Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm
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...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2023-08-01
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| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303023 |
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| _version_ | 1850037386962010112 |
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| author | Cheng ZHONG Di ZHAI Yang LU Xiaobo LIU Xinru WANG Xiongwen ZHAO |
| author_facet | Cheng ZHONG Di ZHAI Yang LU Xiaobo LIU Xinru WANG Xiongwen ZHAO |
| author_sort | Cheng ZHONG |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-0270264eebfa447bb811fe69e99a606b |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2023-08-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-0270264eebfa447bb811fe69e99a606b2025-08-20T02:56:52ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492023-08-01568687610.11930/j.issn.1004-9649.202303023zgdl-56-07-zhongcheng1Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf AlgorithmCheng ZHONG0Di ZHAI1Yang LU2Xiaobo LIU3Xinru WANG4Xiongwen ZHAO5State Grid Xiong’an New Area Electric Power Supply Company, Xiong’an 071000, ChinaState Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, ChinaState Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaTo 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.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303023underground power pipe gallerywireless sensor networkscoverage optimizationimproved gray wolf algorithmdifferential evolution |
| spellingShingle | Cheng ZHONG Di ZHAI Yang LU Xiaobo LIU Xinru WANG Xiongwen ZHAO Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm Zhongguo dianli underground power pipe gallery wireless sensor networks coverage optimization improved gray wolf algorithm differential evolution |
| title | Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm |
| title_full | Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm |
| title_fullStr | Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm |
| title_full_unstemmed | Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm |
| title_short | Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm |
| title_sort | coverage optimization technology of power pipe gallery based on improved gray wolf algorithm |
| topic | underground power pipe gallery wireless sensor networks coverage optimization improved gray wolf algorithm differential evolution |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303023 |
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