基于遗传算法的分布式光伏配网储能优化配置研究

Study on Optimized Allocation of Distributed Photovoltaic Distribution Network Energy Storage Based on Genetic Algorithm

为了改善配网电能质量、实现配网负荷水平的调节,提出基于遗传算法的分布式光伏配网储能优化配置方法。在分析复合储能工作原理与蓄电池储能调峰优化的前提下,构建两阶段储能优化配置模型。第一阶段优化配置模型中,以最小电压波动、网损为目标函数,从而确定蓄电池储能的最佳接入位置。第二阶段优化配置模型中,将配网接入的最低储能设备总容量作为目标函数,从而实现储能设备容量的优化配置。通过最佳保留策略、交叉、变异率的自适应变化,对遗传过程进行优化。采用改进的遗传算法对两阶段储能优化配置模型进行求解,以此确定储能的最佳配置方案及运行优化策略。试验结果表明:该方法对配网储能进行优化配置后,配网电压波动指标明显下降至1.95%,并且网损值、电压波动指标大幅降低。该方法能够实现各类负荷的调峰,具有削峰填谷效应。

To improve the power quality of distribution network and realize the regulation of distribution network load level,the optimized allocation method of distributed photovoltaic distribution network energy storage based on genetic algorithm is proposed.Under the premise of analyzing the working principle of composite energy storage and optimization of battery energy storage peak adjustment,a two-stage energy storage optimization allocation model is constructed.In the first stage optimization allocation model,the minimum voltage fluctuation and network loss are taken as the objective function,to determine the optimal access location of battery storage.In the second stage optimization allocation model,the minimum total capacity of energy storage equipment accessed by the distribution network is taken as the objective function,to realize the optimal allocation of energy storage equipment capacity.The genetic process is optimized through adaptive changes in the optimal retention strategy,crossover,and mutation rate.The improved genetic algorithm is used to solve the two-stage energy storage optimal allocation model,to determine the best allocation scheme and operation optimization strategy of energy storage.The experimental results show that after the method optimizes the allocation of energy storage in the distribution network,the voltage fluctuation index of the distribution network decreases significantly to 1.95%,the network loss value and voltage fluctuation index reduce significantly.The method can realize the peak adjustment of all kinds of loads and has the effect of peak shaving and valley filling.