Energy cost minimization through optimization of EV, home and workplace battery storage

作     者：ZHONG QianWen BUCKLEY Stephen VASSALLO Anthony SUN YiZe 

作者机构：School of Mechanical Engineering Donghua University Faculty of Engineering & Information Technologies University of Sydney 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2018年第61卷第5期

页      面：761-773页

核心收录：

学科分类：080801[工学-电机与电器] 0808[工学-电气工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：supported by the China Scholarship Council and Donghua University Graduate Student Degree Thesis Innovation Fund Project (Grant No. CUSF-DH-D-2013059) 

主　　题：electric vehicle electric vehicle(EV) optimization energy management storage battery vehicle to grid(V2G) 

摘      要：Besides grid-to-vehicle(G2 V) and vehicle-to-grid(V2 G) functions, the battery of an electric vehicle(EV) also has the specific feature of mobility. This means that EVs not only have the potential to utilize the storage of cheap electricity for use in high energy price periods, but can also transfer energy from one place to another place. Based on these special features of an EV battery, a new EV energy scheduling method has been developed and is described in this article. The approach is aimed at optimizing the utilization EV energy for EVs that are regularly used in multiple places. The objective is to minimize electricity costs from multiple meter points. This work applies real data in order to analyze the effectiveness of the method. The results show that by applying the control strategy presented in this paper at locations where the EVs are parked, the electricity cost can be reduced without shifting the demand and lowering customer s satisfaction. The effects of PV size and number of EVs on our model are also analyzed in this paper. This model has the potential to be used by energy system designers as a new perspective to determine optimal sizes of generators or storage devices in energy systems.