Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes
The increasing integration of photovoltaic generators (PVGs) and the uneven economic development in different regions may cause the unbalanced spatial-temporal distribution of load demands in an urban distribution network (UDN). This may lead to undesired consequences, including PVG curtailment, loa...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | Journal of Modern Power Systems and Clean Energy |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9497859/ |
| _version_ | 1811265686624796672 |
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| author | Hongjun Gao Wang Ma Yingmeng Xiang Zao Tang Xiandong Xu Hongjin Pan Fan Zhang Junyong Liu |
| author_facet | Hongjun Gao Wang Ma Yingmeng Xiang Zao Tang Xiandong Xu Hongjin Pan Fan Zhang Junyong Liu |
| author_sort | Hongjun Gao |
| collection | DOAJ |
| description | The increasing integration of photovoltaic generators (PVGs) and the uneven economic development in different regions may cause the unbalanced spatial-temporal distribution of load demands in an urban distribution network (UDN). This may lead to undesired consequences, including PVG curtailment, load shedding, and equipment inefficiency, etc. Global dynamic reconfiguration provides a promising method to solve those challenges. However, the power flow transfer capabilities for different kinds of switches are diverse, and the willingness of distribution system operators (DSOs) to select them is also different. In this paper, we formulate a multi-objective dynamic reconfiguration optimization model suitable for multi-level switching modes to minimize the operation cost, load imbalance, and the PVG curtailment. The multi-level switching includes feeder-level switching, transformer-level switching, and substation-level switching. A novel load balancing index is devised to quantify the global load balancing degree at different levels. Then, a stochastic programming model based on selected scenarios is established to address the uncertainties of PVGs and loads. Afterward, the fuzzy c-means (FCMs) clustering is applied to divide the time periods of reconfiguration. Further-more, the modified binary particle swarm optimization (BPSO) and Cplex solver are combined to solve the proposed mixed-in-teger second-order cone programming (MISOCP) model. Numerical results based on the 148-node and 297-node systems are obtained to validate the effectiveness of the proposed method. |
| first_indexed | 2024-04-12T20:28:28Z |
| format | Article |
| id | doaj.art-99428f356285445b825079baa91d51c8 |
| institution | Directory Open Access Journal |
| issn | 2196-5420 |
| language | English |
| last_indexed | 2024-04-12T20:28:28Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | Journal of Modern Power Systems and Clean Energy |
| spelling | doaj.art-99428f356285445b825079baa91d51c82022-12-22T03:17:48ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202022-01-011051241125510.35833/MPCE.2020.0008709497859Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching ModesHongjun Gao0Wang Ma1Yingmeng Xiang2Zao Tang3Xiandong Xu4Hongjin Pan5Fan Zhang6Junyong Liu7College of Electrical Engineering, Sichuan University,Chengdu,China,610065College of Electrical Engineering, Sichuan University,Chengdu,China,610065Iowa State University,Ames,Iowa,USA,50010College of Electrical Engineering, Sichuan University,Chengdu,China,610065Key Laboratory of Smart Grid of Ministry of Education, Tianjin University,Tianjin,China,300072College of Electrical Engineering, Sichuan University,Chengdu,China,610065College of Electrical Engineering, Sichuan University,Chengdu,China,610065College of Electrical Engineering, Sichuan University,Chengdu,China,610065The increasing integration of photovoltaic generators (PVGs) and the uneven economic development in different regions may cause the unbalanced spatial-temporal distribution of load demands in an urban distribution network (UDN). This may lead to undesired consequences, including PVG curtailment, load shedding, and equipment inefficiency, etc. Global dynamic reconfiguration provides a promising method to solve those challenges. However, the power flow transfer capabilities for different kinds of switches are diverse, and the willingness of distribution system operators (DSOs) to select them is also different. In this paper, we formulate a multi-objective dynamic reconfiguration optimization model suitable for multi-level switching modes to minimize the operation cost, load imbalance, and the PVG curtailment. The multi-level switching includes feeder-level switching, transformer-level switching, and substation-level switching. A novel load balancing index is devised to quantify the global load balancing degree at different levels. Then, a stochastic programming model based on selected scenarios is established to address the uncertainties of PVGs and loads. Afterward, the fuzzy c-means (FCMs) clustering is applied to divide the time periods of reconfiguration. Further-more, the modified binary particle swarm optimization (BPSO) and Cplex solver are combined to solve the proposed mixed-in-teger second-order cone programming (MISOCP) model. Numerical results based on the 148-node and 297-node systems are obtained to validate the effectiveness of the proposed method.https://ieeexplore.ieee.org/document/9497859/Binary particle swarm optimization (BPSO)dynamic reconfigurationmulti-level switchingmixed-integer second-order cone programming (MISOCP)urban distribution network (UDN) |
| spellingShingle | Hongjun Gao Wang Ma Yingmeng Xiang Zao Tang Xiandong Xu Hongjin Pan Fan Zhang Junyong Liu Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes Journal of Modern Power Systems and Clean Energy Binary particle swarm optimization (BPSO) dynamic reconfiguration multi-level switching mixed-integer second-order cone programming (MISOCP) urban distribution network (UDN) |
| title | Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes |
| title_full | Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes |
| title_fullStr | Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes |
| title_full_unstemmed | Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes |
| title_short | Multi-objective Dynamic Reconfiguration for Urban Distribution Network Considering Multi-level Switching Modes |
| title_sort | multi objective dynamic reconfiguration for urban distribution network considering multi level switching modes |
| topic | Binary particle swarm optimization (BPSO) dynamic reconfiguration multi-level switching mixed-integer second-order cone programming (MISOCP) urban distribution network (UDN) |
| url | https://ieeexplore.ieee.org/document/9497859/ |
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