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Karen ChiangDiane CunninghamSouthern Company Load Research

When Normal Weather Is Not Normal

AEIC Load Research Workshop

April 2006

Southern Company2

Southern Company

• One of the largest producers of electricity in the United States

• Service area• 120,000 square miles in 4 states• Nearly 4.1 million customers• Population of 12 million

• More than 27,000 miles of transmission lines

• 79 generating stations

• Nearly 39,000 megawatts of generating capacity

• Sources of generation: 69% coal; 16% nuclear; 3% hydro; and 12% oil and gas.

Southern Company3

Southern Company Subsidiaries

• Alabama Power

• Georgia Power

• Gulf Power

• Mississippi Power

• Savannah Electric

• Southern Nuclear

• Southern Power

• Southern Company Services

• Southern LINK

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Southern Company Service Area

GeorgiaPower

AlabamaPower

Gulf Power

GeorgiaPower

AlabamaPower

Gulf PowerMississippi

Power

SavannahElectric

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Applications for Normal Weather

• Energy & Demand Forecasts.

• Energy & Demand Growth Rates.

• Flat Rate Pricing.

• Demand Side Management Program Evaluation/Assessment.

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Defining Normal Weather

• NOAA 30-year Average

• Self-Defined Historical Period Average

• NOAA Typical Meteorological Year (TMY)

• Rank & Average Method

Pros & Cons:

• Averaging methods good for energy forecasting, but lack temperature extremes necessary for demand forecasting.

• TMY provides temperature variations day to day, but still may not contain the extremes.

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Rank and Average Method

AverageDay Year1 Year2 Year1 Year2

1 80 94 93 95 942 88 93 92 94 933 90 85 91 93 924 89 93 91 93 925 81 95 91 93 926 89 91 90 92 917 91 93 90 92 918 90 92 90 92 919 82 84 89 91 90

10 90 92 89 91 9011 92 82 88 90 8912 91 90 83 85 8413 83 92 82 84 8314 91 91 81 83 8215 93 83 80 82 81

Actual Temp. Rank Hi - Low

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Analysis of Ranking Methods

• Choices of Ranking Methods• Monthly• Seasonally• Annually

• Based on the method selected, you can effect which (when) the peak will occur.

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Comparison of Ranking Methods

13-Year RankedAverage Monthly

Jan 53.69 64.97Feb 58.19 66.94Mar 63.76 70.68Apr 69.92 75.27 RankedMay 77.72 80.27 Seasonally 86.35Jun 80.91 83.90Jul 82.44 85.74 RankedAug 82.95 84.95 Annually 86.35Sep 79.77 82.56Oct 73.88 77.21Nov 63.11 71.60Dec 56.78 66.59

Max Temperatures Based on Ranking Method

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Selecting a Reference Year

1990 86.71 28-Aug1991 85.13 14-Jul1992 84.88 12-Jul1993 86.07 27-Jul1994 84.82 27-Jun1995 87.21 17-Aug1996 85.59 22-Jul1997 85.44 4-Jul1998 87.54 8-Jul1999 89.00 1-Aug2000 90.42 29-Aug2001 84.90 9-Jul2002 84.86 18-Jul

Daily Average 82.95 18-Aug

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Selecting a Reference Year

• Randomly select any year

• Select a year based on minimum variance

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Calculation of Variance Before and After the Ranking

Day Year 1 Year 2 Year 3 Average Var Year 1 Var Year 2 Var Year 31 80.00 94.00 88.00 87.33 53.78 44.44 0.442 88.00 93.00 93.00 91.33 11.11 2.78 2.783 90.00 85.00 85.00 86.67 11.11 2.78 2.784 89.00 93.00 95.00 92.33 11.11 0.44 7.115 81.00 95.00 95.00 90.33 87.11 21.78 21.786 89.00 91.00 91.00 90.33 1.78 0.44 0.447 91.00 93.00 91.00 91.67 0.44 1.78 0.448 90.00 92.00 92.00 91.33 1.78 0.44 0.449 82.00 84.00 84.00 83.33 1.78 0.44 0.44

10 90.00 92.00 92.00 91.33 1.78 0.44 0.4411 92.00 82.00 82.00 85.33 44.44 11.11 11.1112 91.00 90.00 88.00 89.67 1.78 0.11 2.7813 83.00 92.00 92.00 89.00 36.00 9.00 9.0014 91.00 91.00 91.00 91.00 0.00 0.00 0.0015 93.00 83.00 88.00 88.00 25.00 25.00 0.00

Sum 289.00 121.00 60.00

Rank Year 1 Year 2 Year 3 Average Var Year 1 Var Year 2 Var Year 31 93.00 95.00 95.00 94.33 1.78 0.44 0.442 92.00 94.00 95.00 93.67 2.78 0.11 1.783 91.00 93.00 93.00 92.33 1.78 0.44 0.444 91.00 93.00 92.00 92.00 1.00 1.00 0.005 91.00 93.00 92.00 92.00 1.00 1.00 0.006 90.00 92.00 92.00 91.33 1.78 0.44 0.447 90.00 92.00 91.00 91.00 1.00 1.00 0.008 90.00 92.00 91.00 91.00 1.00 1.00 0.009 89.00 91.00 91.00 90.33 1.78 0.44 0.44

10 89.00 91.00 88.00 89.33 0.11 2.78 1.7811 88.00 90.00 88.00 88.67 0.44 1.78 0.4412 83.00 85.00 88.00 85.33 5.44 0.11 7.1113 82.00 84.00 85.00 83.67 2.78 0.11 1.7814 81.00 83.00 84.00 82.67 2.78 0.11 1.7815 80.00 82.00 82.00 81.33 1.78 0.44 0.44

Sum 27.22 11.22 16.89

Calculation of Variance Before Ranking Applied

Calculation of Variance After Ranking Applied

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Reference Year based on Minimum Variance

Weather Profile

20

30

40

50

60

70

80

90

1 10 19 28 37 46 55 64 73 82 91 100 109 118 127 136 145 154 163 172 181 190 199 208 217 226 235 244 253 262 271 280 289 298 307 316 325 334 343 352 361

Average 1992 Min Variance 1995 Min Variance after ranking

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Selecting a Reference Year

• Randomly select any year

• Select a year based on minimum variance

• Use the period average as the reference year

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Reference Year based on Period Average

Weather Profile

20

30

40

50

60

70

80

90

1 9 17 25 33 41 49 57 65 73 81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201209 217 225 233 241249 257 265 273 281289 297 305 313 321329 337 345 353 361

Average Rank Annually

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Reference Year based on Period Average

Weather Profile

30

40

50

60

70

80

90

1 9 17 25 33 41 49 57 65 73 81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201 209 217 225 233 241 249 257 265 273 281 289 297 305 313 321 329 337 345 353 361

Average Ranked Monthly

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Conclusion

• Rank and average method produces a normal profile appropriate for capturing extreme weather conditions.

• Seasonal or Annual ranking is preferable than monthly ranking to determine typical extreme temperatures.

• Using the period average as reference year is preferable over other selection methods.

• it captures the peak temperature on the same day as period average.

• It reduces the volatility from day to day across the year.