Multi-objective optimisation model and hybrid optimization algorithm for Electric Vehicle Charge Scheduling
Durga Mahato, Vikas Kumar Aharwal, Apurba Sinha
Abstract
Electric vehicles (EV) are moderately defeating more roads and replacing pollutants of classical vehicles. Due to rising EV, it is imperative to provide charging stations. However, unscheduled EVs are left because of the unavailability of adequate energy or charging slots. This paper develops an optimisation aware technique for charge scheduling in EV. The first step is the simulation of EV in the Vehicular Ad-hoc Network (VANET) model. Here, the discovery of the changing request from EVs and accessible charging stations is performed. Then, the charge scheduling algorithm is called for scheduling the EV, wherein the charge scheduling algorithm is newly modelled using Jaya-based Multi-Verse Optimizer (JMVO). The proposed JMVO is devised by combining Multi-Verse Optimiser (MVO) and Jaya optimisation algorithm. Here, a multiobjective fitness function is newly devised with certain parameters, including charging cost, user preference, remaining power and distance parameter. As per the scheduling method, the EVs are allocated to the charging station. Then, the EV charging scheduling model attributes are updated to expose the method’s efficiency. The proposed JMVO outperformed with the smallest charging cost of 62.721, smallest fitness of 0.010, highest power of 2.605J and highest user convenience of 0.769. [email protected]