Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game
With more and more microgrids operate in coordination, the process of power interaction between microgrids and between microgrids and distribution networks has become increasingly complicated, which also affects the investment interests of microgrid and distribution network operators. To explore the...
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2022-06-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202107162 |
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| _version_ | 1850053958930792448 |
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| author | Ruiyuan PAN Zhong TANG Chenhao SHI Minjie WEI An LI Weiyang DAI |
| author_facet | Ruiyuan PAN Zhong TANG Chenhao SHI Minjie WEI An LI Weiyang DAI |
| author_sort | Ruiyuan PAN |
| collection | DOAJ |
| description | With more and more microgrids operate in coordination, the process of power interaction between microgrids and between microgrids and distribution networks has become increasingly complicated, which also affects the investment interests of microgrid and distribution network operators. To explore the best planning strategy for joint investment between the two, this paper proposes a method for optimal configuration of the multi-microgrid system with multi-agent investment based on the Stackelberg game. Firstly, on the basis of the multi-microgrid system model, a function model is constructed, which considering the operating costs and economic benefits of microgrid operators, investment costs of distribution network operators in microgrids, as well as interests of delays in grid upgrades and electricity sales and purchases. Then, a Stackelberg game model is built to minimize the payoff function of the multi-microgrid system and maximize the revenue of distribution networks separately. In addition, an algorithm combining the adaptive genetic algorithm and particle swarm optimization is proposed to solve the optimal configuration of distributed power in the multi-microgrid system. Finally, a comparative experiment with four sets of plans proves that the proposed planning method can better balance the revenue between multi-microgrid operators and distribution network operators. |
| format | Article |
| id | doaj-art-e377c2393bd8485fa61912ed761619d5 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2022-06-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-e377c2393bd8485fa61912ed761619d52025-08-20T02:52:24ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492022-06-01556657310.11930/j.issn.1004-9649.202107162zgdl-55-10-panruiyuanOptimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg GameRuiyuan PAN0Zhong TANG1Chenhao SHI2Minjie WEI3An LI4Weiyang DAI5College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaJiangsu Electric Power Company Maintenance Branch, Nanjing 211102, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaCollege of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, ChinaWith more and more microgrids operate in coordination, the process of power interaction between microgrids and between microgrids and distribution networks has become increasingly complicated, which also affects the investment interests of microgrid and distribution network operators. To explore the best planning strategy for joint investment between the two, this paper proposes a method for optimal configuration of the multi-microgrid system with multi-agent investment based on the Stackelberg game. Firstly, on the basis of the multi-microgrid system model, a function model is constructed, which considering the operating costs and economic benefits of microgrid operators, investment costs of distribution network operators in microgrids, as well as interests of delays in grid upgrades and electricity sales and purchases. Then, a Stackelberg game model is built to minimize the payoff function of the multi-microgrid system and maximize the revenue of distribution networks separately. In addition, an algorithm combining the adaptive genetic algorithm and particle swarm optimization is proposed to solve the optimal configuration of distributed power in the multi-microgrid system. Finally, a comparative experiment with four sets of plans proves that the proposed planning method can better balance the revenue between multi-microgrid operators and distribution network operators.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202107162multi-microgrid systemjoint investmentoptimal configurationstackelberg gameadaptive genetic algorithm |
| spellingShingle | Ruiyuan PAN Zhong TANG Chenhao SHI Minjie WEI An LI Weiyang DAI Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game Zhongguo dianli multi-microgrid system joint investment optimal configuration stackelberg game adaptive genetic algorithm |
| title | Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game |
| title_full | Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game |
| title_fullStr | Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game |
| title_full_unstemmed | Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game |
| title_short | Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game |
| title_sort | optimal configuration of multi microgrid system with multi agent joint investment based on stackelberg game |
| topic | multi-microgrid system joint investment optimal configuration stackelberg game adaptive genetic algorithm |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202107162 |
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