{"title":"Integrated Planning of Urban Electricity and Gas Distribution Systems Considering Demand Response","authors":"Ke Sun, Chun Li, Ji Wu, Chengcheng Shao","doi":"10.1109/EI250167.2020.9346695","DOIUrl":null,"url":null,"abstract":"In this paper, we developed an optimal planning model for an integrated urban energy system in order to explore the potential for integrated operation between different energy forms. Both the respective modes of operation of the grid and the natural gas network are considered, as well as the application of coupling units and demand response. Nonlinearities in the operation of the energy network are handled by the piecewise linearization methods. Therefore, a mixed-integer linear planning (MILP) model is developed that can be efficiently solved by existing solvers. A case study of 26 electric nodes and 20 gas node systems is conducted to validate the effectiveness of the method. The case results show that the integrated demand response can reduce system cost and improve the load curve.","PeriodicalId":339798,"journal":{"name":"2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EI250167.2020.9346695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we developed an optimal planning model for an integrated urban energy system in order to explore the potential for integrated operation between different energy forms. Both the respective modes of operation of the grid and the natural gas network are considered, as well as the application of coupling units and demand response. Nonlinearities in the operation of the energy network are handled by the piecewise linearization methods. Therefore, a mixed-integer linear planning (MILP) model is developed that can be efficiently solved by existing solvers. A case study of 26 electric nodes and 20 gas node systems is conducted to validate the effectiveness of the method. The case results show that the integrated demand response can reduce system cost and improve the load curve.