{"title":"网格约束下局部能源社区分布式能源聚合优化运行","authors":"Shubham Gupta;Vinod Kumar Yadav;Madhusudan Singh","doi":"10.1109/TII.2025.3558313","DOIUrl":null,"url":null,"abstract":"This article presents a framework to efficiently manage a sizable fleet of diverse distributed energy resources (DERs) operating within distribution systems to optimize the operations of local energy communities (LECs) and improve grid services. First, we develop aggregation modeling for DERs to evaluate cumulative flexibility that considers their preferences, spatial placement, and temporal behavior. Subsequently, we employ a hierarchical control framework (HCF) to put these aggregated flexibility of DERs for their effective dispatching. The HCF involves three key entities: an electric utility (EU) operator, community aggregators (CAs), and individual DERs. CAs harness the flexibility obtained from the aggregated DERs within their respective LECs to minimize operational costs while also considering the distribution network constraints. On the other hand, the EU operator coordinates dispatch setpoints received from CAs along with the disaggregated DERs to regulate distribution system node voltages and reduce power losses to enhance grid services. Numerical simulations conducted on a modified IEEE-123 bus radial distribution network demonstrate the efficacy of our approach in effectively managing DERs for cost-efficient operations and improving grid services.","PeriodicalId":13301,"journal":{"name":"IEEE Transactions on Industrial Informatics","volume":"21 7","pages":"5723-5733"},"PeriodicalIF":9.9000,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aggregation of Distributed Energy Resources for Optimal Operation in Local Energy Communities With Grid Constraints\",\"authors\":\"Shubham Gupta;Vinod Kumar Yadav;Madhusudan Singh\",\"doi\":\"10.1109/TII.2025.3558313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a framework to efficiently manage a sizable fleet of diverse distributed energy resources (DERs) operating within distribution systems to optimize the operations of local energy communities (LECs) and improve grid services. First, we develop aggregation modeling for DERs to evaluate cumulative flexibility that considers their preferences, spatial placement, and temporal behavior. Subsequently, we employ a hierarchical control framework (HCF) to put these aggregated flexibility of DERs for their effective dispatching. The HCF involves three key entities: an electric utility (EU) operator, community aggregators (CAs), and individual DERs. CAs harness the flexibility obtained from the aggregated DERs within their respective LECs to minimize operational costs while also considering the distribution network constraints. On the other hand, the EU operator coordinates dispatch setpoints received from CAs along with the disaggregated DERs to regulate distribution system node voltages and reduce power losses to enhance grid services. Numerical simulations conducted on a modified IEEE-123 bus radial distribution network demonstrate the efficacy of our approach in effectively managing DERs for cost-efficient operations and improving grid services.\",\"PeriodicalId\":13301,\"journal\":{\"name\":\"IEEE Transactions on Industrial Informatics\",\"volume\":\"21 7\",\"pages\":\"5723-5733\"},\"PeriodicalIF\":9.9000,\"publicationDate\":\"2025-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Industrial Informatics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10970075/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Informatics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10970075/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Aggregation of Distributed Energy Resources for Optimal Operation in Local Energy Communities With Grid Constraints
This article presents a framework to efficiently manage a sizable fleet of diverse distributed energy resources (DERs) operating within distribution systems to optimize the operations of local energy communities (LECs) and improve grid services. First, we develop aggregation modeling for DERs to evaluate cumulative flexibility that considers their preferences, spatial placement, and temporal behavior. Subsequently, we employ a hierarchical control framework (HCF) to put these aggregated flexibility of DERs for their effective dispatching. The HCF involves three key entities: an electric utility (EU) operator, community aggregators (CAs), and individual DERs. CAs harness the flexibility obtained from the aggregated DERs within their respective LECs to minimize operational costs while also considering the distribution network constraints. On the other hand, the EU operator coordinates dispatch setpoints received from CAs along with the disaggregated DERs to regulate distribution system node voltages and reduce power losses to enhance grid services. Numerical simulations conducted on a modified IEEE-123 bus radial distribution network demonstrate the efficacy of our approach in effectively managing DERs for cost-efficient operations and improving grid services.
期刊介绍:
The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.