Regulation Cost Forecasting Model for Systems with High Renewable Energy Penetration Based on Stochastic Distribution of Net Load Modeling

Abstract

With the increasing installed capacity of wind power and PV, the strong randomness of power generation makes the requirements of power systems for regulation and other ancillary services increase. However, the traditional regulation requirement prediction method cannot meet the problem of randomness on both sides of the plant and the user well. Therefore, this paper designs a regulation requirement forecasting method based on netload random distribution modeling. Combined with the hypothetical typical operation scenario of the Chinese power system in 2025, the total cost of regulation is predicted. The results show that China’s total cost of regulation can reach 10.62 billion yuan in 2025. And the sensitivity test results show that the total cost of regulation increases with the decrease of sub-period and with the increase of coverage of random fluctuation of net load.