Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm
This paper proposes a novel optimization method for fault current limiter (FCL) reactance configuration based on joint simulation and penalty function constraint optimization. By integrating MATLAB and ATP for joint simulation, the method accurately derives the constraint conditions of the objective...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/5/1077 |
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| _version_ | 1850031425241219072 |
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| author | Jun Zhao Chao Xing Zhigang Zhang Boyuan Liang Lu Sun Bin Wei Weiqi Qin Shuguo Gao |
| author_facet | Jun Zhao Chao Xing Zhigang Zhang Boyuan Liang Lu Sun Bin Wei Weiqi Qin Shuguo Gao |
| author_sort | Jun Zhao |
| collection | DOAJ |
| description | This paper proposes a novel optimization method for fault current limiter (FCL) reactance configuration based on joint simulation and penalty function constraint optimization. By integrating MATLAB and ATP for joint simulation, the method accurately derives the constraint conditions of the objective optimization function, providing critical data support for the optimization process. To address the challenges of high computational complexity and solution difficulties in constrained optimization, the Penalty Function Method (PFM) is employed to transform the original constrained optimization problem into a standard unconstrained optimization problem, significantly reducing computational complexity and ensuring the feasibility of the solution. On this basis, the Gravitational Search Algorithm (GSA) is applied to compute the optimal reactance value. Through comparative analysis of engineering case studies, the superiority of the GSA over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in optimization performance is validated, further confirming the accuracy and efficiency of the proposed method. The results indicate that this method not only achieves precise calculation results but also significantly improves computational efficiency. Moreover, the integration of PFM and GSA demonstrates excellent robustness, providing reliable technical support for the optimized deployment of fast-switching fault current limiters in large-scale power grids. |
| format | Article |
| id | doaj-art-648f9d54816649f59dd3952a7548f1b4 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-648f9d54816649f59dd3952a7548f1b42025-08-20T02:58:58ZengMDPI AGEnergies1996-10732025-02-01185107710.3390/en18051077Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained AlgorithmJun Zhao0Chao Xing1Zhigang Zhang2Boyuan Liang3Lu Sun4Bin Wei5Weiqi Qin6Shuguo Gao7Electric Power Research Institute, State Grid Hebei Electric Power Company, Shijiazhuang 050000, ChinaElectric Power Research Institute, State Grid Hebei Electric Power Company, Shijiazhuang 050000, ChinaElectric Power Research Institute, State Grid Hebei Electric Power Company, Shijiazhuang 050000, ChinaElectric Power Research Institute, State Grid Hebei Electric Power Company, Shijiazhuang 050000, ChinaElectric Power Research Institute, State Grid Hebei Electric Power Company, Shijiazhuang 050000, 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, ChinaElectric Power Research Institute, State Grid Hebei Electric Power Company, Shijiazhuang 050000, ChinaThis paper proposes a novel optimization method for fault current limiter (FCL) reactance configuration based on joint simulation and penalty function constraint optimization. By integrating MATLAB and ATP for joint simulation, the method accurately derives the constraint conditions of the objective optimization function, providing critical data support for the optimization process. To address the challenges of high computational complexity and solution difficulties in constrained optimization, the Penalty Function Method (PFM) is employed to transform the original constrained optimization problem into a standard unconstrained optimization problem, significantly reducing computational complexity and ensuring the feasibility of the solution. On this basis, the Gravitational Search Algorithm (GSA) is applied to compute the optimal reactance value. Through comparative analysis of engineering case studies, the superiority of the GSA over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in optimization performance is validated, further confirming the accuracy and efficiency of the proposed method. The results indicate that this method not only achieves precise calculation results but also significantly improves computational efficiency. Moreover, the integration of PFM and GSA demonstrates excellent robustness, providing reliable technical support for the optimized deployment of fast-switching fault current limiters in large-scale power grids.https://www.mdpi.com/1996-1073/18/5/1077fault current limiteroptimal configuration of reactance valuejoint simulationpenalty function methodgravitational search algorithm |
| spellingShingle | Jun Zhao Chao Xing Zhigang Zhang Boyuan Liang Lu Sun Bin Wei Weiqi Qin Shuguo Gao Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm Energies fault current limiter optimal configuration of reactance value joint simulation penalty function method gravitational search algorithm |
| title | Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm |
| title_full | Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm |
| title_fullStr | Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm |
| title_full_unstemmed | Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm |
| title_short | Optimization of Fault Current Limiter Reactance Based on Joint Simulation and Penalty Function-Constrained Algorithm |
| title_sort | optimization of fault current limiter reactance based on joint simulation and penalty function constrained algorithm |
| topic | fault current limiter optimal configuration of reactance value joint simulation penalty function method gravitational search algorithm |
| url | https://www.mdpi.com/1996-1073/18/5/1077 |
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