{"title":"Residential Virtual Power Plant Control: A Novel Hierarchical Multi-Objective Optimization Approach","authors":"Mohamed Bahloul;Liam Breathnach;Shafi Khadem","doi":"10.1109/TSG.2024.3479972","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel approach to address hierarchical multi-objective optimization for residential virtual power plant (VPP) in a coordinated and efficient manner. The solution is flexible and caters to the diverse needs of stakeholders. It serves as a foundation for developing an optimal control solution for a residential distributed energy storage systems (ESS)- based VPP solution. A day-ahead scheduling using a novel hierarchical multi-objective optimization approach is developed for the ESS energy capacity and power budget allocation. The objectives are to simultaneously provide multiple local services, optimize the distributed ESS deployment, and provide the aggregator a clear visibility of the ESS remaining resources. This visibility of the features and use of remaining energy capacity and power budget will help the aggregator to create a virtual ESS that can be applied to provide additional services in the local and wholesale energy market. A focus on power-oriented applications provision is considered further; however, the results could be extended easily to other services. Real case studies utilizing data from the StoreNet project and complying with Irish energy market regulations further illuminate the discussion. The results obtained from employing different design methods are thoroughly examined, shedding light on their respective merits and limitations.","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"16 2","pages":"1301-1313"},"PeriodicalIF":8.6000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10715723","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Smart Grid","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10715723/","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
This paper proposes a novel approach to address hierarchical multi-objective optimization for residential virtual power plant (VPP) in a coordinated and efficient manner. The solution is flexible and caters to the diverse needs of stakeholders. It serves as a foundation for developing an optimal control solution for a residential distributed energy storage systems (ESS)- based VPP solution. A day-ahead scheduling using a novel hierarchical multi-objective optimization approach is developed for the ESS energy capacity and power budget allocation. The objectives are to simultaneously provide multiple local services, optimize the distributed ESS deployment, and provide the aggregator a clear visibility of the ESS remaining resources. This visibility of the features and use of remaining energy capacity and power budget will help the aggregator to create a virtual ESS that can be applied to provide additional services in the local and wholesale energy market. A focus on power-oriented applications provision is considered further; however, the results could be extended easily to other services. Real case studies utilizing data from the StoreNet project and complying with Irish energy market regulations further illuminate the discussion. The results obtained from employing different design methods are thoroughly examined, shedding light on their respective merits and limitations.
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.