基于Spark和粒子群算法的分布式配电网重构方法

Reconfiguration Method for Distribution Network Based on Spark and PSO Algorithm

当前配电网结构日趋复杂且有分布式电源大量接入,现有人工智能算法进行配电网优化重构后会出现大量数据,导致算法搜索空间暴增、处理效率下降。为提高传统粒子群算法的处理效率,提出了一种粒子群优化算法,以配电网故障后重构的网损最小为目标函数,建立配电网故障后重构模型。充分利用分布式集群计算资源,通过Spark框架对优化粒子群算法并行化操作,以提升算法的处理效率。

At present,the structure of the distribution network is becoming more and more complex,and there are a large number of distributed power sources.After the optimization and reconstruction of the distribution network by the existing artificial intelligence algorithms,a large amount of data will appear,resulting in a sharp increase in the search space of the algorithm and a decrease in processing efficiency.In order to improve the processing efficiency of traditional particle swarm optimization,a particle swarm optimization algorithm is proposed.Taking the minimum network loss reconstructed after a distribution network fault as the objective function,the post-fault reconstruction model of the distribution network is established.It makes full use of distributed cluster computing resources and parallelizes the optimization particle swarm algorithm through the Spark framework to improve the processing efficiency of the algorithm.