基于改进GSO算法的变电站蓄电池组监测网络优化方法

Optimization Method of Substation Battery Monitoring Network Based on Improved GSO Algorithm

针对当前现有变电站蓄电池组监测网络在运行中存在监测精度低、监测运行能耗大的问题,引入改进萤火虫群优化(Glowworm Swarm Optimization,GSO)算法,开展变电站蓄电池组监测网络优化方法研究。针对监测网络中的各个节点,计算运行能耗。在变电站蓄电池组监测过程中,以网络运行消耗能量最小为优化目标,完成蓄电池组监测网络优化目标函数与约束条件设计。利用改进GSO算法,对监测网络拓扑结构进行优化。实验证明,利用新优化方法优化后的监测网络的监测精度更高,且网络运行能耗得到显著降低,具有极高的应用价值。

In view of the problems of low monitoring accuracy and high energy consumption in the operation of the existing substation battery monitoring network,an improved Glowworm Swarm Optimization(GSO)algorithm was introduced to study the optimization method of the substation battery monitoring network.The energy consumption was calculated for each node in the monitoring network.In the process of substation battery monitoring,the minimum energy consumption of network operation is the optimization goal,and the optimization objective function and constraint conditions of battery monitoring network were designed.Using the improved GSO algorithm,the monitoring network topology was optimized.The experiment shows that the monitoring precision of the network optimized by the new optimization method is higher,and the energy consumption of the network is significantly reduced.The new optimization method has high application value.