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Distributed Renewable Generation Profiling Methodology ERCOT Load Profiling March 4, 2008.

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Presentation on theme: "Distributed Renewable Generation Profiling Methodology ERCOT Load Profiling March 4, 2008."— Presentation transcript:

1 Distributed Renewable Generation Profiling Methodology ERCOT Load Profiling March 4, 2008

2 2 Distributed Renewable Generation (DRG) TDSPs responded to ERCOT’s request for information on premises that have DRG with a generation capacity < 50 kW. What is out there? Five of the ESI IDs included above have PV and wind generation. This means there are currently 87 unique ESI IDs known to have one or more type of DRG (< 50 kW).

3 3 DRG Sites – Available Information Even though TDSPs provided the best information available there are many barriers to analyzing DRG sites. For example: Given the above, it is difficult to identify the effects of DRG from the available meter read data. An interconnection agreement date is not necessarily meaningful. DRG may have been operating for years before agreement is signed, or may not operate until well after agreement is completed. Sometimes inverter capacity is known—but generator capacity is not known. Presently, energy exported to the Distribution System (energy outflow from the premise) is only available for a handful of ESI IDs.

4 4 Residential DRG – Photovoltaic (PV)

5 5 Residential PV

6 6 Due to potential confidentiality issues, a chart displaying both DRG capacity (kW) and annual usage (kWh) is not presented here. However, the correlation of the two variables is 0.217 (excluding the outlier). The table of ESI ID counts below may help illustrate the relationship. Each respective variable’s median value serves as the break between high and low.

7 7 Business PV

8 8

9 9 Residential DRG – Wind

10 10 Residential Wind

11 11 Residential Wind For wind ESI IDs the correlation of DRG capacity and annual usage is 0.153. The following table of ESI ID counts uses each respective variable’s median value as the break between high and low. Values equal to the median were treated as low.

12 12 Business Wind

13 13 Business Wind

14 14 PV Generation How much energy will a PV array produce? Given the currently known average Residential PV generation capacity of 3.5 kW (AC), at 100% capacity factor there would be (3.5 * 24 =) 84 kWh generated per day. If we utilize the Interstate Renewable Energy Council’s irradiance estimate of 20% from its presentation to the DGTF on 12/04/07, the estimated yield would be 16.8 kWh per day. Applying the above to the average Business PV generation capacity of 8.9 kW (AC) yields an estimated 42.7 kWh per day. For simplicity, the energy produced by a PV array is presented in most of the slides as a sine wave spanning 9:00 AM to 5:00 PM.

15 15 Residential PV

16 16 Residential PV – Building the Profile How would a daily PV load profile be derived? To build a PV profile (consistent with what has come to be known as ‘Option 5’) for a specific profile type and weather zone, e.g., for PV ESI ID that is currently assigned RESHIWR NCENT: This PV profile can then be used in the Data Aggregation process. The kWh ‘outflow to the grid’ would be applied in settlement evenly across all days, spanning the intervals from 11:00 AM to 3:00 PM. 1. For a specific day, take the current RESHIWR NCENT profile; 2. Multiply each value by 0.89 to scale it to the average PV ESI ID (more info in Appendix A); 3. Scale it such that when the PV generation shape is applied in the next step the kWh will remain the same; 4. Subtract the values of the PV generation shape to produce the RESHIPV NCENT load profile.

17 17 Residential PV – Building the Profile

18 18 Residential PV – Building the Profile

19 19 Residential PV – Building the Profile

20 20 Residential PV – Building the Profile

21 21 Residential PV – Applying the Profile

22 22 Residential PV – Applying the Profile

23 23 Residential PV – Applying the Profile

24 24 Residential PV – Applying the Profile In the preceding slide the ESI ID’s usage was higher than that of the PV profile. What if an ESI ID had significantly lower usage?

25 25 Residential PV – Applying the Profile

26 26 Business PV – Building the Profile

27 27 Business PV – Building the Profile

28 28 Business PV – Building the Profile

29 29 Business PV – Building the Profile

30 30 Business PV – Applying the Profile

31 31 Business PV – Applying the Profile

32 32 Business PV – Applying the Profile

33 33 PV Model Building Following are some additional details planned for inclusion in the load profile models for PV ESI IDs. The examples shown are for Residential, but the same methodology would be applied to Business as well.

34 34 Residential PV Generation assumptions –Represented using Sine function –Begin/End Times for PV Generation are day of year & weather zone specific 1 hour after sunrise 1 hour before sunset –Daily kWh Generation is based on 3.5 kW with a 20% capacity factor Average daily PV Generation is 16.8 kWh Average daily PV produces output for 10.2 hours (range: 7.9 – 12.4) Daily PV Generation is prorated based on hours of generation for the day compared to an average day Example day with 8 hours of Generation: Residential PV – Building the Model

35 35 Residential PV Model assumptions –Standard Profile multiplied by 1.17 Where: Average PV premise Daily kWh = 69.83 (adjusted for PV Gen) Average Standard Profile Daily kWh = 59.58 – Subtract PV Generation from scaled up Profile – if result in an interval is negative, set to zero Beta test MetrixND Project file has been developed for Reshiwr_North – Results for 2005 shown graphically on the next 3 slides Residential PV – Building the Model

36 36 PV Gen PV Profile Standard Profile Residential HIWR North PV

37 37 PV Gen PV Profile Standard Profile Residential HIWR North PV

38 38 PV Gen PV Profile Standard Profile Residential HIWR North PV

39 39 Wind – Building the Profile How would a daily wind load profile be derived for Residential and Business? At this point it appears that energy from distributed wind generation would be spread evenly across all hours. Though a ‘wind’ profile type assignment would still be needed to address kWh outflow to the distribution system, the standard profile for the respective profile type (but renamed) would still be used in settlement. Wind-generated ‘outflow to the grid’ would likely be spread evenly to all hours in settlement, as well.

40 40 Residential Wind – Applying the Profile

41 41 DRG Questions or comments?

42 42 Appendix A – Profile Scalar Scalar for the ‘standard’ load profile: Slide 5 shows the average kWh ‘inflow to premise’ to be 13,668 for 2007. The profile type and weather zone combination that had the most reported PV generation was RESHIWR NCENT. That combination’s kWh for all of 2007 from the new profile models was 16,281. The ratio of these two values is approximately 0.84. Using this value as a scalar in the first step of building a PV load profile serves two purposes: 1.It maintains a proportional PV output as the ESI ID’s kWh ‘inflow to premise’ varies; and 2.It prevents the PV load profile value from going negative.

43 43 Appendix A – Profile Scalar Scalar for the ‘standard’ load profile: Slide 5 shows the average kWh ‘inflow to premise’ to be 13,668 for 2007. To determine the scalar for the standard load profile, the following ratio was calculated for each Residential PV ESI ID: kWh load for 2007 / 2007 kWh for respective profile type & weather zone The average of the 51 ratios (excluding the outlier) is approximately 0.89. Using this value as a scalar in the first step of building a PV load profile serves two purposes: 1.It maintains a proportional PV output as the ESI ID’s kWh ‘inflow to premise’ varies; and 2.It prevents the PV load profile value from going negative.

44 44 Appendix B – Insolation Across Texas Source: InfinitePower.org

45 45 Appendix C – Sunrise Times

46 46 Appendix D – Sunset Times


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