Power system multi-target energy storage optimization method based on improved genetic algorithm

An improved genetic algorithm-based multi-target energy storage optimization method for a power system comprises the following steps of: firstly, constructing an energy storage multi-target optimization model in which the minimum total energy storage cost is configured as a target function in a manner of configuring energy storage on a power supply side, a power grid side and a load side; and then solving the constructed energy storage multi-objective optimization model by adopting a genetic algorithm of non-dominated sorting based on a Pareto optimal concept to obtain an energy storage optimization scheme, including configuration places and capacities of energy storage. Smooth new energy output at the power supply side, peak clipping and valley filling at the power grid side and cost reduction at the load side through peak-valley arbitrage are realized at the same time. 一种基于改进遗传算法的电力系统多目标储能优化方法，先针对在电源侧、电网侧、负荷侧均配置储能的方式构建配置储能总成本最小为目标函数的储能多目标优化模型，然后采用基于Pareto最优概念的非支配排序的遗传算法对构建的储能多目标优化模型进行求解，得到储能优化方案，包括各储能的配置地点和