The present research project considers the theoretical analysis and the computational implementation of an optimization method to solve the problem of optimal programming of the charging of electric vehicles in secondary electric distribution networks in order to find charging strategies that guarantee the feasible operation of the secondary network and minimize the system losses and deviation in the operating voltage. In this optimization proposal, it is considered only a secondary network that feeds a set of houses and the owner of the electric vehicle charges his vehicle in his own residence. For each day of programming, the know data is: the initial levels of the vehicle's state of charge, vehicle types, a time frame in which the vehicle is at home and available for charging, the system's hourly demand curve, network's data, the capacity of the transformer that feed the secondary network, etc. The result of the optimization strategy provides the times at which each vehicle is to be charged and the losses values resulting from the optimization process. It is intended to optimize the problem by using a Greedy Randomized Adaptive Search Procedure (GRASP) algorithm. The GRASP algorithm is one of the best meta-heuristics available to optimize complex problems.
News published in Agência FAPESP Newsletter about the scholarship: