Jin Gao, Zhenguo Shao, Feixiong Chen, Yuchao Chen, Yongqi Lin, Hongjie Deng
{"title":"基于点对点多能交易的多微电网分布式鲁棒运行策略","authors":"Jin Gao, Zhenguo Shao, Feixiong Chen, Yuchao Chen, Yongqi Lin, Hongjie Deng","doi":"10.1049/esi2.12107","DOIUrl":null,"url":null,"abstract":"<p>In microgrid (MG) systems, traditional centralised energy trading models can lead to issues such as low energy efficiency due to unstable energy supply and lack of flexibility. Peer-to-peer (P2P) trading models have been widely used due to their advantages in promoting the sustainable development of renewable energy and reducing energy trading costs. However, P2P multi-energy trading requires mutual agreements between two microgrids (MGs), and the uncertainties of renewable energy and load affects energy supply security. To address these issues, this article proposed a distributed robust operation strategy based on P2P multi-energy trading for multi-microgrid (MMG) systems. Firstly, a two-stage robust optimisation (TRO) method was adopted to consider the uncertainties of P2P multi-energy trading between MGs, which reduced the conservatism of robust optimisation (RO). Secondly, a TRO model for P2P multi-energy trading among MGs was established based on the Nash bargaining theory, where each MG negotiates with others based on their energy contributions in the cooperation. Additionally, a distributed algorithm was used to protect the privacy of each MG. Finally, the simulation results based on three MGs showed that the proposed approach can achieve a fair distribution of cooperative interests and effectively promote cooperation among MGs.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12107","citationCount":"1","resultStr":"{\"title\":\"Distributed robust operation strategy of multi-microgrid based on peer-to-peer multi-energy trading\",\"authors\":\"Jin Gao, Zhenguo Shao, Feixiong Chen, Yuchao Chen, Yongqi Lin, Hongjie Deng\",\"doi\":\"10.1049/esi2.12107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In microgrid (MG) systems, traditional centralised energy trading models can lead to issues such as low energy efficiency due to unstable energy supply and lack of flexibility. Peer-to-peer (P2P) trading models have been widely used due to their advantages in promoting the sustainable development of renewable energy and reducing energy trading costs. However, P2P multi-energy trading requires mutual agreements between two microgrids (MGs), and the uncertainties of renewable energy and load affects energy supply security. To address these issues, this article proposed a distributed robust operation strategy based on P2P multi-energy trading for multi-microgrid (MMG) systems. Firstly, a two-stage robust optimisation (TRO) method was adopted to consider the uncertainties of P2P multi-energy trading between MGs, which reduced the conservatism of robust optimisation (RO). Secondly, a TRO model for P2P multi-energy trading among MGs was established based on the Nash bargaining theory, where each MG negotiates with others based on their energy contributions in the cooperation. Additionally, a distributed algorithm was used to protect the privacy of each MG. Finally, the simulation results based on three MGs showed that the proposed approach can achieve a fair distribution of cooperative interests and effectively promote cooperation among MGs.</p>\",\"PeriodicalId\":33288,\"journal\":{\"name\":\"IET Energy Systems Integration\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12107\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Energy Systems Integration\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/esi2.12107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Energy Systems Integration","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/esi2.12107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Distributed robust operation strategy of multi-microgrid based on peer-to-peer multi-energy trading
In microgrid (MG) systems, traditional centralised energy trading models can lead to issues such as low energy efficiency due to unstable energy supply and lack of flexibility. Peer-to-peer (P2P) trading models have been widely used due to their advantages in promoting the sustainable development of renewable energy and reducing energy trading costs. However, P2P multi-energy trading requires mutual agreements between two microgrids (MGs), and the uncertainties of renewable energy and load affects energy supply security. To address these issues, this article proposed a distributed robust operation strategy based on P2P multi-energy trading for multi-microgrid (MMG) systems. Firstly, a two-stage robust optimisation (TRO) method was adopted to consider the uncertainties of P2P multi-energy trading between MGs, which reduced the conservatism of robust optimisation (RO). Secondly, a TRO model for P2P multi-energy trading among MGs was established based on the Nash bargaining theory, where each MG negotiates with others based on their energy contributions in the cooperation. Additionally, a distributed algorithm was used to protect the privacy of each MG. Finally, the simulation results based on three MGs showed that the proposed approach can achieve a fair distribution of cooperative interests and effectively promote cooperation among MGs.