Coalitional game theory based local power exchange algorithm for networked microgrids
© 2019 Elsevier Ltd The future distribution network may encompass a large number of microgrids, in which case local networked microgrids can be formed and all the microgrids in the network be connected to the main grid through a distribution sub-station. To improve the efficiency of the entire netwo...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/135866 |
| _version_ | 1811073669880872960 |
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| author | Mei, Jie Chen, Chen Wang, Jianhui Kirtley, James L |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Mei, Jie Chen, Chen Wang, Jianhui Kirtley, James L |
| author_sort | Mei, Jie |
| collection | MIT |
| description | © 2019 Elsevier Ltd The future distribution network may encompass a large number of microgrids, in which case local networked microgrids can be formed and all the microgrids in the network be connected to the main grid through a distribution sub-station. To improve the efficiency of the entire network rather than focusing on improving the efficiency and reliability of each microgrid, this paper proposes a coalitional-game-theory-based local power exchange algorithm to identify incentives for coalitional operation and help microgrids in the network trade power locally with neighboring microgrids, so as to meet their own power requirements while achieving higher expected individual utility. Compared with the traditional operation situation, simulation results show that the proposed coalitional- game-theory-based local power exchange algorithm can help increase individual microgrid utility in the network. When there are 30 microgrids in the network, for example, each microgrid is expected to have a 16% increment of individual utility on average. |
| first_indexed | 2024-09-23T09:36:43Z |
| format | Article |
| id | mit-1721.1/135866 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:36:43Z |
| publishDate | 2021 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1358662023-03-01T21:17:18Z Coalitional game theory based local power exchange algorithm for networked microgrids Mei, Jie Chen, Chen Wang, Jianhui Kirtley, James L Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science © 2019 Elsevier Ltd The future distribution network may encompass a large number of microgrids, in which case local networked microgrids can be formed and all the microgrids in the network be connected to the main grid through a distribution sub-station. To improve the efficiency of the entire network rather than focusing on improving the efficiency and reliability of each microgrid, this paper proposes a coalitional-game-theory-based local power exchange algorithm to identify incentives for coalitional operation and help microgrids in the network trade power locally with neighboring microgrids, so as to meet their own power requirements while achieving higher expected individual utility. Compared with the traditional operation situation, simulation results show that the proposed coalitional- game-theory-based local power exchange algorithm can help increase individual microgrid utility in the network. When there are 30 microgrids in the network, for example, each microgrid is expected to have a 16% increment of individual utility on average. 2021-10-27T20:29:43Z 2021-10-27T20:29:43Z 2019 2019-06-10T15:38:00Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/135866 en 10.1016/j.apenergy.2019.01.208 Applied Energy Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Other repository |
| spellingShingle | Mei, Jie Chen, Chen Wang, Jianhui Kirtley, James L Coalitional game theory based local power exchange algorithm for networked microgrids |
| title | Coalitional game theory based local power exchange algorithm for networked microgrids |
| title_full | Coalitional game theory based local power exchange algorithm for networked microgrids |
| title_fullStr | Coalitional game theory based local power exchange algorithm for networked microgrids |
| title_full_unstemmed | Coalitional game theory based local power exchange algorithm for networked microgrids |
| title_short | Coalitional game theory based local power exchange algorithm for networked microgrids |
| title_sort | coalitional game theory based local power exchange algorithm for networked microgrids |
| url | https://hdl.handle.net/1721.1/135866 |
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