Development of an Algorithm to Control and Optimize the Coordinated Charging Process of a Group of Electric Vehicles

Abstract

The increasing number of electric vehicles (EVs) 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. The deployment of EVs as an alternative to internal combustion engines will pose new challenges for electric power systems, grid operators, electricity suppliers and consumers. The impacts of the increasing penetration of EVs will be felt at the level of the distribution grid, as the lack of infrastructure capacity may hinder the increasing number of EVs from being simultaneously charged. Scenarios in which there is no local coordination between all the EVs to be charged through the same distribution power transformer may lead to new peak demands, possibly impeding the charging of all the vehicles. Therefore, the increasing number of EVs will require a control system to manage their recharging process. This study proposes the development of a decentralized charging control system, which is able to control and optimize the charging process of number of EVs in a coordinate way. Thus charging a greater number of EVs will be feasible without needing to invest in increasing the capacity of the grid infrastructure. To accomplish this, the algorithm considers the users preferences, such as their next time of use and desired state of charge while taking every users tariff scheme into consideration (i.e. different price structures/values and contracted power). The optimization objectives will be set for both the distribution grid operator, maximizing the number of EVs being charged simultaneously and for the consumers, minimizing the deviation from the minimum cost of the charge. Various entities are interested in such management. For instance, the distribution grid operator is interested in managing the charging to incorporate the maximum number of EVs without massively reinforcing the grid, whereas the consumers are interested in minimizing the cost of charging and increasing the reliability of supply. It is expected to develop a flexible algorithm, which may be used in scenarios with different electric grid characteristics and consumer load profiles. The integration of different charging patterns and various types of electricity tariffs leads to a more realistic approach.