Haoming Zhao, Zhanbo Xu, Jiang Wu, Kun Liu, Lei Yang, X. Guan
{"title":"Optimal Coordination of EVs and HVAC Systems with Uncertain Renewable Supply","authors":"Haoming Zhao, Zhanbo Xu, Jiang Wu, Kun Liu, Lei Yang, X. Guan","doi":"10.1109/COASE.2019.8843270","DOIUrl":null,"url":null,"abstract":"The stochastic demand of electric vehicles (EVs) charging and building’s heating, ventilation and air conditioning (HVAC) system account for a large proportion in social energy consumption. The photovoltaic (PV) system becomes miniaturized and applied on roof of smart buildings with the development of a sequence of PV power generation technologies. Due to the randomness of weather conditions and human behavior, the power supply is random as well as the power demand. To guarantee the power balance in real-time, it is necessary to coordinate the dispatch of EVs and HVACs with the uncertainties from both sides. A mixed integer programming is formulated to model the coordination of the EVs and HVAC systems. The operation strategies of EVs and HVAC systems under uncertainties in both supply and demand are determined based on the model predictive control (MPC) framework. The performance of the coordination of EVs and HVAC systems is demonstrated using numerical case studies. The results show that coordinating the operation of EVs and HVAC systems can significantly reduce the cost and accommodate the uncertainties in the PV supply.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"74 1","pages":"733-738"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2019.8843270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The stochastic demand of electric vehicles (EVs) charging and building’s heating, ventilation and air conditioning (HVAC) system account for a large proportion in social energy consumption. The photovoltaic (PV) system becomes miniaturized and applied on roof of smart buildings with the development of a sequence of PV power generation technologies. Due to the randomness of weather conditions and human behavior, the power supply is random as well as the power demand. To guarantee the power balance in real-time, it is necessary to coordinate the dispatch of EVs and HVACs with the uncertainties from both sides. A mixed integer programming is formulated to model the coordination of the EVs and HVAC systems. The operation strategies of EVs and HVAC systems under uncertainties in both supply and demand are determined based on the model predictive control (MPC) framework. The performance of the coordination of EVs and HVAC systems is demonstrated using numerical case studies. The results show that coordinating the operation of EVs and HVAC systems can significantly reduce the cost and accommodate the uncertainties in the PV supply.