Peinan Fan;Yixun Xue;Haotian Zhao;Xinyue Chang;Jia Su;Ke Wang;Hongbin Sun
{"title":"考虑区域供热网络重构增强虚拟电厂灵活性","authors":"Peinan Fan;Yixun Xue;Haotian Zhao;Xinyue Chang;Jia Su;Ke Wang;Hongbin Sun","doi":"10.17775/CSEEJPES.2022.08680","DOIUrl":null,"url":null,"abstract":"Large-scale renewable energy penetration desires higher flexibility in the power system. Combined heat and power virtual power plants (CUP-VPPs) provide an economic-effective method to improve the power system flexibility by aggregating the distributed resources of an electric-thermal coupling system. The topology can be optimally reconfigured in a power distribution system by operating tie and segment switches. Similarly, the heat flow profile can be redistributed in the district heating system (DHS) with valve switching and provide notable flexibility for CHP-VPPs self-scheduling. To address this issue, an aggregation model for the CHP-VPP is proposed to trade in typical day-ahead energy and reserve electricity markets, which is formulated as an adjustable robust optimization (ARO) problem to assure the realizability of all dispatch requests. The energy flow model is introduced in DHS formulation to make the model solvable. Due to the binary switching variables in the second stage of the proposed ARO problem, classical Karush-Kuhn-Tucker-based algorithms cannot be adopted directly and a nested column-and-constraint generation solution strategy is proposed. Case studies based on an actual CHP-VPP certify the validity of the proposed model and algorithm.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"11 2","pages":"826-837"},"PeriodicalIF":6.9000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10609312","citationCount":"0","resultStr":"{\"title\":\"Enhancing Flexibility of Virtual Power Plants Considering Reconfiguration of District Heating Network\",\"authors\":\"Peinan Fan;Yixun Xue;Haotian Zhao;Xinyue Chang;Jia Su;Ke Wang;Hongbin Sun\",\"doi\":\"10.17775/CSEEJPES.2022.08680\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large-scale renewable energy penetration desires higher flexibility in the power system. Combined heat and power virtual power plants (CUP-VPPs) provide an economic-effective method to improve the power system flexibility by aggregating the distributed resources of an electric-thermal coupling system. The topology can be optimally reconfigured in a power distribution system by operating tie and segment switches. Similarly, the heat flow profile can be redistributed in the district heating system (DHS) with valve switching and provide notable flexibility for CHP-VPPs self-scheduling. To address this issue, an aggregation model for the CHP-VPP is proposed to trade in typical day-ahead energy and reserve electricity markets, which is formulated as an adjustable robust optimization (ARO) problem to assure the realizability of all dispatch requests. The energy flow model is introduced in DHS formulation to make the model solvable. Due to the binary switching variables in the second stage of the proposed ARO problem, classical Karush-Kuhn-Tucker-based algorithms cannot be adopted directly and a nested column-and-constraint generation solution strategy is proposed. Case studies based on an actual CHP-VPP certify the validity of the proposed model and algorithm.\",\"PeriodicalId\":10729,\"journal\":{\"name\":\"CSEE Journal of Power and Energy Systems\",\"volume\":\"11 2\",\"pages\":\"826-837\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10609312\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CSEE Journal of Power and Energy Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10609312/\",\"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":"CSEE Journal of Power and Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10609312/","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}
Enhancing Flexibility of Virtual Power Plants Considering Reconfiguration of District Heating Network
Large-scale renewable energy penetration desires higher flexibility in the power system. Combined heat and power virtual power plants (CUP-VPPs) provide an economic-effective method to improve the power system flexibility by aggregating the distributed resources of an electric-thermal coupling system. The topology can be optimally reconfigured in a power distribution system by operating tie and segment switches. Similarly, the heat flow profile can be redistributed in the district heating system (DHS) with valve switching and provide notable flexibility for CHP-VPPs self-scheduling. To address this issue, an aggregation model for the CHP-VPP is proposed to trade in typical day-ahead energy and reserve electricity markets, which is formulated as an adjustable robust optimization (ARO) problem to assure the realizability of all dispatch requests. The energy flow model is introduced in DHS formulation to make the model solvable. Due to the binary switching variables in the second stage of the proposed ARO problem, classical Karush-Kuhn-Tucker-based algorithms cannot be adopted directly and a nested column-and-constraint generation solution strategy is proposed. Case studies based on an actual CHP-VPP certify the validity of the proposed model and algorithm.
期刊介绍:
The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.