基于改进灰狼算法的电力管廊覆盖优化技术  

Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm

作　　者：钟成 翟迪 陆阳 刘晓波[3] 王心如 赵雄文[3] ZHONG Cheng;ZHAI Di;LU Yang;LIU Xiaobo;WANG Xinru;ZHAO Xiongwen(State Grid Xiong’an New Area Electric Power Supply Company,Xiong’an 071000,China;State Grid Smart Grid Research Institute Co.,Ltd.,Beijing 102209,China;State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University,Beijing 102206,China)

机构地区：[1]国网雄安新区供电公司,河北雄安071000 [2]国网智能电网研究院有限公司,北京102209 [3]华北电力大学新能源电力系统国家重点实验室,北京102206

出　　处：《中国电力》2023年第8期68-76,共9页Electric Power

基　　金：国家电网有限公司科技项目(面向城市电网的本地融合通信网络体系及内生可信安全关键技术研究,5700-202213221A-1-1-ZN)。

摘　　要：针对狭长电力管廊环境下无线传感网络覆盖受不规则形状、障碍物及电磁干扰影响导致通信质量降低的问题,构建了基于最低接入速率约束的电力监测覆盖感知模型,提出结合神经元映射和差分进化的改进灰狼覆盖优化算法。首先,通过神经元混沌映射生成均匀的初始种群。然后,利用非线性收敛因子平衡全局和局部搜索能力。最后,引入差分进化算法对灰狼个体进行变异。通过仿真分析对比了不同覆盖优化方法,结果表明:所提算法具有较强的搜索能力,能够在狭长电力管廊环境下显著提高网络的覆盖性能并满足待监测节点的通信需求。To address the problem of reduced communication quality in narrow underground power pipe gallery,where wireless sensor network coverage is affected by irregular shapes,obstacles,and electromagnetic interference,a power monitoring coverage sensing model is constructed based on the minimum access rate constraint,and an improved gray wolf coverage optimization algorithm is proposed by combining neuron mapping and differential evolution.Firstly,a uniform initial population is generated by neuron chaos mapping.Then,the nonlinear convergence factor is used to balance the global and local search ability.And finally,a differential evolution algorithm is introduced to mutate the gray wolf individuals.A comparative simulation analysis is made of various coverage optimization methods,and the results show that the proposed algorithm has robust search capabilities and it can significantly improve the network coverage performance in the narrow underground power pipe galleries,while effectively satisfying the communication needs of the monitored nodes.

关 键 词：电力地下管廊 无线传感器网络 覆盖优化 改进灰狼算法 差分进化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TM73[自动化与计算机技术—控制科学与工程]