MEMORANDUM. To: PRL Performance Standards Subgroup From: Donna Pratt Subject: Performance Method Recommendation Date: January 18, 2001

Transcription

1 MEMORANDUM To: PRL Performance Standards Subgroup From: Donna Pratt Subject: Performance Method Recommendation Date: January 18, 2001 The Emergency Demand Response Program Manual is in its final phase of development and we need to provide a final detailed recommendation to the ISO for the method for determining performance during an emergency event, and how compliance is determined. As discussed during the last PRL WG meeting on January 4, there were several issues the NYISO took into consideration when deciding on a single method for assessing performance: Allow CSPs to maintain existing load reduction programs or design new programs; A single method that facilitates and standardizes settlement between CSP and NYISO; The method should reflect the end-use customer s historic usage without being overly complex; and Performance methods employed elsewhere. The 10-day rolling average by hour method provides the most comprehensible and reproducible method without being overly complex. It is a less subjective method because the parameters are clearly defined and it incorporates the end-use customer s historic usage for the period immediately preceding the emergency event. While no single method will be completely accurate for every customer, the 10-day rolling average by hour method tends to normalize variations in load attributed to operations or weather. In some extreme cases, the average may result in performance that is understated or overstated, but overall, the 10-day rolling average meets the design criteria more completely than other methods evaluated: Comprehensible easy for customers to understand; Accurate minimizes gaming; Reproducible can be calculated by customers; and Flexible accommodates difference customer circumstances. Other methods examined were eliminated for the following reasons: Prior day or prior hour methods offer more room for gaming and are more subjective because parameters may be selected to maximize customer benefit. Day-type averages can reach back to days that may not appropriately represent the otherwise operating conditions of the event day.

2 Taking these concerns into consideration, I propose the following revised recommendation for assessing end-user performance during an emergency event. 1. The NYISO shall select a single method for CSPs to use for assessing performance during an emergency event: the average 10-day method. 2. Description of the average 10-day method: 2.1 The otherwise applicable load shall be determined by taking the simple average, by hour, of the 10 previous weekdays, excluding holidays and NYISO-declared curtailment days. 2.2 The following 6 days shall be considered holidays (when the holdiay falls on a weekday) and excluded from the average for this method: New Year s Day, Memorial Day, Independence Day, Labor Day, Thanksgiving Day and Christmas Day. 2.3 The average by hour for weekdays shall be computed as follows: the simple average, by hour, for 10 previous consectuive weekdays prior to the day of the actual event when there are no holidays or NYISO curtailment events in the 10 previous consecutive weekdays (Example 2.3). 2.4 Exclusions from the rolling average for weekdays: If a holiday or curtailment day occurs within the 10 previous consecutive weekdays prior to the day of the actual event, the holiday or curtailment day is eliminated from the simple average. In this case, the simple average by hour is produced from the remaining number of days as long as there is a minimum of 7 days in the average (Example 2.4.1) If there are less than 7 weekdays in the average due to multiple curtailment days and/or holidays, go back to include previous weekdays until there are 7 previous weekdays in the average (Example 2.4.2) Exclude the value from any hour in which the actual load in that hour is more than 50% greater or more than 50% less than the corresponding hourly rolling average after all other exclusions. There must be a minimum of 7 and a maximum of 10 hourly weekday values for every hour (Example 2.4.3, scenario only see section titled Discussion Regarding Methods and Shutdowns ) Weekend calculation: the rolling average by hour for a weekend Emergency Demand Response Program event shall include the 6 weekend days (Saturdays and Sundays) prior to the weekend event (Example 2.5). 1 This latest provision accounts for exclusion of shutdowns and also for hours when extreme operating conditions may occur from recovery operations or equipment testing. Excluding hours where the actual load is less than 50% of the rolling average for the hour prevents the customer s performance from being understated. Windfalls are prevented by excluding hours where the difference between actual load and the rolling average is greater than 50%. The alternatives to this provision would be: a) to require the customer to delcare shutdown days to the LSE and ISO 30 days in advance; b) to eliminate days entirely from the average when any hour was below 50% of the rolling average which would mean reaching back more days; or c) not acknowledging shutdown days for purposes of computing performance under the Emergency Demand Response Program.

3 2.5.1 Exclusions: Any weekend day that contains an Emergency Demand Response Program event shall be excluded from the rolling average by hour calculation and shall not be replaced (Example 2.5.1). Performance Measurement Performance is measured as the difference between the baseline (rolling average by hour) and the actual metered usage by hour during the event. Where P h = performance in the hour above P h = BL h AL h BL h = baseline for the hour as calculated using the rolling average method described AL h = actual load in the hour Initial Compliance Initial Compliance (P-IC) is measured as the first event hour in which performance in the hour is greater than zero ( actual load is less than baseline). Final Compliance (Restored Load) Final Compliance (P-FC) is measured as the last hour in which performance is greater than zero, following an hour in which performance is greater than zero, or the last hour of the EDRP event, whichever is earlier. Compliance Period The Compliance Period includes every hour in the EDRP event in which performance was greater than zero, beginning with the Initial Compliance hour and ending with the Final Compliance hour or the end of the EDRP event, whichever is earlier. The table on the next page illustrates examples of Initial Compliance and Final Compliance.

4 Examples of Performance during an EDRP 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM Customer 1 BL AL Performance P-IC P P P-FC Compliance Period Customer 2 BL AL Performance Compliance Period P-IC P P P-FC Customer 3 BL AL Performance P-IC P-FC Compliance Period Legend BL = BaseLine IC = Initial Compliance P = Performance AL = Actual Load FC = Final Compliance

5 Discussion Regarding Methods and Shutdowns The following two graphics illustrate the results of evaluating different methods for handling performance during regular operations and shutdowns. (These graphics are also in the PowerPoint file that was included with the . I recommend that you print this material and view the PowerPoint versions of the graphics while reading the material below.) The load data used for these examples came from a single customer, approximately 1.1MW. The data were mapped to 2001 ensuring that day types and holiday loads were preserved. Methodologies for computing the simple average by hour: A: Use the 10 previous weekdays; B: Use the previous 5 days of the same weekday type (e.g. 5 Wednesdays, etc.); and C: Use the 5 highest values out of the 10 previous weekdays. In addition, I calculated the average weekday for the month of the event and the prior Scenario 1 - no holidays or other event days Simple rolling avg Avg day type (5 Thurs.) Max. 5 intvls out of 10 Avg. May Weekday Avg. April Weekday Hour month since the sample events occurred early in the month. Scenario 1 Baseline calculation for an event with no holidays or other events (Example 2.3).

6 Evaluation: Conclusion: The net difference between the day-type method and simple rolling average method are the smallest and the greatest net difference occurs between the highest 5 interval method and the simple rolling average method. The highest 5 interval method overstates the net load of the simple rolling average method by approximately 65% with individual hour variances of as much as 12%. The highest 5 interval method also overstates the net load of the day-type average method by approximately 35% with individual hour variances of up to 6%, with some hourly values lower than the simple rolling average. The simple rolling average method closely follows the average April weekday average because the majority of the days used to calculate the average came from the month of April. Although the May average is the median of all the plots, using the average weekday for the month can only occur after the fact, the customer then has no way of knowing whether he performed during the event until the end of the bill period. For this example, the simple 10-day rolling average most closely matches the typical load this customer would operate at, based on the April weekday average data. The highest 5 interval method signficantly overstates the typical load for the period when compared to the monthly average for April. The day-type average starts out with a noteworthy variance, but falls in line with the simple rolling average and monthly weekday average after 9:00 am.

7 Scenario 2 - Shutdown during week prior to event Shutdown incl. in avg. Max. 5 intvls out of 10 Declared Shutdown excluded Day type avg incl shutdown day Day type avg w/o shutdown day Avg. July Weekday Avg. June Weekday Scenario 2 Shutdown during the week prior to an event This graph is based on the scenario described in Example The event occurs on the Monday after a shutdown week, with a holiday in the week prior to shutdown. Evaluation: The original simple rolling average method did not account for shutdowns. The dark blue line at the bottom of the graph clearly shows how a customer s load would be understated if an extended shutdown occurred prior to an event. The lighter blue line represents the average using the 5 highest intervals out of the last 10 days. In this example, the 5 highest interval method is a close match to using the simple rolling average and excluding the shutdown days. This requires that the customer would have to declare the shutdown days to the CSP and the ISO 30 days in advance to prevent gaming. Both these methods tend to overstate the monthly average for the preceding month, June, but not as dramatically as in Scenario 1. The day type method was calculated two ways: including the shutdown day (purple line) and excluding the shutdown day (brown line). Here the day type method shows more of a variance with the monthly average early in the day and only comes close to the average late in the day when the shutdown day is eliminated from the average.

8 The method not shown in this example is the provision explained in item 2.4.3: Exclude the value from any hour in which the actual load in that hour is more than 50% greater or more than 50% less than the corresponding hourly rolling average after all other exclusions. There must be a minimum of 7 and a maximum of 10 hourly weekday values for every hour. This method was not plotted because for this customer, no intervals were greater or less than 50% of the hourly average. Conclusion: The highest 5 interval method works in this scenario because the event occurred following a shutdown week. The hourly average is still overstated, but not as much as in the case where no events or holidays occur. Eliminating declared shutdown days from the average also tends to overstate the hourly averages, but it may appease the customers who feel this is an important feature. Again, this method would require that the CSP be notified of a shutdown 30 days in advance and it must provide this information to the ISO when the customer s load is submitted for payment. The day type average method showed the greatest amount of variance from the average monthly weekday profile and the other methods mentioned above. Clearly we need some method for taking genuine shutdowns into account when computing the simple rolling average. The provision in accounts for dramatic changes in load, but makes the calculation more complex. The alternative would be that shutdowns must be declared 30 days in advance in order to be excluded from the simple rolling average calculation. This will require additional administrative work for the CSPs, but simplifies the calculation. I would like your opinions on one additional issue: If an Emergency Demand Response Program (EDRP) event is called while a customer is shut down, should that customer be eligible for payment under the EDRP? Consider: In order to exclude the customer from participation of an EDRP event that occurs during the customer s shutdown, the LSE and ISO would have to know that the customer intended to be shut down on the day of the event. It is possible that the customer could have a one-day shutdown that occurs on the same day as an event. In this case, who would determine (and how) whether the customer shut down for reasons other than the EDRP event? Customers who are shut down may receive windfall payments for performance. Please review this revised recommendation for assessing performance and return your comments to the group by the end of the day Monday, January 22, Regards,

9

10 Example 2.3 events Simple Rolling Average with no holidays or EDRP occurs on May 3, 2001 Average includes April 19, 20, 23, 24, 25, 26, 27, 30, May 1 and May 2 (10 weekdays prior to day of event) For each hour, the average will be made up of the sum of the loads for the hour divided by 10 (or the number of days to be included as described in items and 2.3.1). For example, the average for hour ending 01:00 will be the sum of the loads from the hour ending 01:00 for each of the 10 days, divided by 10. Time 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 Day # Day # Day # Day # Day # Day # Day # Day # Day # Day# Sum 1,250 1,400 1,550 1,700 1,850 2,000 2,150 2,300 Averag e

11 Example Simple Rolling Average with a holiday Holiday occurs on May 30, 2001 Average includes May 16, 17, 18, 21, 22, 23, 24, 25 and May 29 (9 weekdays prior to day of event Memorial Day, May 28, 2001 is excluded from average) Time 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 Day # Day # Day # Day # Day # Day # Day # Day # Day # Sum 1,050 1,200 1,350 1,500 1,650 1,800 1,950 2,100 Averag e

12 Example Simple Rolling Average with a holiday and multiple EDRP events within the 10 days prior to another EDRP event Holiday occurs on July 6, 2001 Average includes June 21, 25, 27, 28, July 2, 3, and 5 (7 weekdays prior to day of event Excluded from average: NYISO events of 6/22, 6/26 and 6/29 plus holiday - Independence Day, 7/4) Time 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 Day # Day # Day # Day # Day # Day # Day # Sum ,250 1,400 1,550 1,700 1,850 Averag e

13 Example Simple Rolling Average with high/low usage hour exclusions* Holiday occurs on July 16, 2001 Shutdown occurs from July 9 through July 13, 2001 Average includes June 27, 28, 29 and July 2, 3, 5 and 6 (7 weekdays prior to day of event Excluded from average: holiday - Independence Day, 7/4) *none of the intervals in the sample data for the days used in the average were 50% greater or less than the average.

14 Example 2.5 Simple Rolling Average Calculation for Weekend days occurs on June 16, 2001 Average includes May 26, 27, June 2, 3, 9, and June 10 (6 weekend days prior to day of event) For each hour, the average will be made up of the sum of the loads for the hour divided by 6 (or the number of days to be included as described in items 2.5.1). For example, the average for hour ending 01:00 will be the sum of the loads from the hour ending 01:00 for each of the 6 days, divided by 6. Time 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 Day # Day # Day # Day # Day # Day # Sum Averag e

15 Example Simple Rolling Average Calculation for Weekend days with weekend EDRP events within 3 weeks of one another occurs on June 30, 2001 Average includes June 9, 10, 17, 23 and June 24 (5 weekend days prior to day of event Excluded from average: June 16 because another event occurred on that weekend day). Time 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 Day # Day # Day # Day # Day # Sum Averag e