Optimal charging strategy for electric vehicles using symbolic–graphic combination principle. Issue 13 (31st May 2019)

• Record Type: Journal Article
• Authors: Zhang, Jialei; Pei, Yunqing; Shen, Jiaming; Wang, Laili; Ding, Tao
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 13(2019)
• Page Start: 2761
• Page End: 2769
• Publication Date: 2019-05-31
• Subjects: bin packing -- power grids -- optimisation -- electric vehicles -- scheduling -- battery powered vehicles -- genetic algorithms -- battery chargers; optimal charging strategy -- electric vehicles -- symbolic–graphic combination principle -- reliable technical support -- increasing electric vehicle penetration -- charging strategies -- current EV charger technology -- charging start time -- time instant -- valley‐filling charging problem -- rectangle packing problem -- valley‐filling problem -- load valley -- valley‐filling effect -- Zero‐Gap Lowest Horizontal line algorithm; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.6831
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : To provide reliable technical support for the power grid to accommodate the increasing electric vehicle (EV) penetration, various charging strategies have been studied in the literature. Considering the difficulties of the device‐level implementation and the limitations of the current EV charger technology, this study focuses on co‐ordinating the charging start time (i.e. the time instant when each EV starts charging). To avoid excessive reduction of the adjustable range of the charging start time, this study applies a symbolic–graphic combination principle to address this problem. This involves formulating the valley‐filling charging problem as a rectangle packing problem, which is equivalent to divide the valley‐filling problem into two sub‐problems: filling the load valley and optimising the valley‐filling effect. Furthermore, a Zero‐Gap Lowest Horizontal line (ZGLH) algorithm is proposed to fill the load valley without producing any undesirable gaps. In addition, a genetic algorithm (GA) is employed to further optimise the valley‐filling effect by regulating the scheduled sequence. The proposed ZGLH algorithm can guarantee the charging start time to be continuously regulated within the controllable range rather than discretely regulated as in other works, and it does not add extra computational overhead. The effectiveness of the optimal charging strategy was quantitatively verified by several simulation cases.