Optimized time step for electric vehicle charging optimization considering cost and temperature

Abstract

An optimal decentralized scheduling strategy for charging one Electric Vehicle (EV) is proposed to minimize the customer charging cost. Moreover, the EVs can offers more profit when considering the vehicle to grid feature, by discharging the EV in the grid at high peak demand the EV’ owner can earn money and reduce his charging bill. Compared to existing methods, the main advantages of the proposed strategy is the considerations of an optimized time step. By doing so, the optimization problem uses a minimum number of decision variables and constraints. Then, the problem can be solved by all optimization method to reach the global optimum in reduced time. To formulate and solve a non-linear constrained optimization problem, the scheduling process takes into consideration: the time of arrival and time departure of the EV, the daily energy prices, the initial State of Charge (SoC) and the final SoC desired by the customer, the power limitations, and the temperature. The results obtained show a high impact of the optimal scheduling strategy and significant charging cost reduction compared to the uncontrolled charging and fixed time step algorithms. Moreover, the charging strategy only requires that each EV solves its optimization problem locally, therefore, its deployment requires a low computing capacity.