Stochastic optimization of hybrid energy storage considering wind power and photovoltaic correlation to smooth fluctuation

With the increasing degree of grid integration of renewable energy sources (RES), their power uncertainty has a great impact on the safety and economy of power system operation. Energy storage can effectively mitigate the fluctuations caused by renewable energy uncertainty due to its flexible charging and discharging characteristics. In this paper, a hybrid energy storage system (HESS) optimization and regulation scheme that considers the uncertainty and correlation of wind power and photovoltaic (PV) is proposed to economically and efficiently achieve the smoothing of fluctuations in renewable energy output. Typical scenarios of wind power and PV are firstly generated using kernel density estimation and copula functions, and then the frequency components of each typical scenario are extracted based on empirical mode decomposition (EMD). Finally, a stochastic optimization model of HESS is constructed to obtain the grid-connected power of renewable energy and the regulation plan of each energy storage device.