A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm
Accurate localization of partial discharge in GIS equipment remains a key focus of daily maintenance for substations, which can be achieved through advanced detection and location techniques, as well as regular maintenance and testing of the equipment. However, there is currently an issue with low a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/6/2928 |
| _version_ | 1797612032857473024 |
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| author | Hao Qiang Qun Wang Hui Niu Zhaoqi Wang Jianfeng Zheng |
| author_facet | Hao Qiang Qun Wang Hui Niu Zhaoqi Wang Jianfeng Zheng |
| author_sort | Hao Qiang |
| collection | DOAJ |
| description | Accurate localization of partial discharge in GIS equipment remains a key focus of daily maintenance for substations, which can be achieved through advanced detection and location techniques, as well as regular maintenance and testing of the equipment. However, there is currently an issue with low accuracy in the localization algorithm. Aiming at the problems of low precision and local optimization of the swarm intelligence algorithm in partial discharge localization system of GIS equipment, this paper proposes a 3D localization algorithm based on a time difference of arrival (TDOA) model of the improved artificial fish swarm algorithm (IAFSA). By introducing the investigation behaviour of the artificial bee colony(ABC) algorithm into the artificial fish swarms algorithm (AFSA), this algorithm is more efficient to jump out of the local extremum, enhance the optimization performance, improve the global search ability and overcome the premature convergence. Furthermore, more precise positioning can be achieved with dynamic parameters. The results of the testing function show that IAFSA is significantly superior to AFSA and particle swarm optimization (PSO) in terms of positioning accuracy and stability. When applied to partial discharge localization experiments, the maximum relative positioning error is less than 2.5%. This validates that the proposed method in this paper can achieve high-precision partial discharge localization, has good engineering application value, and provides strong support for the safe operation of GIS equipment. |
| first_indexed | 2024-03-11T06:36:09Z |
| format | Article |
| id | doaj.art-a8e27d0e4857405eb442eaa83b0223be |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T06:36:09Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-a8e27d0e4857405eb442eaa83b0223be2023-11-17T10:52:54ZengMDPI AGEnergies1996-10732023-03-01166292810.3390/en16062928A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms AlgorithmHao Qiang0Qun Wang1Hui Niu2Zhaoqi Wang3Jianfeng Zheng4School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, ChinaSchool of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, ChinaSchool of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, ChinaSchool of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, ChinaSchool of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, ChinaAccurate localization of partial discharge in GIS equipment remains a key focus of daily maintenance for substations, which can be achieved through advanced detection and location techniques, as well as regular maintenance and testing of the equipment. However, there is currently an issue with low accuracy in the localization algorithm. Aiming at the problems of low precision and local optimization of the swarm intelligence algorithm in partial discharge localization system of GIS equipment, this paper proposes a 3D localization algorithm based on a time difference of arrival (TDOA) model of the improved artificial fish swarm algorithm (IAFSA). By introducing the investigation behaviour of the artificial bee colony(ABC) algorithm into the artificial fish swarms algorithm (AFSA), this algorithm is more efficient to jump out of the local extremum, enhance the optimization performance, improve the global search ability and overcome the premature convergence. Furthermore, more precise positioning can be achieved with dynamic parameters. The results of the testing function show that IAFSA is significantly superior to AFSA and particle swarm optimization (PSO) in terms of positioning accuracy and stability. When applied to partial discharge localization experiments, the maximum relative positioning error is less than 2.5%. This validates that the proposed method in this paper can achieve high-precision partial discharge localization, has good engineering application value, and provides strong support for the safe operation of GIS equipment.https://www.mdpi.com/1996-1073/16/6/2928AFSAGIS equipmentpartial dischargeprecise localization |
| spellingShingle | Hao Qiang Qun Wang Hui Niu Zhaoqi Wang Jianfeng Zheng A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm Energies AFSA GIS equipment partial discharge precise localization |
| title | A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm |
| title_full | A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm |
| title_fullStr | A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm |
| title_full_unstemmed | A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm |
| title_short | A Partial Discharge Localization Method Based on the Improved Artificial Fish Swarms Algorithm |
| title_sort | partial discharge localization method based on the improved artificial fish swarms algorithm |
| topic | AFSA GIS equipment partial discharge precise localization |
| url | https://www.mdpi.com/1996-1073/16/6/2928 |
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