1. 10/31/2015 1 1 Economic Value of Stabilizing Regional Conservation Investments Changes to Analytical Approach and Updated Results

2. 10/31/2015 2 2 Goal of the Analysis l Determine whether there is a net economic value to the region’s power system that could result from stabilizing the annual level of conservation resource acquisition l Identify and evaluate conservation deployment strategies that provide the best net economic value to the regional power system considering practical limitations on program ramp rates and market volatility

3. 10/31/2015 3 3 Analytical Approach Selected l Use ConSOD model to simulate two responses to variations in future market prices: “Sustained Orderly Development” (SOD) - Conservation acquisitions are deployed in uniform annual increments based on long- run avoided costs “Market Price Response” (MPR) - Conservation acquisitions are deployed based on rolling average of short-term market prices

4. 10/31/2015 4 4 Analytical Issues – Required Data and Assumptions l Major Assumptions –Relationship between “rolling average” Market Prices and Annual Level of conservation acquisition –Relationship between Ramp Rate and Total Resource Cost of conservation acquisitions –Rate at which conservation acquisitions can be Ramped Up and Down –Amplitude and Frequency and Duration of wholesale market price spikes

5. 10/31/2015 5 5 What’s Changed? l Prior l Prior analysis based on “Regional” historical relationships between: –Annual Expenditures and Total Acquisitions –Level of Annual acquisitions and Cost/aMW –Changes in Acquisition Levels and Changes in Cost/aMW –Acquisition Levels and Market Prices l Updated l Updated analysis based on historical experience of 10 individual PNW utilities

6. 10/31/2015 6 6 Is There A Relationship Between Market Prices and Annual Level of Conservation Acquisition? – Regional Data

7. 10/31/2015 7 7 Is There A Relationship Between Market Prices and the Annual Level Conservation Acquisitions? – Utility Data

8. 10/31/2015 8 8 Negatively Annual Conservation Acquisitions are Negatively Correlated to “Same-Year’s” Market Prices – Regional Data

9. 10/31/2015 9 9 Annual Conservation Acquisitions Appear To Be Very Weakly but Positively Correlated to “Current Year’s” Market Prices – Utility Data

10. 10/31/2015 10 Annual Conservation Acquisitions are Strongly and Positively Correlated to “Last-Year’s” Market Prices – Regional Data

11. 10/31/2015 11 Annual Conservation Acquisitions Appear To Be Weakly and Positively Correlated to “Last- Year’s” Market Prices – Utility Data

12. 10/31/2015 12 However - If we exclude 2000-01 They’re NOT

13. 10/31/2015 13 Changes in Annual Conservation Acquisition Are Strongly Correlated to Changes in Prior Year’s Market Prices – Regional Data

14. 10/31/2015 14 Excluding 2000-01, Changes in Annual Conservation Acquisition Are Weakly Correlated to Changes in Prior Year’s Market Prices – Regional Data

15. 10/31/2015 15 Changes in Annual Conservation Acquisition Are Not Correlated to Changes in Prior Year’s Market Prices – Utility Data

16. 10/31/2015 16 Relationship Between Market Prices and Changes in the Annual Level of Conservation Acquisition l Conclusion – Historical evidence does not indicate a statistically significant relationship between Conservation Acquisitions and Market Prices l However, changes in acquisition levels appear to lag market prices due to the inertia intrinsic in »Budget cycles »Infrastructure response »Project/Program lead times –Assumption – Ramp ups in conservation acquisitions lag the “rolling average” monthly market price changes by 0 – 18 months, with a “expected value” lag of 6 months

17. 10/31/2015 17 Is There A Relationship Between Ramp Rate and Total Resource Cost of Conservation Acquisitions? STILL NO DATA on TRC Used Utility Cost (Again)

18. 10/31/2015 18 Regional Utility Annual Conservation Acquisition Levels Have Varied Significantly Average – 6.7 aMW/yr Standard Deviation – 6.2 aMW/yr

19. 10/31/2015 19 Regional Conservation Acquisition Costs Have Varied Significantly Average - $2.22 million/aMW Standard Deviation - $1.13 million/aMW

20. 10/31/2015 20 Utility Conservation Acquisition Levels Have Varied Significantly Over Time

21. 10/31/2015 21 Utility Conservation Acquisition Costs Have Varied Significantly Over Time

22. 10/31/2015 22 Strongly Total Utility Conservation Expenditures Are Strongly Correlated to Annual Acquisition Levels

23. 10/31/2015 23 Strongly Correlated Changes in Utility Conservation Expenditures are Strongly Correlated to Changes in Conservation Acquisitions

24. 10/31/2015 24 Cost/aMW and Magnitude of Annual Conservation Acquisitions Are Weakly Correlated – Regional Data

25. 10/31/2015 25 Not Utility Cost/aMW Are Not Correlated to Annual Acquisition Levels

26. 10/31/2015 26 Changes in Conservation Acquisitions Are Weakly Correlated and Inversely Related to Utility Acquisition Costs

27. 10/31/2015 27 Relationship between Ramp Rate and Utility Cost of conservation acquisitions l Conclusion - There is only a weak relationship between ramp rates (up or down) and utility conservation acquisition costs. l Utility conservation acquisition costs ($/aMW) are lower when ramping up than when ramping down. l Assumption – –Assume 10% higher cost/aMW during ramp down than ramp up.

28. 10/31/2015 28 Utility Conservation Acquisition “Ramp Rates” Vary Over A Wide Range Average -.2 aMW Standard Deviation – 4.3 aMW

29. 10/31/2015 29 Rate at which conservation acquisitions can be Ramped Up and Ramped Down l Conclusion - Conservation has been ramped up and down within a range of +/- 10 aMW l Assumption – Constrain ramp rate to “monthly” availability” of each conservation cost block (e.g. maximum annual change = 12x monthly availability).

30. 10/31/2015 30 Amplitude, Duration and Frequency of wholesale market price spikes l Wholesale market prices will fluctuate as a result of: –Over/Under building –Extreme weather events (hot or cold) –Hydro-system availability –Short-run economic/business cycles Assumption:“Randomize” the forecast of future “price spikes” in response to hydro-system availability, ignore “short-run” weather & business cycles