Optimal charging strategy for electric vehicles using symbolic-graphic combination principle

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.