Abstract
Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 1.6% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.
Original language | American English |
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Number of pages | 6 |
State | Published - 2023 |
Event | 50th IEEE Photovoltaic Specialists Conference - San Juan, Puerto Rico Duration: 11 Jun 2023 → 16 Jun 2023 |
Conference
Conference | 50th IEEE Photovoltaic Specialists Conference |
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City | San Juan, Puerto Rico |
Period | 11/06/23 → 16/06/23 |
Bibliographical note
See NREL/CP-5400-88820 for paper as published in proceedingsNREL Publication Number
- NREL/CP-5D00-85148
Keywords
- potential high limit
- PV
- reliability services
- spinning reserves