Interruptible charge scheduling of plug-in electric vehicle to minimize charging cost using heuristic algorithm

In recent times, transportation electrification has been recognized as one of the key solutions to accelerate global GHG emission reductions. As the electric vehicle industry grows faster, plug-in electric vehicles (PEV) are expected to be the most dominant load in the utility sector in less than a decade. Regular charging of the battery energy storage system (BESS) is a mandate for the continued operation of the vehicle, and the PEVs are connected to the utility to charge. Since PEVs are mobility loads, predicting the interconnection of these mobility loads in the utility network for recharging is a major challenge. The intermittent connection of mobility loads to the grid for charging leads to an unpredictable increase in electricity demand and other grid-related issues. Optimal scheduling of PEV charging would conquer the grid-related issues and provide financial benefits to the users. In this paper, an intelligent charge scheduling technique of PEV charging for both residential and commercial charging stations using the heuristic algorithm is proposed and discussed. The primary objective of the algorithm is to achieve the minimization of PEV charging costs by implementing an interrupted charging schedule. The proposed algorithm is tested by conducting exhaustive simulation studies under several conditions for PEVs with different power ratings for residential and commercial charging scenarios. The time-of-use pricing (ToUP) system is adopted as a tariff system in this paper. A detailed comparison of the unscheduled algorithm, the modified placement algorithm (MPA) and proposed heuristic technique-based charge scheduling is carried out through simulation studies. A detailed cost analysis for charging the PEVs with the selected charge scheduling techniques for various conditions is conducted and cost minimization by implementing the proposed charging scheme is validated.