Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm
Distribution network reconfiguration involves altering the topology structure of distribution networks by adjusting the switch states, which plays an important role in the smart grid since it can effectively isolate faults, reduce the power loss, and improve the system stability. However, the fault...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Biomimetics |
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| Online Access: | https://www.mdpi.com/2313-7673/8/5/431 |
| _version_ | 1797581084504883200 |
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| author | Xin Li Mingyang Li Moduo Yu Qinqin Fan |
| author_facet | Xin Li Mingyang Li Moduo Yu Qinqin Fan |
| author_sort | Xin Li |
| collection | DOAJ |
| description | Distribution network reconfiguration involves altering the topology structure of distribution networks by adjusting the switch states, which plays an important role in the smart grid since it can effectively isolate faults, reduce the power loss, and improve the system stability. However, the fault reconfiguration of the distribution network is often regarded as a single-objective or multi-objective optimization problem, and its multimodality is often ignored in existing studies. Therefore, the obtained solutions may be unsuitable or infeasible when the environment changes. To improve the availability and robustness of the solutions, an improved discrete multimodal multi-objective particle swarm optimization (IDMMPSO) algorithm is proposed to solve the fault reconfiguration problem of the distribution network. To demonstrate the performance of the proposed IDMMPSO algorithm, the IEEE33-bus distribution system is used in the experiment. Moreover, the proposed algorithm is compared with other competitors. Experimental results show that the proposed algorithm can provide different equivalent solutions for decision-makers in solving the fault reconfiguration problem of the distribution network. |
| first_indexed | 2024-03-10T23:00:07Z |
| format | Article |
| id | doaj.art-41f12f5dd2464939841f724ed55ea33e |
| institution | Directory Open Access Journal |
| issn | 2313-7673 |
| language | English |
| last_indexed | 2024-03-10T23:00:07Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomimetics |
| spelling | doaj.art-41f12f5dd2464939841f724ed55ea33e2023-11-19T09:44:24ZengMDPI AGBiomimetics2313-76732023-09-018543110.3390/biomimetics8050431Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization AlgorithmXin Li0Mingyang Li1Moduo Yu2Qinqin Fan3Logistics Research Center, Shanghai Maritime University, Shanghai 201306, ChinaLogistics Research Center, Shanghai Maritime University, Shanghai 201306, ChinaKey Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, ChinaLogistics Research Center, Shanghai Maritime University, Shanghai 201306, ChinaDistribution network reconfiguration involves altering the topology structure of distribution networks by adjusting the switch states, which plays an important role in the smart grid since it can effectively isolate faults, reduce the power loss, and improve the system stability. However, the fault reconfiguration of the distribution network is often regarded as a single-objective or multi-objective optimization problem, and its multimodality is often ignored in existing studies. Therefore, the obtained solutions may be unsuitable or infeasible when the environment changes. To improve the availability and robustness of the solutions, an improved discrete multimodal multi-objective particle swarm optimization (IDMMPSO) algorithm is proposed to solve the fault reconfiguration problem of the distribution network. To demonstrate the performance of the proposed IDMMPSO algorithm, the IEEE33-bus distribution system is used in the experiment. Moreover, the proposed algorithm is compared with other competitors. Experimental results show that the proposed algorithm can provide different equivalent solutions for decision-makers in solving the fault reconfiguration problem of the distribution network.https://www.mdpi.com/2313-7673/8/5/431distribution networkfault reconfigurationsmart gridmultimodal multi-objective discrete optimizationevolutionary computation |
| spellingShingle | Xin Li Mingyang Li Moduo Yu Qinqin Fan Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm Biomimetics distribution network fault reconfiguration smart grid multimodal multi-objective discrete optimization evolutionary computation |
| title | Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm |
| title_full | Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm |
| title_fullStr | Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm |
| title_full_unstemmed | Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm |
| title_short | Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm |
| title_sort | fault reconfiguration in distribution networks based on improved discrete multimodal multi objective particle swarm optimization algorithm |
| topic | distribution network fault reconfiguration smart grid multimodal multi-objective discrete optimization evolutionary computation |
| url | https://www.mdpi.com/2313-7673/8/5/431 |
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