Smart scheduling and economic analysis of electric vehicles for peak load shaving considering renewable energy resources

This paper reflects the outcome of an investigation on economic benefits of scheduling electric vehicles charging and discharging for the purpose of peak load shaving in a distribution system. In this study, a number of wind turbines as a favourite type of renewable energy resources are placed in the power system under study. Two different cases are define with time of use and real time price to find related costs. Grid constraints like voltage profile and lines thermal limits beside customers comfort level are considered as the mandatory conditions to be met through the study. Genetic algorithm is utilized to find optimum value of charging and discharging power on an hourly based for individual vehicles corresponding to pricing signals. Monte Carlo simulation method is used to model uncertainties for the study. Simulation results verify electric vehicles capabilities in shaving peak load of the system. Intelligent scheduled charging also shows a substantial drop in cost of customers compared to the case of unplanned charging.