Stochastic Modelling and Integration of Electric Vehicles in the Distribution System Using the Jaya Algorithm

Abstract

Electric vehicles (EVs) have enormous promise for the development of future transportation systems. The widespread use of EVs could negatively impact how power systems operate, particularly at the distribution level. Therefore, smart charging techniques are essential to increasing EV adoption in general. The connection between the electricity grid and the transportation network is made at electric vehicle charging stations (EVCS), and both networks will be simultaneously impacted by the operational behaviour of EVs. Therefore, EVCS must be placed in a distribution network in the best possible way. In this paper, an efficient and smart charging approach is formulated to schedule the charging of electric vehicles so that adverse effects like an increase in peak demand for the system and the cost of charging electric vehicles are minimized. The EV load model is formulated by considering factors such as the state of charge, trip distance travelled, and the user’s charging behaviour. The proposed electric charging schedule reduces the peak load and optimizes the cost of charging. Different types of EVs are considered based on their usage patterns for making realistic problem formulations. The smart charging technique presented in this work reduces the peak demand by 30% and the cost of charging by 50%. In addition, EVCS placement is implemented alongside distributed generation on IEEE 33 and 69 bus systems to reduce power losses and improve the voltage profile by using a metaheuristic algorithm known as Jaya Algorithm. The effectiveness of the proposed algorithm is established by comparing the results with published work.