基于改进灰狼算法的电力管廊覆盖优化技术

doi:10.11930/j.issn.1004-9649.202303023

中国电力 ›› 2023, Vol. 56 ›› Issue (8): 68-76.DOI: 10.11930/j.issn.1004-9649.202303023

• 面向电网设备状态感知的低功耗无线传感网技术及应用 • 上一篇下一篇

基于改进灰狼算法的电力管廊覆盖优化技术

钟成¹, 翟迪², 陆阳², 刘晓波³, 王心如³, 赵雄文³

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

收稿日期:2023-03-06 修回日期:2023-05-22 发布日期:2023-08-28
作者简介:钟成（1970—），男，硕士，高级工程师（教授级），从事电力物联网、智能电网、智能传感与量测技术研究，E-mail：hebeizhongc@163.com;翟迪（1989—），男，通信作者，博士，从事物联网、无损探伤、室内定位技术研究，E-mail：dasluogu@163.com;陆阳（1984—），男，博士，高级工程师（教授级），从事电力传感网、智能电网、电力传感技术研究，E-mail：luyang@geiri.sgcc.com.cn;刘晓波（2000—），男，硕士研究生，从事新型电力系统、无线传感网络、电力物联网研究，E-mail：3025066980@qq.com
基金资助:
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）。

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

ZHONG Cheng¹, ZHAI Di², LU Yang², LIU Xiaobo³, WANG Xinru³, ZHAO Xiongwen³

1. State Grid Xiong'an New Area Electric Power Supply Company, Xiong'an 071000, China;
2. State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China;
3. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Received:2023-03-06 Revised:2023-05-22 Published:2023-08-28
Supported by:
This work is supported by Science and Technology Projects of SGCC (Research on Local Integrated Communication Network System and Endogenous Security Technologies Oriented to Urban Grid, No.5700-202213221A-1-1-ZN).

摘要/Abstract

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。

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

Abstract: 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.

Key words: underground power pipe gallery, wireless sensor networks, coverage optimization, improved gray wolf algorithm, differential evolution

钟成, 翟迪, 陆阳, 刘晓波, 王心如, 赵雄文. 基于改进灰狼算法的电力管廊覆盖优化技术[J]. 中国电力, 2023, 56(8): 68-76.

ZHONG Cheng, ZHAI Di, LU Yang, LIU Xiaobo, WANG Xinru, ZHAO Xiongwen. Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm[J]. Electric Power, 2023, 56(8): 68-76.

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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

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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

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