Into Avista s Electricity Forecasts. Presented by Randy Barcus Avista Chief Economist Itron s Energy Forecaster s Group Meeting

Transcription

1 Incorporating Global Warming Into Avista s Electricity Forecasts Presented by Randy Barcus Avista Chief Economist Itron s Energy Forecaster s Group Meeting May 1, 009 Las Vegas, Nevada

2 Presentation Outline The Computations Weather and Sales Relationship Climate Change Theory Global Warming Data Driven Results Regression Analysis Actual Results Presentation Tips

3 Utility Business Characteristics My Company Investor-Owned We W sell electricity it in Eastern Washington and Northern Idaho 6,000 square miles 700,000 people 355,000 retail customers We distribute natural gas in Southwest Oregon 3,000 square miles 1,100,000 people 315,000 retail customers Fuel Sources Hydro, coal, wood-waste, gas and wind Gas purchased in Rockies and Canada 3

4 Management, Bankers and Stock Price Utility Senior Management high risk aversion, engineers and accountants, budget driven decision making process Bankers and Stock Analysts benchmarks to similar companies, management stock options, peer performance Financial Considerations Global Warming impact on revenue heretofore unknown; calming the jitters of the stakeholders 4

5 The Math Weather and Sales Relationship Electric residential in Washington Electric commercial in Idaho (Constant) NOSUMHDD QualityHDD CDD (Constant) NOSUMHDD QualityHDD CDD Electric Washington 5 monthly data series Electric Idaho 5 monthly data series 5

6 Climate Change Theory Preponderance of evidence on climate warming Various contributions, carbon dioxide most prominent Even with stringent reductions, warming likely to continue Consistent application of information to balance Supply and Demand Expect 1 degree warming every 40 years, both summer and winter 6

7 Average January Spokane Temperature /31/1890 1/31/1894 1/31/1898 1/31/190 1/31/1906 1/31/1910 1/31/1914 1/31/1918 1/31/19 1/31/196 1/31/1930 1/31/1934 1/31/1938 1/31/194 1/31/1946 1/31/1950 1/31/1954 1/31/1958 1/31/196 1/31/1966 1/31/1970 1/31/1974 1/31/1978 1/31/198 1/31/1986 1/31/1990 1/31/1994 1/31/1998 1/31/00 1/30/ y = 5E-05x x x

8 8,500 8,000 7,500 7,000 6,500 6,000 5, Spokane HDD Trend y = x R = NOAA Normal is 6,

9 Average July Spokane Temperature y = 4E-05x x x /31/1890 7/31/1894 7/31/1898 7/31/190 7/31/1906 7/31/1910 7/31/1914 7/31/1918 7/31/19 7/31/196 7/31/1930 7/31/1934 7/31/1938 7/31/194 7/31/1946 7/31/1950 7/31/1954 7/31/1958 7/31/196 7/31/1966 7/31/1970 7/31/1974 7/31/1978 7/31/198 7/31/1986 7/31/1990 7/31/1994 7/31/1998 7/31/00 7/31/006 9

10 Cooling Degree Day Trends Normal = 394 y = x R =

11 Intermountain Annual Weather Summary November 008 to October 009 Winter will be much colder and drier than normal, on average, with snowfall above normal in the north and below normal in the south. The coldest temperatures will occur in late December; early, mid-, and late January; and early February. The snowiest periods will be in mid- November, early and mid-december, mid- and late January, and late February. April and May will be cooler than normal, with slightly above-normal precipitation. Summer will be cooler than normal, with slightly above-normal rainfall. The hottest periods will be in mid- and late June and early and mid- to late July. September and October will be warmer and drier than normal. 11

12 Spokane NWS Global Warming Degree Day Trends % % 5%.8% 6.1% 47.3% 48.6% 160% % % 4% 6% 5.9% 7.% 8.4% 19.7% 130.9% 13.% 133.5% 134.7% 136.0% 137.% 138.5% 139.8% 141.0% 14.3% % 109.5% 110.8% 11.0% 113.3% 114.6% 115.8% 117.1% 118.3% 119.6% 10.9% 1.1% % % % % 1 100% 95.% 95.0% 94.7% 94.4% 94.1% 93.9% 93.6% 93.3% 93.1% 9.8% 9.5% 9.% 9.0% 91.7% 91.4% 91.1% 90.9% 90.6% 90.3% 90.1% 89.8% 89.5% 89.% 89.0% 88.7% 88.4% 88.1% 87.9% 87.6% 87.3% 87.1% 86.8% 80% Heating Degree Days Cooling Degree Days

13 15,000 14,000 13,000 Electric Average Use per Average Customer 100,000 y = 183x ,000 80,000 Annual kwh Residential Annual kwh Commercial 1,000 11,000 10,000 9,000 70,000 y = -4x ,000 50,000 40, Residential Commercial Linear (Residential) Linear (Commercial)

14 1,500, ,000 (500,000) Global Warming Impact Normal minus Warming HDD and CDD Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Nov-11 (1,500,000) (,500,000) (3,500,000) (4,500,000) Residential Commercial Industrial System Total kwh 14

15 MW Difference Normal minus Warming HDD & CDD Av erage MW

16 Electric Sales Forecast Base w/ GW vs. Normal Weather 14,000,000,000 13,000,000,000 Compound Growth Rates Base 1.68% Normal 1.73% 1,000,000,000 h annual kw 11,000,000,000 10,000,000,000 Reduction in avg MW ,000,000,000 8,000,000,000 7,000,000, Electric Base Electric Normal 16

17 Process Timeline Concept presented to senior management January 007 Rough estimate June 007 Presented to Investment Bankers July 007 NOAA/CPS Climate Change Conference November 007 Industry Forecaster s Conference May 008 Completed July 008 Presented to Technical Advisory Committee September

18 Lessons Learned It s important to be consistent It helps to have the data and a model The first time is the worst time 18