Capacity optimization of Energy Storage Based on Intelligent optimization Algorithm and Photovoltaic Power Prediction Error Data

The battery energy storage system (BESS) is an effective means to compensate the photovoltaic (PV) power prediction errors, so as to improve the reliability of the PV power prediction results as the power grid dispatching reference. A bi-level capacity optimization model of BESS is established to solve the problem that the economy and technology are difficult to balance. Based on the prediction errors compensation strategy considering the energy balance of BESS charge-discharge, the operation layer optimizes the operating parameters by minimizing the index for the balance of BESS charge-discharge and the penalty cost of prediction errors. And the economic layer optimizes the energy storage capacity with objective of maximizing the net income of PV energy storage system. Then, through the harmony search and multi-objective particle swarm optimization (HS-MOPSO) algorithm, a comprehensive optimal capacity configuration scheme is obtained. Finally, the validations based on practical data show the advantages of the proposed method.