基于粒子群优化的加权伏罗诺伊图变电站规划

针对变电站规划问题，提出一种基于粒子群优化的加权伏罗诺伊图(weighted Voronoi diagram，WVD)变电站规划方法，在变电站数量和容量组合确定的情况下，对变电站的位置和供电范围进行优化。根据变电站及负荷分布的特点，给出全新的权重计算方法，其权重可自适应调整，从而形成基于加权伏罗诺伊图的变电站规划方法。该方法在保证算法收敛的同时，使变电站的位置及供电范围更合理。利用粒子群优化算法的全局搜索特点，实现了基于粒子群优化的加权伏罗诺伊图(particle swarm optimization-weighted voronoi diagram，PSO-WVD)变电站选址及供电范围规划。算例结果表明所提方法无论在变电站站址的确定方面，还是在变电站供电范围的划分方面都比单一方法可靠、合理。

Substation Location Planning of the Weighted Voronoi Diagram Based on Particle Swarm Optimization Algorithm

This paper presented a novel method for substation location planning of the weighted Voronoi diagram (WVD) based on particle swarm optimization (PSO) algorithm, which could optimize the location and power supply area of substations while the number and capacity of the substations were predefined. A new weighting coefficient expression was proposed based on the characteristic of the substation and load distribution. By introducing the self-adaptation of the weighting coefficient, the substation location planning method was presented based on the weighted Voronoi diagram, which could get more reasonable location and power supply area of the substations with keeping the convergence. Combining the global searching ability of the PSO, a particle swarm optimization-weighted voronoi diagram (PSO-WVD) substation location planning method was proposed to optimize the location and power supply area of the substations simultaneously. Test results indicate that the method is more reliable and reasonable than each method.