Online Charge and Discharge Estimation of Electric Vehicles in Presence of Uncertainties in the Renewable Power and Number of Distributed Energy Resources

Nowadays, the need has increased to manage distributed energy resources due to advances in the renewable energies industry, the distance between energy resources and local loads, growth in the number of electric vehicles, and high power transmission costs. In this regard, important challenges, such as power exchange management between distributed energy resources and electric vehicle batteries, have been raised for optimal use of the power generated from these resources. Since home consumers are supposed to have wind turbines or photovoltaics installed to the supply part of their power consumption, the impact of wind and solar radiation uncertainties on their output power should be considered. Considering these challenges and in an attempt to flatten the difference curve between the generated power of resources and consumption power of local loads, this paper proposes an efficient method based on mean-field theory to control the charge and discharge of electric vehicle batteries. On the other hand, with the increase in the number of electric vehicles and distributed energy resources, the control of charging and discharging of too many batteries requires heavy and time-consuming calculations. This paper proposes an innovative method by introducing some coefficients for online estimation of the charge and discharge of batteries, which leads to a reduction in the volume of calculations. To this end, a compromise has been made between the performance, the volume of calculation reduction, and the necessity of these calculations. Simulation results illustrate the quality and efficiency of the charge and discharge estimation of batteries based on the proposed method.