Abstract
Electric vehicle charging is one of the common techniques for techno-economic energy management in the distribution system, which, if implemented properly, brings several benefits such as the peak load shaving, total costs reduction, losses minimization, etc. Unlike traditional charging methods, it is not necessary to completely charge electric vehicles. Instead, each vehicle can be charged smartly just based on its demand for its next trips. In this way, charging takes less time and the total consumption is balanced without any discomfort for the drivers. To implement this smart method, electric vehicle owners must fill in an information sheet that contains the number and lengths of the their next. Then, its required energy is calculated this info, and the initial battery state of charge. Finally, the charging management system starts the planning according to its upstream distribution system operator. Several parameters are needed for the planning such as time of use tariff of the electricity, the distribution transformer or substation physical limits, the rate of the charge (normal or fast), etc. The aim of the planning is to minimize the charging cost considering the technical and economic constraints. Here, the YALMIP and MOSEK software are used as the solver of the proposed mixed-integer linear programming model.
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