Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm
To address the problems of slow convergence speed, easy to fall into local minima and low convergence accuracy presented by previous algorithms in DC distribution network fault location, this paper adopts the improved artificial bee colony slime mould algorithm (SMA) to improve and solve. On the bas...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10155120/ |
| _version_ | 1827915341194330112 |
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| author | Tian-Xiang Ma Xin Duan Yan Xu Ruo-Lin Wang Xiao-Yu Li |
| author_facet | Tian-Xiang Ma Xin Duan Yan Xu Ruo-Lin Wang Xiao-Yu Li |
| author_sort | Tian-Xiang Ma |
| collection | DOAJ |
| description | To address the problems of slow convergence speed, easy to fall into local minima and low convergence accuracy presented by previous algorithms in DC distribution network fault location, this paper adopts the improved artificial bee colony slime mould algorithm (SMA) to improve and solve. On the basis of SMA, an adaptive adjustable feedback factor and an improved crossover operator are introduced to improve the convergence speed; artificial bee colony (ABC) algorithm is introduced to improve the search ability to jump out of local minima, and the artificial bee colony slime mould algorithm (ISMA) is formed. Firstly, based on the six-terminal DC distribution network topology, a mathematical model of bipolar short-circuit fault as well as single-pole grounded short-circuit fault is established based on a fault occurring between G-VSC and W-VSC as an example. Then the principle of the improved ISMA is introduced in detail, and a suitable fitness function is established as the measure of fault location in DC distribution network. Finally, experimental simulations are conducted to obtain fault points from the optimization search and compare them with the actual values to verify the accuracy of the algorithm. In addition, the efficiency and robustness of ISMA are further verified by comparing with other algorithms. |
| first_indexed | 2024-03-13T02:58:08Z |
| format | Article |
| id | doaj.art-f1179b6a59b6487e9e06b26d485480fc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T02:58:08Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f1179b6a59b6487e9e06b26d485480fc2023-06-27T23:00:26ZengIEEEIEEE Access2169-35362023-01-0111626306263810.1109/ACCESS.2023.328732210155120Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould AlgorithmTian-Xiang Ma0https://orcid.org/0000-0001-9449-2787Xin Duan1Yan Xu2Ruo-Lin Wang3Xiao-Yu Li4State Grid Hebei Electric Power Research Institute, Shijiazhuang, ChinaState Grid Hebei Electric Power Research Institute, Shijiazhuang, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University (Baoding), Baoding, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University (Baoding), Baoding, ChinaState Grid Hebei Electric Power Research Institute, Shijiazhuang, ChinaTo address the problems of slow convergence speed, easy to fall into local minima and low convergence accuracy presented by previous algorithms in DC distribution network fault location, this paper adopts the improved artificial bee colony slime mould algorithm (SMA) to improve and solve. On the basis of SMA, an adaptive adjustable feedback factor and an improved crossover operator are introduced to improve the convergence speed; artificial bee colony (ABC) algorithm is introduced to improve the search ability to jump out of local minima, and the artificial bee colony slime mould algorithm (ISMA) is formed. Firstly, based on the six-terminal DC distribution network topology, a mathematical model of bipolar short-circuit fault as well as single-pole grounded short-circuit fault is established based on a fault occurring between G-VSC and W-VSC as an example. Then the principle of the improved ISMA is introduced in detail, and a suitable fitness function is established as the measure of fault location in DC distribution network. Finally, experimental simulations are conducted to obtain fault points from the optimization search and compare them with the actual values to verify the accuracy of the algorithm. In addition, the efficiency and robustness of ISMA are further verified by comparing with other algorithms.https://ieeexplore.ieee.org/document/10155120/Distribution networkfault locationparameter identificationDC distribution systemartificial bee colony slime mould algorithm |
| spellingShingle | Tian-Xiang Ma Xin Duan Yan Xu Ruo-Lin Wang Xiao-Yu Li Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm IEEE Access Distribution network fault location parameter identification DC distribution system artificial bee colony slime mould algorithm |
| title | Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm |
| title_full | Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm |
| title_fullStr | Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm |
| title_full_unstemmed | Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm |
| title_short | Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm |
| title_sort | research on fault location in dc distribution network based on adaptive artificial bee colony slime mould algorithm |
| topic | Distribution network fault location parameter identification DC distribution system artificial bee colony slime mould algorithm |
| url | https://ieeexplore.ieee.org/document/10155120/ |
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