摘要
针对多类型分布式电源接入配电网后造成配电网拓扑结果复杂,而传统的遗传算法寻优搜索范围大、局部寻优易收敛等问题,本文提出一种基于改进蝙蝠算法的配电网重构算法。该算法利用回支关联动态矩阵切割合并电网回路,在保证配电网辐射状拓扑结构的同时简化拓扑搜索;利用K-means聚类对种群数据进行初始化聚类,解决局部最优;利用Powell局部搜索,加快算法的收敛速度。仿真实验表明,与其他标准蝙蝠算法和粒子优化算法相比,本文改进的算法有较快的收敛速度和较高的寻优精度;在配电网重构中,本文改进算法与其他算法相比,不仅有效地降低了原配电网的有功耗损还提高了节点电压幅值,一定程度上改善了系统的电压质量。
In view of such problems as complex network topology structure due to access to the distribution network of multiple types of distributed power supply,the traditional genetic algorithm has the problem of big optimization search range and easy convergence by local optimization. In this paper,a kind of distribution network reconfiguration algorithm based on improved bat algorithm is proposed. The algorithm uses the back branch correlation dynamic matrix to cut and merge the network loop,which simplifies the topology search while ensuring the radial topology of the distribution network. The K-means clustering is used to initialize the population data to solve the local optimum. In addition,the Powell local search is used to accelerate the convergence rate of the algorithm. It is shown by the simulation experiment that the improved algorithm,compared to other standard bat algorithm and particle swarm optimization algorithm,has faster convergence speed and higher searching accuracy. In the reconstruction of distribution network,the improved algorithm proposed in this paper,with comparison to other algorithms,not only reduces effectively the active power loss of original distribution network,but also improves the amplitude of node voltage and,to a certain extent,improves the voltage quality of the system.
出处
《电力电容器与无功补偿》
北大核心
2018年第1期124-131,共8页
Power Capacitor & Reactive Power Compensation
基金
国家电网公司科技项目(5215J01506AN)
