Fault Location and Restoration of Microgrids via Particle Swarm Optimization
This aim of this work was to develop an integrated fault location and restoration approach for microgrids (MGs). The work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimizat...
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MDPI AG
2021-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/15/7036 |
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| author | Wei-Chen Lin Wei-Tzer Huang Kai-Chao Yao Hong-Ting Chen Chun-Chiang Ma |
| author_facet | Wei-Chen Lin Wei-Tzer Huang Kai-Chao Yao Hong-Ting Chen Chun-Chiang Ma |
| author_sort | Wei-Chen Lin |
| collection | DOAJ |
| description | This aim of this work was to develop an integrated fault location and restoration approach for microgrids (MGs). The work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (<i>BCBV</i>) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of a fault, the voltage variation at each bus is calculated by using the Z<sub>bus</sub> modification algorithm to modify Z<sub>bus</sub>. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations was utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve fault location and restoration problems in MGs. |
| first_indexed | 2024-03-10T09:19:04Z |
| format | Article |
| id | doaj.art-a232c15bc8a1490c80e503d08d338f30 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:19:04Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
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| spelling | doaj.art-a232c15bc8a1490c80e503d08d338f302023-11-22T05:23:27ZengMDPI AGApplied Sciences2076-34172021-07-011115703610.3390/app11157036Fault Location and Restoration of Microgrids via Particle Swarm OptimizationWei-Chen Lin0Wei-Tzer Huang1Kai-Chao Yao2Hong-Ting Chen3Chun-Chiang Ma4Department of Industrial Education and Technology, National Changhua University of Education, No. 2, Shida Rd., Changhua 500, TaiwanDepartment of Industrial Education and Technology, National Changhua University of Education, No. 2, Shida Rd., Changhua 500, TaiwanDepartment of Industrial Education and Technology, National Changhua University of Education, No. 2, Shida Rd., Changhua 500, TaiwanDepartment of Industrial Education and Technology, National Changhua University of Education, No. 2, Shida Rd., Changhua 500, TaiwanDepartment of Industrial Education and Technology, National Changhua University of Education, No. 2, Shida Rd., Changhua 500, TaiwanThis aim of this work was to develop an integrated fault location and restoration approach for microgrids (MGs). The work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (<i>BCBV</i>) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of a fault, the voltage variation at each bus is calculated by using the Z<sub>bus</sub> modification algorithm to modify Z<sub>bus</sub>. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations was utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve fault location and restoration problems in MGs.https://www.mdpi.com/2076-3417/11/15/7036fault locationservice restorationparticle swam optimizationmicrogridpower flowshort-circuit fault |
| spellingShingle | Wei-Chen Lin Wei-Tzer Huang Kai-Chao Yao Hong-Ting Chen Chun-Chiang Ma Fault Location and Restoration of Microgrids via Particle Swarm Optimization Applied Sciences fault location service restoration particle swam optimization microgrid power flow short-circuit fault |
| title | Fault Location and Restoration of Microgrids via Particle Swarm Optimization |
| title_full | Fault Location and Restoration of Microgrids via Particle Swarm Optimization |
| title_fullStr | Fault Location and Restoration of Microgrids via Particle Swarm Optimization |
| title_full_unstemmed | Fault Location and Restoration of Microgrids via Particle Swarm Optimization |
| title_short | Fault Location and Restoration of Microgrids via Particle Swarm Optimization |
| title_sort | fault location and restoration of microgrids via particle swarm optimization |
| topic | fault location service restoration particle swam optimization microgrid power flow short-circuit fault |
| url | https://www.mdpi.com/2076-3417/11/15/7036 |
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