基于改进粒子群算法的高压配电网拓扑自动成图技术

Automatic Mapping Technology of High-voltage Distribution Network Topology Based on Improved Particle Swarm Algorithm

配电网拓扑成图能够以图形化的方式显示配电网结构,这种可视化有助于操作人员更好地理解和监控网络,从而提高电网可靠性和自动化运营。但现有的拓扑成图技术更多仍依赖于人工绘制,针对高压配电网拓扑成图人工工作量大且布局不合理的问题,该文基于改进粒子群算法设计一种针对高压配电网的拓扑自动成图技术,首先,对数据模型进行抽取,结合布置图框架设计原则和布线规则,确定以线路交叉和线路总长度最小作为复合优化目标;然后,通过对基本粒子群算法的惯性权重和局部粒子的搜索方式进行改进,提升全局寻优水平。实验仿真结果表明,所提方法求解时间短,完成率较高,整体布局更美观合理,可以很好地解决配电网拓扑自动成图问题。

The power distribution network topology mapping allows for the visualization of the structure of the distribution network.Such visualization aids operators in better understanding and monitoring the network,thus enhancing grid reliability and automated operations.However,current topology mapping techniques largely rely on manual drawing.In view of the significant manual workload and often suboptimal layout associated with high-voltage distribution network topology mapping,this paper proposes an automated topology mapping technique for high-voltage distribution networks based on an improved particle swarm optimization algorithm.Firstly,the data model is extracted.By integrating layout framework design principles and wiring rules,the optimization goals are set to minimize line crossings and the total length of lines.Enhancements to the inertia weight and local particle search method of the basic particle swarm algorithm are introduced,elevating its global optimization capabilities.Simulation results indicate that the proposed method offers shorter computation times,higher completion rates,and an overall more aesthetically pleasing and logical layout.It addresses the challenges of automated topology mapping for power distribution networks effectively.