Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm
Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications. However, the low accuracy and poor convergence of these algorithms have been challenging for system operator...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2022-04-01
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| Series: | Global Energy Interconnection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096511722000330 |
| _version_ | 1811336595942408192 |
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| author | Xiaoyan Ma Yunfei Mu Yu Zhang Chenxi Zang Shurong Li Xinyang Jiang Meng Cui |
| author_facet | Xiaoyan Ma Yunfei Mu Yu Zhang Chenxi Zang Shurong Li Xinyang Jiang Meng Cui |
| author_sort | Xiaoyan Ma |
| collection | DOAJ |
| description | Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications. However, the low accuracy and poor convergence of these algorithms have been challenging for system operators. The bird swarm algorithm (BSA), a new bio- heuristic cluster intelligent algorithm, can potentially address these challenges; however, its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions. To analyze the impact of a multi-objective economic–environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA, a self-adaptive levy flight strategy-based BSA (LF–BSA) was proposed. It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy, stability, and speed, thereby improving its optimization performance. Six typical test functions were used to compare the LF–BSA with three commonly accepted algorithms to verify its excellence. Finally, a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated. The results proved the feasibility of the proposed LF–BSA, effectiveness of the multi- objective optimization, and necessity of using renewable energy and energy storage in microgrid dispatching optimization. |
| first_indexed | 2024-04-13T17:41:44Z |
| format | Article |
| id | doaj.art-9ecd6368385945f596cbb6a6047a2f85 |
| institution | Directory Open Access Journal |
| issn | 2096-5117 |
| language | English |
| last_indexed | 2024-04-13T17:41:44Z |
| publishDate | 2022-04-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Global Energy Interconnection |
| spelling | doaj.art-9ecd6368385945f596cbb6a6047a2f852022-12-22T02:37:10ZengKeAi Communications Co., Ltd.Global Energy Interconnection2096-51172022-04-0152154167Multi-objective microgrid optimal dispatching based on improved bird swarm algorithmXiaoyan Ma0Yunfei Mu1Yu Zhang2Chenxi Zang3Shurong Li4Xinyang Jiang5Meng Cui6Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, PR ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, PR ChinaGlobal Energy Interconnection Development and Cooperation Organization, Beijing 100031, PR ChinaXiamen University, Xiamen 361102, PR ChinaState Grid Xiongan New Area Electric Power Supply Company, Baoding 071700, PR ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, PR ChinaState Grid Baoding Electric Power Supply Company, Baoding 071000, PR ChinaMulti-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications. However, the low accuracy and poor convergence of these algorithms have been challenging for system operators. The bird swarm algorithm (BSA), a new bio- heuristic cluster intelligent algorithm, can potentially address these challenges; however, its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions. To analyze the impact of a multi-objective economic–environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA, a self-adaptive levy flight strategy-based BSA (LF–BSA) was proposed. It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy, stability, and speed, thereby improving its optimization performance. Six typical test functions were used to compare the LF–BSA with three commonly accepted algorithms to verify its excellence. Finally, a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated. The results proved the feasibility of the proposed LF–BSA, effectiveness of the multi- objective optimization, and necessity of using renewable energy and energy storage in microgrid dispatching optimization.http://www.sciencedirect.com/science/article/pii/S2096511722000330MicrogridOperation optimizationBird swarm algorithmLevy flight strategySelf-adaptive |
| spellingShingle | Xiaoyan Ma Yunfei Mu Yu Zhang Chenxi Zang Shurong Li Xinyang Jiang Meng Cui Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm Global Energy Interconnection Microgrid Operation optimization Bird swarm algorithm Levy flight strategy Self-adaptive |
| title | Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm |
| title_full | Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm |
| title_fullStr | Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm |
| title_full_unstemmed | Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm |
| title_short | Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm |
| title_sort | multi objective microgrid optimal dispatching based on improved bird swarm algorithm |
| topic | Microgrid Operation optimization Bird swarm algorithm Levy flight strategy Self-adaptive |
| url | http://www.sciencedirect.com/science/article/pii/S2096511722000330 |
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