Developing Load Reduction Estimates Caused by Interrupting and/or Curtailing Large Customers

Developing Load Reduction Estimates Caused by Interrupting and/or Curtailing Large Customers

By Carl L. Raish2000 AEIC Load Research Conference

July 31, 2000

2000 AEIC Load Research Conference

2

Tampa Electric’s Interruptible Rate Class

• 32 Customers, 72 Accounts• 1,631.5 GWH for Class in 1999• 22.8 GWH per Account• 7.6 MW Average Non-coincident Peak• 285.9 MW 1999 Class Peak• 174.3 MW at 1999 Winter Peak• 60.8 MW at 1999 Summer Peak

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3

As a result of statewide generation shortages in 1999 the number of

interruptions was at a record level

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4

Monthly Interruption Frequencies1986 - 2000

0

2

4

6

8

1986 1988 1990 1992 1994 1996 1998 2000

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5

Annual Interruption Frequencies

0

2

4

6

8

10

12

14

16

18

1986 1988 1990 1992 1994 1996 1998 2000

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Monthly Interruption Durations1986 - 2000

0

5

10

15

20

25

1986 1988 1990 1992 1994 1996 1998 2000

Ho

urs

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7

Annual Interruption Durations

0

5

10

15

20

25

30

35

1986 1988 1990 1992 1994 1996 1998 2000

Ho

urs

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Reduction Estimates at Individual Account Level

• Need to estimate amount of load interrupted in MW and MWH during 1998 and 1999

• Use account 15-minute data for the year (100% load research sample in place)

• For each interruption, select demands for the day prior to and the day of interruption

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9

Customer 50089 Day Before and Day of Interruption

0

1

2

3

4

5

6

7

8

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW

July 28 and 29

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• Notification is typically sent out 2 hours before actual interruption

• Find 10 closest matching day-pairs (without interruptions) -- match demands for the entire day before and the day of interruption up to 3 hours before start of interruption

• Average the 10 day-pairs together by interval

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0

1

2

3

4

5

6

7

8

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW

Jul 28,29 10 Day Avg

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12


• Run linear regression on intervals prior to interruption • Model actual demand as a function of average demand• If R-square > .5 and there are no outliers, then use the

regression estimate.• Otherwise, use the 10-day average demands

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13

Customer 50089 Before Interruption

3

4

5

6

7

4.5 4.7 4.9 5.1 5.3 5.5 5.7 5.9 6.1 6.3 6.5

10 Day Avg MW

Act

ual

MW

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• Run linear regression on intervals prior to interruption • Model actual demand as a function of average demand• Apply model to the average demands for the rest of

the day to predict what the demand levels would have been without an interruption

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15


0

1

2

3

4

5

6

7

8

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW

Jul 28,29 10 Day Avg Regress

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• Interruption / curtailment starts when the percentage difference between the actual demand and the predicted demand is negative and its absolute value is greater than all differences prior to the interruption

• Interruption / curtailment ends when residual goes positive after the interruption end time or the residual percentage is 2/3 of the maximum

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-6

-4

-2

0

2

4

6

8

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW

Jul 28,29 Regress Residual

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• Interruption / curtailment amount is the difference between the actual and predicted demands

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19


0

1

2

3

4

5

6

7

8

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW

Jul 28,29 10 Day Avg Regress Curtailment

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0

0.2

0.4

0.6

0.8

1

1.2

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW

Jul 28,29 10 Day Avg Regress Curtailment

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Customer 20143Before Interruption

0.7

0.8

0.9

1

1.1

1.2

0.8 0.85 0.9 0.95 1 1.05 1.1 1.15

10 Day Avg MW

Act

ual

MW

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Reduction Estimates at IS Class Level

• Sum individual account reduction amounts on an interval-by-interval basis to obtain class totals

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IS Class Jul 29, 1999

0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW

pred actual curtailed act+curt

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Apply the same method and compare results on some days in

1999 without interruptions

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Customer 20143 Consecutive Days with No Interruption

0

0.2

0.4

0.6

0.8

1

1.2

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW


July 31, 2000


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0

0.2

0.4

0.6

0.8

1

1.2

1.4

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW


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27


0

1

2

3

4

5

6

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW


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28


0

1

2

3

4

5

6

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW


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29

IS Class Consecutive Days with No Interruption

0

50

100

150

200

250

300

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW


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30

IS Class Consecutive Days with No Interruption

0

50

100

150

200

250

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00

MW


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Dealing with interruptions / curtailments on consecutive days

• One occurrence in 1998: June 22 and 23

• Four occurrences in 1999: April 5 and 6, April 23 and 24,

July 29, 30 and 31

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IS ClassJuly Consecutive Interruptions

0

50

100

150

200

250

0 12:00 0:00 12:00 0:00 12:00 0:00 12:00

MW

Act 28 - 31

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0

50

100

150

200

250

300

0 12:00 0:00 12:00 0:00 12:00 0:00 12:00

MW

Act 28 - 31 Act 21 - 23

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0

50

100

150

200

250

300

0 12:00 0:00 12:00 0:00 12:00 0:00 12:00

MW

Act 28 - 31 Act 21 - 23 Pred 29

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0

50

100

150

200

250

300

0 12:00 0:00 12:00 0:00 12:00 0:00 12:00

MW

Act 28 - 31 Act 21 - 23 Pred 30

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0

50

100

150

200

250

300

0 12:00 0:00 12:00 0:00 12:00 0:00 12:00

MW

Act 28 - 31 Act 21 - 23 Pred 31

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IS ClassJul 31, 1999

0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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38


0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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Dealing with voluntary curtailments occurring more than three hours before the start of the actual

interruption

• Three occurrences:June 19, 1998; April 26, 1999;

July 30, 1999

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0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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IS ClassApr 26, 1999

0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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Shortest Interruption

• April 3, 1998 12:52 - 13:05

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IS ClassApr 3, 1998

0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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Longest Interruption

• April 24, 1999 12:30 - 20:04

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0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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Winter Morning Interruption

• January 6, 1999 06:37 - 08:14

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IS ClassJan 6, 1999

0

50

100

150

200

250

300

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

MW


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Interrupted / Curtailed KWH1998 - 1999

0

1000

2000

3000

4000

5000

6000

7000

41998

61998

11999

41999

51999

71999

81999

91999

101999

Month

MW

H

AfterDuringBefore

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MWH Interrupted / Curtailed1998

22%

56%

22%

before

during

after

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MWH Interrupted / Curtailed1999

21%

61%

18%

before

during

after

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Follow-up Analysis

• Analyze the impact on Individual Customer and IS Class load as a result of third party purchases

• Focus on impacts associated with new notification system during May 2000

• Customer notification includes hourly forecasts of:– Probability of Interruption– Probability of third party purchase– Third party purchase price levels– Duration of purchase

Developing Load Reduction Estimates Caused by Interrupting and/or Curtailing Large Customers

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