The first component is the Clark Fork Water Budget 17 Model. It looks over the long-term record and optimizes 18 water flow through the projects to maximize generation 19 20 values.This step is necessary to recognize the storage capabilities inherent in a hydro project.The long-term 21 optimization is simplified to provide present-day computers 22 wi th the ability to efficiently solve the equations. Each 23 project is represented by one power curve instead of 24 mul tiple curves representing individual turbines.Model Kalich, Di 13 Avista Corporation 1 granularity is daily instead of hourly. Project elevation 2 and flow constraints are retained. 3 Outputs of the Clark Fork Water Budget Model are 4 weekly beginning and ending project elevations for the 5 Noxon Rapids and Cabinet Gorge projects. These elevations 6 are exported to the second module of the Clark Fork 7 Optimization Package--the Clark Fork Optimization Model 8 Input Database. It is discussed below. 9 Q. What is the source for hydroelectric flows in the 10 Clark Fork Water Budget Model? 11 A. The source is the 2007-08 NWPP Headwater Benefits 12 Study. To shape the monthly NWPP data Avista used a daily 13 study obtained from the Bonneville Power Administration 14 (BPA) .The BPA data were from the U. S. Army Corp of 15 Engineers study re-creating daily historical flows on the 16 Clark Fork River back to 1929 based on today's river 17 system. 18 Because of the need for daily inflow values that 19 the NWPP does not provide, and the fact that the BPA data 20 is daily, Avista elected to shape the NWPP monthly data 21 using the daily shapes of the BPA study in each month. 22 Q. What data does the Clark Fork Optimzation Model 23 Input Database contain? 24 A. The Clark Fork Optimization Model Input Database 25 contains the daily inflows and side flows into the Kalich, Di 14 Avista Corporation 1 Company's Clark Fork River projects described above.It 2 also contains representative hourly market prices enabling 3 the model to maximize generation levels in the higher- 4 valued on-peak periods. 5 Q. What is the third elemnt of the Clark Fork 6 Optimization Package? 7 8 A. The third element is the Clark Fork Optimization Model itself.This hourly model uses a mixed-integer 9 optimization routine to maximize the value of the Clark 10 Fork proj ects over time.Each project is represented in 11 detail, including individual turbine efficiency curves, 12 physical and license-constrained reservoir elevations, 13 tailrace elevations,and minimum and maximum flow 14 constraints. 15 The Clark Fork Optimization Model shapes 16 generation into the most economically beneficial time 17 periods using the projects' storage reservoirs.It also 18 maximizes the value of generation by flowing water through 19 the turbines at their most economically efficient points on 20 the power curves. 21 Q. What is the fourth elemnt of the Clark Fork 22 Optimzation Package? 23 A. The fourth element is the Clark Fork Optimization 24 Model Output Database. This database contains results from 25 the Clark Fork Optimization Model, including hourly turbine Kalich, Di 15 Avista Corporation 1 discharge and spill flows, hourly generation levels, hourly 2 generation values, and hourly reservoir elevations. 3 Q. How did the Company ensure the Clark Fork 4 Optimization Package accurately reflects the operations and 5 value of the Clark Fork projects? 6 A. Once the Clark Fork Optimization Package models 7 were completed, it was benchmarked against the Company's 8 2000-2009 actual results at the Clark Fork projects to 9 ensure its accuracy. 10 11 Q. How did the results comare? A. The Clark Fork Optimization Package initially 12 over-estimated generation relative to the 2000-2009 periods 13 by approximately 6 percent.This result was expected, as 14 Avista does not operate its projects in isolation. Instead 15 the Company uses the Clark Fork projects to meet its load 16 17 and reserve needs.There are also times where units are down for maintenance or forced outage.To reconcile the 18 Clark Fork Optimization Package with actual operating 19 history, the power curves for each project were therefore 20 reduced by the 6 percent difference.After the 21 benchmarking process, the model generated just over 100 22 percent of actual generation levels during the 2000-2009 23 period. 24 Q. How is the generation then used for ratemking 25 purposes? Kalich, Di 16 Avista Corporation 1 A. The generation levels for each project (Mid- 2 Columbia, Spokane River, and Clark Fork) are input into the 3 dispatch model (AURORAxmp) where Avista's portfolio value 4 is quantified for ratemaking purposes. 5 Q. Are the models included in the Company's filing? 6 A. Yes.All four components of the Clark Fork 7 Optimization Package are included in my workpapers, 8 including all input and output data. 9 Q. Does the Clark Fork Optimzation Package account 10 for recent upgrades at the Noxon Rapids project? 11 A. Yes.Once the original model was benchmarked 12 against recent generation years that did not benefit from 13 upgrades at Noxon, the three newly upgraded units (1, 2, 14 and 3) were input into the model to reflect the higher 15 anticipated generation levels.As Unit 2 will not enter 16 service until April 1, 2011, all proforma periods prior to 17 April 2011 include upgrades only to Units 1 and 3. 18 Q. How much additional genera tion did the new units 19 provide based on your modeling? 20 A. The Company evaluated generation levels with the 21 old Noxon units 1 through 3, and the newly upgraded units 22 over the 50-year period for this case.Generation levels 23 from the upgrades increased by a total of 35,778 MWh (4.08 24 aMW) a year, or 1.3 percent. Kalich, Di 17 Avista Corporation 1 Q. How much additional generation does the new Unit 2 2 provide? 3 A. On an annual basis the new Unit 2 included in this 4 case generates 10,326 MWh per year on average over the 50- S year period, or 1.18 aMW. 6 Q. Why did the Company not use simlar models in this 7 case for the Spokane River and Mid-Columia projects? 8 9 A. The Clark Fork Optimization Package is the product of several years of work by Avista.The Company has not 10 yet attempted to build a model for the Mid-Columbia due to 11 those projects' significant reliance on upstream (e. g., 12 Grand Coulee Dam) projects that greatly affect their 13 14 output.A model for the Spokane River projects is under development but is not yet ready for use.The Company 15 hopes to have a working version for the Spokane River 16 system prior to its next rate proceeding.We will 17 subsequently examine a model for the Mid-Columbia projects. 18 Q. Please explain why the Company developed the Clark 19 Fork Optimzation Package. 20 A. The Clark Fork Optimization Package is the 21 culmination of nearly ten years of work by the Company to 22 bring in-house a tool to enable true optimization of our 23 hydro facilities.In 2002 the Company acquired the Vista 24 suite from Synexus Global. This tool was used to evaluate 25 system operations and support upgrades at our Noxon Rapids Kalich, Di 18 Avista Corporation 1 2 and Cabinet Gorge projects.It also was used to evaluate various Spokane River proj ect upgrades.Because of some 3 problems inherent to the Vista model, and very slow 4 solution times, it. was retired in the middle of the last 5 decade.We then evaluated other options in the 6 marketplace, and the Company acquired Riverware from the 7 University of Colorado at Boulder. After working with this 8 tool over a number of years it became apparent that it 9 cannot meet our need for efficient unit-level dispatch 10 modeling. 11 Due to the apparent lack of a strong package for 12 hydro modeling in the marketplace, the Company began 13 developing the Clark Fork Optimization Package in the 14 middle of 2009. 15 Q. How is the Company using the new Clark Fork 16 Optimzation Package in its business operations, and how 17 does it intend to use the tool into the future? 18 A. The Clark Fork Optimization Package is an 19 essential tool to assist the Company with optimizing hydro 20 system operations, both in short- and long-term planning. 21 Its results are also used for Company budgets, hydro 22 project market valuation studies, and upgrade studies. 23 Gi ven its solution efficiency, it is possible to run large 24 hydro-flow records through it, as is necessary for rate 25 filings such this. Kalich, Di 19 Avista Corporation 1 The Company anticipates using its new model to analyze 2 opportuni ties to increase the value of the Clark Fork 3 projects and lower overall system costs to customers. With 4 this model there is now a potential to analyze a 5 coordination agreement between Clark Fork River project 6 operators that would be similar to the Pacific Northwest 7 Coordination Agreement. Initiation of discussions on this 8 a potential agreement between the various parties with 9 projects on the river has been hampered to a large extent 10 by the lack of a good means to model the values of 11 coordination. 12 Q.How does the AURORA Dispatch Model operate 13 Company-controlled hydroelectric generation resources? 14 A.The Dispatch Model treats all hydroelectric 15 generation plants wi thin a load area as a single large 16 plant. The Company's hydroelectric plants are on average, 17 however, more flexible than the average plant used in each 18 load area. To account for this additional flexibility, the 19 Company algebraically extracts its plants from the region 20 and develops individual hydro operations logic for them. 21 Company-controlled hydroelectric resources are separated 22 into three river systems:the Spokane River, the Clark 23 Fork River, and individually separate the Mid-Columbia 24 projects.This separation ensures that the flexibility Kalich, Di 20 Avista Corporation 1 inherent in these resources is credited to customers in the 2 pro forma exercise. 3 Q.Please compare the operating statistics from the 4 Dispatch Model to recent historical hydroelectric plant 5 operations. 6 A.Over the pro forma period the Dispatch Model 7 generates 69 percent of Clark Fork hydro generation during 8 on-peak hours (based on the average of the 50 year hydro 9 record) . Since on-peak hours represent only 57 percent of 10 the year, this demonstrates a substantial shift of hydro 11 resources to the more valuable on-peak hours.This is 12 identical to the 5-year average of on-peak hydroelectric 13 generation at the Clark Fork through 2009.Similar 14 performance is achieved for the Spokane and Mid-Columbia 15 projects. 16 17 18 iv. OTHE KEY MODELING ASSUMTIONS Q.Please describe your update to pro form period 19 natural gas prices. 20 A.Natural gas prices for this filing are based on a 21 3-month average from October 1, 2009 to December 31, 2009 22 of the rate period forward prices.Natural gas prices 23 used in the Dispatch Model are presented below in Table No 24 i. 25 Kalich, Di 21 Avista Corporation 1 Table No. i - Pro Form Natural Gas Prices 2 3 AECO CHICAGO CIG EL PASO MALIN NECT NWPCRM 5.957 PG&E CITY 6.50 RATHDRUM 5.882 SJUAN BASIN 6.056 SOCAL 6.345 STANFIELD 6.566 SUMAS 5.90 Hen Hub 6.709 6.265 5.975 6.277 6.265 6.372 6.424 Q.What is the Company's assumtion for rate period 4 loads? 5 A.Rate period loads (October 2010 through September 6 2011) used in this case are taken from the Company's load 7 forecast completed in July 2009. As this load is generated 8 using "normal weather," it eliminates the need for a 9 weather-normalization adjustment. Removing the 2009 actual 10 (test year) generation from the Clearwater (previously 11 known as Potlatch) cogeneration facility, from the October 12 2010 to September 2011 proforma period loads, results in 13 system loads of 1,070.4 aMW as filed in this proceeding. 14 The Company's latest energy loads and resources 15 tabulation (L&R) is attached in Exhibit No.5, Schedule 1. 16 Q.Please discuss the availability assumtions for 17 your therml and gas generating facilities. 18 A.For baseload generating facilities such as Coyote 19 Springs 2, Kettle Falls Generating Station, and Colstrip, 20 we use a 5-year average through 2009 to estimate long-run 21 operating performance. The following table summarizes the Kalich, Di 22 Avista Corporation 1 average forced outage rates for each of the Company's 2 thermal and gas generation facilities. 3 Table No.2 - Equivalent Forced Outage Rates (EFOR) Of 4 Avista Therml and Gas Plants 5 6 Plant EFOR Plant EFOR Colstrip 9.36%Rathdrum 5.00 Coyote Springs 5.07%Northeast 5.00 Lancaster 3.00 Kettle Falls 1.58% Boulder Park 15.00 Kettle Falls CT 5.00 Q.Colstrip had an extended outage in 2009. Would 7 it be reasonable to exclude this single year from the 8 average? 9 A.No. In the past, various parties have advocated 10 elimination of years where the Colstrip plant had a high 11 forced outage rate, assuming that such years were abnormal 12 13 and should not be expected to re-occur.This is in fact not the case.The 5-year average of 9.36 percent falls 14 well below the 11.6 percent lifetime plant average. In the 15 25-year history of Colstrip operations there have been 16 seven years (one event every 3.7 years) where forced outage 17 rates exceed 10 percent. It is therefore not uncommon for 18 some years to have outages like the one experienced in 19 2009. See Chart No. 1 for a history of forced outages at 20 Colstrip. 21 Kalich, Di 23 Avista Corporation 1 Chart No. 1 - Colstri Colstrip Unit 3 & 4 Forced Outage History (1984200) 50 45 ~~~-~ ~! ~;¡:O:~i--i\ ~ ¡ ~~: ;:,t, W" :~~~;¡" f¡-~-.. i,,"AnnuaIEFOR ..5yrRollingAvg -1984-2009Avg 40 35 ~,30 2 3 4 ..on ID ~00 CI 0 ..N ..I on =..00 CI 0 ..N ..~on ID ..I0000000000CICICICICICICICI0000ClCl0 CI CI CI CI CI CI Ol Ol CI CI Ol Ol Ol Ol CI Ol ~~0 Cl ~~~~................................N N Q.Please provide a sumry of the monthly and average Northwest forward natural gas and electricity o I i l~ t'~ ai o 25LIW !-$- ,tliit ~ 20 15 10 5 5 prices that directly affect proform costs. 6 A.Table No. 3 presents monthly modeled natural gas 7 and electricity prices for this case. 8 Table No. 3 - Dispatch Model Prices Sumry Oct-10 Nov-10 Dec-10 Jan-11 Felr11 Mar-11 41.15 33.30 31.31 48.91 57.38 55.77 49.19 9 Kalich, Di 24 Avista Corporation 1 Q.Are Mid-Columia electric prices from the 2 Dispatch Model the sam as the Forward Market? 3 A.No,Mid-Columbia electric prices from the 4 Dispatch Model differ from the forward market for a variety 5 of reasons. This being said, they generally are very close 6 as in this filing. Forward market prices are not only an 7 expectation of future prices,but they contain an 8 adjustment for risk or unknown future conditions, based on 9 the premise you can "lock in" prices.The Dispatch Model 10 is a spot market model that forecasts prices for a specific 11 time in the future given load, hydro, and fuel price 12 condi tions .Average annual Mid-Columbia prices in the 13 forward market are $54. 19/MWh on-peak and $42. 56/MWh off- 14 peak (based on average forwards between 10/1/2009 and 15 12/31/2009) .The average Mid-Columbia price from the 16 Dispatch Model is $53. 66/MWh on-peak and $41. 65/MWh off- 17 peak. 18 19 20 V. DEM CLASSIFICATION Q.Witness Knox explains that the Company is 21 changing its methodology for allocating production costs 22 between capacity and energy based on your work.Please 23 explain your concerns with the present methodology and what 24 you propose as a better way to allocate production costs. Kalich, Di 25 Avista Corporation 1 A.The historical method to allocate production 2 costs goes through the various FERC accounts and attempts 3 to determine which costs are for demand and which are for 4 energy.As an example, all thermal fuel in FERC account 5 501 is allocated to energy production, and all "Other" 6 production costs are allocated to demand.Unfortunately, 7 the problem is not this simple. Some of the "Other" costs 8 are almost certainly related to the production of energy 9 and, possibly more surprising to some, various fuel costs 10 can be related to providing capacity (demand). 11 Q.How can some of the costs in your examle be 12 considered energy? 13 A.To produce energy it is necessary to maintain a 14 generation plant in a ready state to do so.The "Other" 15 category is an excellent example of a somewhat arbitrary 16 allocation to demand that is done for lack of any better 17 approach.The "Other" category for both production plant 18 (300 series) and O&M (500 series) includes our gas-fired 19 plants and the Lancaster agreement.The "Other" category 20 is allocated 100 percent demand.Because of this the 21 Company has historically removed our Coyote Springs 2 gas- 22 fired CCCT plant from the "Other" category and instead 23 allocated its costs based on the overall Thermal Peak 24 Credi t figure.But other plants are not broken out this Kalich, Di' 26 Avista Corporation 1 way.Boulder Park, Rathdrum and Northeast are all 2 allocated 100 percent to demand by being in the "Other" 3 category, yet clearly a portion of their plant and O&M 4 costs are attributable to energy production. It is likely 5 that a portion of "Other" expenses are indeed to the 6 benefit of energy production, yet the old allocation method 7 assumed all such costs are attributable to demand. 8 9 Q.How can a fuel cost be classified as demnd? A.Demand, or capacity, is really the production of 10 energy at the time of system peak. Fuel is consumed during 11 periods of peak operation. It would be unreasonable to not 12 consider this fact. And simply because the majority of a 13 fuel expense is incurred outside of peak operating periods 14 does not mean that no fuel should be allocated to demand. 15 Q.Do you have any other concerns about the present 16 demand allocation methodology? 17 A.Yes. Presently all of our generation assets are 18 melded together to create an allocation. Further, a simple 19 accounting methodology is employed to estimate what it 20 might cost to construct our older facilities today. But it 21 is not realistic to assume that historical investments 22 represent our present costs of capacity (demand).Such 23 allocations should be based on the decisions we are making 24 today, and on the costs we incur today when customers 25 consume electrical energy during times of system peak. Kalich, Di 27 Avista Corporation 1 Instead of trying to create an incremental demand cost 2 through a complicated and potentially inaccurate escalation 3 of historical expenses, we should instead use present 4 information for plants we are building to meet new customer 5 demands. 6 Q.Please explain the Company's recommnded method 7 for classifying electricity production costs between energy 8 and demnd. 9 A.The Company believes we should link the 10 classification methodology to the Integrated Resource Plan 11 12 (IRP) .The IRP process is an exercise to meet customer load growth in a least-cost fashion.Central to the 13 equation is the level of our customers' coincident peak 14 demand.We construct a least-cost mix of resources 15 providing both the energy and capacity. 16 Q.What resource does the Company propose be used 17 for splitting demnd and energy costs from overall 18 production expenses? 19 A.We believe that we should use the incremental 20 capaci ty resource from our latest IRP--a gas-fired CCCT. 21 The Company, using its IRP models, calculated the costs of 22 capacity and energy from this resource, and used that 23 figure to allocate overall production costs. 24 Q.How did the Company determne a split between 25 energy and capacity for the incremntal resource? Kalich, Di 28 Avista Corporation 1 A.For the IRP the Company models the Western 2 Interconnect wholesale power marketplace using AURORAxmp. 3 4 AURORAxmp dispatches available resources against electricity loads on an hourly basis.The IRP uses 5 AURORAxmp to look at costs out 20 years and "mark-to- 6 market" (MTM) each potential resource option reasonably 7 available to the Company in the future.The dispatched 8 value of the CCCT (i. e., market sales price less fuel and 9 variable maintenance and operation costs) is tracked .hourly 10 over the 20-year IRP timeframe. Additionally, for the IRP 11 the Company models the 20-year future over 250 Monte Carlo 12 iterations to reflect volatility created by various factors 13 including natural gas prices, load variability and forced 14 outage rates.in other words, for each of the 20 years 15 evaluated for the IRP there are 250 MTM values for the 16 CCCT. The annual average MTM figures represent the energy 17 value generated by the plant.Remaining costs not 18 recovered in the wholesale marketplace are defined as 19 capacity.The ratio of those costs remaining after 20 dispatch into the wholesale marketplace (MTM values) 21 relative to the entire cost of the CCCT plant equals the 22 share of production costs then attributed to demand in the 23 cost of service models. 24 Q.What were the results of your analysis? Kalich, Di 29 Avista Corporation 1 2 A.The analysis allocates 38.1 percent of production costs to demand.Company witness Knox discusses how this 3 demand allocator compares with that derived from the prior 4 peak-credi t methodology. 5 Q.Where are the calculations referenced above 6 contained? 7 A.The calculations are contained in my work papers 8 in an Excel file called "Demand Classification Final." A 9 summary of the results is presented in Exhibit No.5, 10 Schedule 2. 11 Q. How should the demnd allocation be applied to 12 production costs? 13 A.Because the analysis does not differentiate 14 between fixed and variable costs, but instead evaluates all 15 such costs, it should be applied across the board to all 16 production costs. 17 18 19 VI. RESULTS Q.Please sumrize the results from the Dispatch 20 Model that are used for ratemking. 21 A.The Dispatch Model tracks the Company's portfolio. 22 during each hour of the pro forma study.. Fuel costs and 23 generation for each resource are summarized by month. 24 Total market sales and purchases, and their revenues and 25 costs, are also determined and summarized by month. These Kalich, Di 30 Avista Corporation 1 values are contained in Exhibit No.5, Confidential Schedule 2 3 and were provided to Mr. Johnson for use in his 3 calculations.Mr. Johnson adds resource and contract 4 revenues and expenses not accounted for in the Dispatch 5 Model (e.g., fixed costs) to determine net power supply 6 expense. 7 Q.Does this conclude your pre-filed direct 8 testimny? 9 A.Yes, it does. Kalich, Di 31 Avista Corporation 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: (509) 495-4316 FACSIMILE: (509) 495-8851 DAVID .MEYER~AVISTACORP. COM BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION 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 CASE NO. AVU-E-10-01 EXHIBIT NO. 5 CLINT G. 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C o l . 5 + 7 ' C O L 1 5 1 '. . . . . . . . . . . . _ . . . ¡ : 1-'L 14 15 . 4. 6 7 Ca p i t a l . ' r ' " . . . . . . Re c o v e r y . C a p i t a l : F i ; ~ T V a r i a b i ë ' i ' . ' . " ~ . F a s ; t o r d R ~ ~ d v e i : J . F u e l . . . . . . O & M I . ô & M . I T o ~ ¡ L . T ø a l . . . . (~ 0 1 I I . L ( $ m i 1 t . . . . J ~ r n i I L ¡ . . . J $ r r i l L . . i . . . ! $ . ' ! i . I L 1 J $ ! k w - y r t . . . . ($ 5 4 . 7 2 ) , ( $ 2 U 5 ) ' J $ 3 . . 2 . 1 U . . . . . ( S 6 . , 1 . 1 H $ ? S : ! ~ ! : ( $ 3 4 0 . 7 7 : . , ~ 1 lS , ~ % , J 6 2 . 2 9 i I ( ï 5 . 4 5 i C ( ~ . a i ) t : d Î ~ : ? 7 i r i a s . . ~ l l t ( 3 ~ 1 . , 2 4 1 . l S O : ~ 6 . . . 3 7 : i 1 4 7 . 6 0 ) 1 ( 1 9 0 , 3 ~ l i . ! 1.? 5 " , . . . . ! 7 0 : C ? ~ ) 1 . . . ( 1 5 , 6 . 5 1 , . J ~ . 8 6 I ! . . . . . . . . ( ' ! ~ l L . J . ~ : : i ! h ( 3 . ? 6 . 4 A ) f . 1 5 5 . . 2 . 6 . : 3 ! l : ? ! ' . . ( 5 5 , 3 0 ) j ( 2 2 U 8 1 L . .1 6 . : 8 . , , : . J E i ? . 7 6 E . . . 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J 8 ? 3 . 4 : t J 3 . 4 : ? : 3 . 6 . ) ; . . . 2 5 9 . g . . 6 4 : 7 8 . . 1 2 ~ , 5 6 ) ' ( 9 . : 2 5 1 \ 1. 3 . 4 % . ( 5 4 : 2 . 3 . 1 1 . ( 2 2 , 6 9 r . J 3 ~ ~ 2 ) i . , 1 6 . , ~ 3 . U . J S . . 6 . : 4 : 7 1 ¡ . 1 . 3 . 4 S . : e ? ) i . , . . 2 7 1 . 8 ! , . . ' 6 ? ~ ~ 5 . : . . , . J ! ~ ~ 5 7 l ; ( ? I i , O ~ I L . a8 % : . J g : 6 ~ t J 2 4 . 8 3 . L ( 3 . : f ~ I J _ J E i : 4 È ) i . J ! 6 . : ~ 4 : ) ; J 3 . ~ : ~ I i L . , . 3 0 1 . . l l , 7 5 . 2 . 5 . : . ; J l 0 . ~ ? t ( 4 3 . ~ t . I - 12 . 2 % , . . ( 4 9 : ! 6 . 1 \ . . 1 2 6 : S . ? a J 3 . : 3 5 1 ¡ . . . , . . . . I . 6 . . . 3 . ? ~ J ~ 5 : ? S . l L J 3 . I 1 3 . . . 0 0 ) ; , . 3 0 3 . 2 9 : 7 5 , 8 . 2 , . : . . . . ( ~ : ~ 3 . I ¡ . ( 3 9 . m ; . , 1 1 . . 5 " i . 1 4 6 . : t ) ~ J ¡ ( i . 6 . . . ? ~ l L ( ~ 4 : ~ ) I . . . _ _ . ~ : S S . l ¡ . ( ~ , 4 : 1 ) ~ j ~ 3 3 . : 6 . S ) ¡ , L 3 g , S c i . . ? 8 : ! 3 . , ! l . . J ~ . 2 ~ l l . J 2 1 : 1 4 ! ¡ . ~ . . . . .: . t ( : 9 ' : : J 4 4 : 0 9 1 ¡ ( 2 5 , 8 3 L J 3 . , 4 : 9 . 1 1 . . . J 6 . . . R l ) i . . I ! l Q : i . ~ 1 ¡ J 3 2 ( ) . S . 2 I j L . . . 3 2 1 . 1 . 4 ; . . ~ O , ~ ¡ . . , . C l : 2 3 ¡ . o . ? i . ¡ , . L , . : i ~ ~ 3 . ' J L . . 4 ! : S . 6 . ) ~ . J 2 5 , ~ S . l l . J 3 . ~ S . 6 . I L _ . j 6 . . : ! ! ! t . . l ~ : ! : S ) . i . J 3 . . i . ~ ! l c i i ¡ . t . 3 . ~ ~ , 4 : ~ . . . ? ? , . 8 7 - f . . + . . ) , . ~ . i . , . 7 : E ! l . : ; ~: c i i ¡ - i ~ ~ : ~ r i ~ I J K i ~ ) t ' ~ i c i ~ f . - " ~ : ~ i i i . i j ~ ~ j ~ ~ H i i ~ ~ ~ i ~ + i ~ ~ ~ : ~ ¡ . : ~ I . . j i ~ : i : : ~ c i : ~ ~ ¡ ! . .. . . . , . . . . _ L . ~ I . ' J . . . . . l ~ . . . . . . . . . . . , . . . . . J t - _ . _ _ . . . . . . . . . . . . . . . . . . . . 1 , . . ¡ . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . , . ' . . . . . , . . . - . ~ . . . , . . . . '. . . . 8 . : ~ ¡ . . . J 3 3 . : ~ ~ 4 . 1 2 . ~ . 1 5 1 ~ J 3 , ? 8 1 . . _ . . . Q : 3 J l t l ? 1 i , 7 S . l f . J ~ ~ ? . ! i . a . I . . . E 3 ~ 6 5 : . . . ? 1 : " ' 1 , ¡ , . a 1 3 . l J 6 . : 5 ~ ~ + . . . . . . 7 . S . , , ~ . ( 3 . : i . , 4 : ~ ~ . . . ( ~ 0 . 1 s . ! t . . . ( È ~ . 8 ? - ! t . . . , _ , . J ? ~ 1 1 . 1 ? 2 . : ~ 1 ! . . . H ~ p 5 l j . . . L . . . . . 3 . e S . : ~ 8 ; . . . ! : . 6 : . s , 0 + . . . . . . . 2 . 3 . , 5 6 . . ¡ . . . . 9 . 4 . . 2 . 3 . ; . 1 .. . ? : ! , , ¡ . . . . J 2 l ! : 9 . ( ) ! L . . l i . ~ , ~ ! : l . . . ~ : . ~ 3 . I I . . . . . _ J ? : 6 . . s . L l ! ( ) , 4 : ? i ~ ß ! l ~ s . ? 4 . . . ; . . . . . . 3 ~ 2 . . l ' , . . . . ? ~ : ( ) S . . L . ¡ . . 3 ? 6 . 2 . . t . . ~ ~ 0 , 4 7 . + . + .. : . . . . 6 . , 5 " " . . . . . ( ~ 6 . . 3 . 6 . 1 L I 2 . 9 . S . 6 . ) L 1 4 , O l ) " . . . . . . ( ? : ! ~ m . . I ~ . l ! I J . ß ? 2 : 4 . ~ ! . L . _ L . . . 4 c i ? , 2 2 . : L 0 ! , a Q . ; . . . : . 3 . 3 . . 6 9 : 1 S 4 : ? ? L . . '5 . 9 % 1 ( 2 3 . 8 3 ) ¡ ' ( 3 2 . 1 2 ) J J 4 : : c i 9 ) L . . . ( 7 . 8 : 1 L J 6 7 . 8 ~ 1 ! J 2 7 1 . 5 2 l . j . . 4 : 1 2 . 2 0 . 1 0 3 . 0 5 . . 3 5 . 1 7 : . 1 4 0 . 6 8 ¡ , ..Ma r k e t .. . . . . . . . . Va l u e . V a l u e (S j k \ N ~ y r l ( $ r n l ! t J2 5 2 . 4 ( c . $ 6 3 . 1 ( ) ; tf t V a l u e ($ m i l l ' ( $ / k W - y r l ' ¡( s i ï . . o . 9 ) . , ; t $ 8 â ; : i Z I ( _ , . . , .. . . . Ex h i b i t N O . 5 Ca s e N o . A V U - E - I O - O l C. K a l i c h , A v i s t a Sc h e d l e 2 , p . l o f i CONFIDENTIAL Dispatch Model Sumry output Pages i through 3 THESE PAGES ALLEGEDLY CONTAIN TRAE SECRETS OR CONFIDENTIAL MATERIALS AN AR SEPARTELY FILED. Exhbit No.5 Case No. AVU-E-IO-OI C. Kalich, A vista Schedule 3, p. lof 3