Optimizing the Coordinated Charging of a Group of Electric Vehicles

Abstract

The increasing number of electric vehicles in the near future will require control systems endowed with adequate algorithms able to manage their recharging process and avoiding massive investment in reinforcement of low voltage distribution network infrastructure. This work proposes the development of a locally decentralized charging control algorithm, which is able to optimize the charging process of a group of independent EVs. It adjusts the demand profiles of every EV to take advantage of low electricity prices (according to every consumer tariff scheme) during the charging period. Besides considering individual tariff schemes and contracted power the algorithm also takes into consideration users' preferences, such as their desired state-of-charge. In scenarios with large penetration of EVs and different time- of-use tariffs the probability of not being able to charge all EVs at minimum cost is high. Thus, in this study the optimization objectives are minimizing the deviation of the actual charging cost from the minimum charging cost for all the users, as well as, minimizing the maximum individual cost deviation. The integration of different charging patterns and various types of electricity tariffs schemes, with different contracted power values, leads to a more realistic approach and improves what has been done in past studies. One of the main reasons to choose the implementation level of low voltage distribution grids is the fact that it is probably where capacity problems first arise when the number of plugged EVs into the grid increases. In the next few years, it is expected that the rate of purchasing EVs will increase in several developed countries. To this reason, it is extremely important to develop approaches in advance to deal with new type of load which will be imposed by EVs. Accordingly, this work propose a method able to deal with the upcoming trends of EVs, positively contributing to increase the global energy efficiency in transportation system.