Reliability Assessment of Renewable Energy Optimized Operation System with Energy Storage System Based on Particle Swarm Optimized Algorithm

The Copula function was used to fit the edge distribution functions of wind speed and light intensity, and the related wind speed and light intensity scenarios were generated, and a typical daily scenario was generated based on K-means clustering, and the joint output reliability model of the renewable energy system (RES) and the energy storage system (ESS) was established. In the pre-simulation stage, the Markov method and Monte Carlo method are used to generate the working state transition sequence of wind generator turbine (WGT) and Photovoltaic (PV), and the improved particle swarm optimization (PSO) algorithm is used to solve the model with the goal of maximizing the operating benefit of the joint system and the minimum fluctuation of grid-connected power. Finally, the joint system is connected to the IEEE RTS79 system, and the reliability index of the power system with RES is evaluated by using the sequential Monte Carlo method. The numerical example shows that the multi-objective joint system operation model proposed in this paper can improve the reliability and economy of the power system.