Multi-Objective Optimization of Capacity and Power Allocation for Energy Storage Systems in Wind-Photovoltaic- Energy Storage Power Station Microgrid

Energy storage system (ESS) deployment in wind-Photovoltaic (PV) microgrids effectively mitigates renewable power fluctuations and enhances grid accommodation capacity. This research develops a multi-objective optimization framework for energy storage systems in renewable-dominated microgrids, addressing both technical and economic constraints. Based on historical operational data, we establish a dual-variable optimization model that coordinates capacity allocation and power rating through time-series simulations. The model objective function covers the maximization of the daily revenue during the operation of energy storage power station (ESPS), which is of the greatest concern to each energy storage enterprise, as well as the minimization of the daily investment cost of microgrids and their operating costs during operation, to achieve a balance of interests between energy storage enterprises and microgrids. Finally, the game multi-objective hybrid optimization algorithm (GMGOA) is adopted to verify the effectiveness of the proposed method. The simulation results show that this method can determine the optimal configuration scheme of ESPS under the premise of ensuring economy, and improve the consumption rate of renewable energy and the operation efficiency of the microgrid.