LAUSR

In recent days, the deployment of electric vehicles (EVs) in automobile sector is increasing the load demand in the distribution system. To deal with this load demand, the charging management needs to be improved. Nevertheless, an EV needs several hours to complete charge. Reducing the charging time, energy consumption is a huge contest to deal with the promotion of EV over conventional vehicles. The condition of the itineraries may affect the energy consumption of the EV, which needs to be considered before fulfilling the energy demand. In this article, these are considered assigning suitable charging stations (CS) to individual EVs and their scheduling is taken as an optimization problem. The first part deals with the proper assignment of CS, which is a linear optimization problem and the second deals with the charging scheduling problem. An “intelligent charging scheduling algorithm (ICSA)” is proposed with the integration of Henry gas solubility optimization to minimize total daily price incurred by the CS operator. Later, ICSA is clubbed with other standard optimization techniques considering practical constraints. A 2 m point estimation method has been utilized to tackle the uncertainty and its performance has been compared with the Monte-Carlo simulation technique. The robustness of ICSA is evaluated and confirmed using the Wilcoxon signed rank test and Quade test.