Multi-Objective Optimization Strategy of Microgrid Based on Cooperative Operation of Optical Storage in Industrial Park

With the continuous development of photovoltaic power generation and energy storage technology, microgrid systems in industrial parks have gradually become an important means to achieve efficient use of green energy. Aiming at the energy demand of industrial parks, this paper proposes a multi-objective optimization strategy based on the cooperative operation of photovoltaic power generation and energy storage. By analyzing the fluctuation of photovoltaic power generation and the charge-discharge characteristics of the energy storage system, a multi-objective optimization model which can achieve energy balance and maximize economic benefits under different working conditions is constructed. Optimization objectives cover many aspects such as maximizing photovoltaic utilization, minimizing energy storage costs, matching load demand and reducing environmental pollution. In order to solve the multi-objective optimization problem, the non-dominated sorting genetic algorithm (NSGA-II) was used to solve the optimization model, and the actual data of the industrial park was simulated and verified. The results show that the optimization strategy can effectively improve the photovoltaic consumption rate, reduce the operating cost of the system, and ensure the stable operation of important loads, which provides a new technical solution for energy management in industrial parks.