A Probabilistic Method for Reserve Sizing in Power Grids With High Renewable Penetration

Power systems employ reserves to ensure there is adequate generation and storage to meet demand. With the increased use of volatile and uncertain sources of electricity such as solar and wind, the need for reserves is becoming more critical to ensure reliable supply of electricity. Due to the high cost of reserves, methods are required to determine minimal reserves needed. This work proposes a probabilistic data-driven method to determine the minimum reserve size (both power and energy) to satisfy a specified reliability requirement for a bulk power grid. The proposed method is applied to data from two balancing authorities (BPA and CAISO), and the results are compared with those from an alternate deterministic method and to those from the current reserve sizing methods employed by BPA and CAISO. The reserve requirements do not seem to be predicted by simple indicators of volatility, such as installed capacity of wind and solar, which has implications for grid planning in a renewable rich future.