{"title":"基于可再生能源的多微网的混合日前和实时能源交易:随机合作框架","authors":"","doi":"10.1016/j.segan.2024.101516","DOIUrl":null,"url":null,"abstract":"<div><p>This paper proposes a multi-objective optimization framework to model the energy trading between microgrids and microgrid communities in the distribution systems. To this end, a hybrid cooperative and non-cooperative algorithm is presented where the microgrid community leads the optimization problem. The microgrid community performs a multi-objective optimization to determine the transactive retail prices to simultaneously improve its operation cost and system flexibility. However, the microgrids, as the followers of the problem, receive the retail prices from the microgrid community to decide on the amount of hourly trading with the microgrid community. The main objective of microgrids is to reduce their cost as much as possible. For this reason, they cooperate to form several coalitions to enhance their bargaining power in the market. Real-time scheduling will be done to increase the reliability of the proposed model and reduce the imbalance costs of the microgrid community and microgrids. The proposed model is tested on a general case study, and the simulation results show that the cooperation among microgrids reduces their operation costs from $ 3453.66 to $ 2984.33. Also, the multi-objective scheduling increases the flexibility by 28.5 %.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hybrid day-ahead and real-time energy trading of renewable-based multi-microgrids: A stochastic cooperative framework\",\"authors\":\"\",\"doi\":\"10.1016/j.segan.2024.101516\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper proposes a multi-objective optimization framework to model the energy trading between microgrids and microgrid communities in the distribution systems. To this end, a hybrid cooperative and non-cooperative algorithm is presented where the microgrid community leads the optimization problem. The microgrid community performs a multi-objective optimization to determine the transactive retail prices to simultaneously improve its operation cost and system flexibility. However, the microgrids, as the followers of the problem, receive the retail prices from the microgrid community to decide on the amount of hourly trading with the microgrid community. The main objective of microgrids is to reduce their cost as much as possible. For this reason, they cooperate to form several coalitions to enhance their bargaining power in the market. Real-time scheduling will be done to increase the reliability of the proposed model and reduce the imbalance costs of the microgrid community and microgrids. The proposed model is tested on a general case study, and the simulation results show that the cooperation among microgrids reduces their operation costs from $ 3453.66 to $ 2984.33. Also, the multi-objective scheduling increases the flexibility by 28.5 %.</p></div>\",\"PeriodicalId\":56142,\"journal\":{\"name\":\"Sustainable Energy Grids & Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Energy Grids & Networks\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352467724002455\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467724002455","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Hybrid day-ahead and real-time energy trading of renewable-based multi-microgrids: A stochastic cooperative framework
This paper proposes a multi-objective optimization framework to model the energy trading between microgrids and microgrid communities in the distribution systems. To this end, a hybrid cooperative and non-cooperative algorithm is presented where the microgrid community leads the optimization problem. The microgrid community performs a multi-objective optimization to determine the transactive retail prices to simultaneously improve its operation cost and system flexibility. However, the microgrids, as the followers of the problem, receive the retail prices from the microgrid community to decide on the amount of hourly trading with the microgrid community. The main objective of microgrids is to reduce their cost as much as possible. For this reason, they cooperate to form several coalitions to enhance their bargaining power in the market. Real-time scheduling will be done to increase the reliability of the proposed model and reduce the imbalance costs of the microgrid community and microgrids. The proposed model is tested on a general case study, and the simulation results show that the cooperation among microgrids reduces their operation costs from $ 3453.66 to $ 2984.33. Also, the multi-objective scheduling increases the flexibility by 28.5 %.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.