{"title":"Optimal Planning of Multi-Microgrid System With Shared Energy Storage Based on Capacity Leasing and Energy Sharing","authors":"Jianpei Han;Yuchen Fang;Yaowang Li;Ershun Du;Ning Zhang","doi":"10.1109/TSG.2024.3452064","DOIUrl":null,"url":null,"abstract":"Microgrids (MGs) are important forms of supporting the efficient utilization of distributed renewable energy resources (RES). To achieve high proportion penetration of distributed RES and improve the system efficiency, this paper focuses on the multi-microgrid (MMG) system with shared energy storage (SES) and an optimal planning method of MMG system with capacity leasing and energy sharing for PV carrying capability enhancement is proposed. Firstly, a collaborative optimization framework between the multi-microgrid operator (MMGO) and the shared energy storage operator (SESO) is proposed. Secondly, the PV carrying capability index is proposed from two dimensions: the hosting capability and the accommodation capability, and the capacity planning model of the MMG system considering PV carrying capability index is established. Then, the capacity leasing and energy sharing model among MGs as well as between MMG systems and SES system is established. Based on this, a collaborative capacity planning model of MMGO and SESO with the Nash Bargaining game is developed and a distributed solution algorithm is designed. Finally, through a comprehensive case study we can draw that, the proposed planning method with capacity leasing and energy sharing can enhance PV carrying capability of the MMG system while improving economics of MMGO and SESO.","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"16 1","pages":"16-31"},"PeriodicalIF":9.8000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Smart Grid","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10660302/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Microgrids (MGs) are important forms of supporting the efficient utilization of distributed renewable energy resources (RES). To achieve high proportion penetration of distributed RES and improve the system efficiency, this paper focuses on the multi-microgrid (MMG) system with shared energy storage (SES) and an optimal planning method of MMG system with capacity leasing and energy sharing for PV carrying capability enhancement is proposed. Firstly, a collaborative optimization framework between the multi-microgrid operator (MMGO) and the shared energy storage operator (SESO) is proposed. Secondly, the PV carrying capability index is proposed from two dimensions: the hosting capability and the accommodation capability, and the capacity planning model of the MMG system considering PV carrying capability index is established. Then, the capacity leasing and energy sharing model among MGs as well as between MMG systems and SES system is established. Based on this, a collaborative capacity planning model of MMGO and SESO with the Nash Bargaining game is developed and a distributed solution algorithm is designed. Finally, through a comprehensive case study we can draw that, the proposed planning method with capacity leasing and energy sharing can enhance PV carrying capability of the MMG system while improving economics of MMGO and SESO.
期刊介绍:
The IEEE Transactions on Smart Grid is a multidisciplinary journal that focuses on research and development in the field of smart grid technology. It covers various aspects of the smart grid, including energy networks, prosumers (consumers who also produce energy), electric transportation, distributed energy resources, and communications. The journal also addresses the integration of microgrids and active distribution networks with transmission systems. It publishes original research on smart grid theories and principles, including technologies and systems for demand response, Advance Metering Infrastructure, cyber-physical systems, multi-energy systems, transactive energy, data analytics, and electric vehicle integration. Additionally, the journal considers surveys of existing work on the smart grid that propose new perspectives on the history and future of intelligent and active grids.