Research on improving requirement of renewable energy forecasting for system anti-disturbance

Due to the integration of renewable energy, the maximum output of conventional power plants is reduced, and the change of peak valley difference is no longer periodic. In order to cope with the fluctuation of renewable energy, the system needs to increase the rotating reserve capacity. At present, power supply is mainly thermal power in China. The inflexibility of thermal power switch and the existence of minimum technical output increase the volatility of start-up response to renewable energy, and limit the output of renewable energy in the period of low load and renewable energy. Predicting the output power of renewable energy and reducing the uncertainty of renewable energy fluctuation is one of the effective means to reduce the redundant standby capacity of the system. The increase of reserve capacity is related to the prediction accuracy of output power of renewable energy stations. Therefore, renewable energy power prediction is of great significance to the safe and economic operation of power system. According to the requirements of relevant documents and regulations of the national energy administration, all grid connected renewable energy stations need to establish a renewable energy power prediction system. In this paper, hundreds of renewable energy power forecasting service providers has emerged. However, the performance and prediction accuracy of renewable energy power prediction results are uneven, there is a lack of unified test standards and test platform, and an effective integration mechanism and identification method have not been established. Therefore, it is necessary to establish relevant evaluation mechanisms and provide third-party evaluation services, so as to provide a fair reference for selecting strong renewable energy production scheduling support services. However, different from conventional power supply, renewable energy has random volatility, and large-scale renewable energy grid connection brings challenges to the security, stability and economic operation of power grid.