Scheduling Strategy for Charging and Discharging of Electric Vehicles to Reduce the Cost based on Hybrid Local Optimum and Global Optimum Scheme

International Journal of Electronics and Communication Engineering

© 2025 by SSRG - IJECE Journal

Volume 12 Issue 3

Year of Publication : 2025

Authors : Abhay Khonje, B.P. Patil

10.14445/23488549/IJECE-V12I3P107

How to Cite?

Abhay Khonje, B.P. Patil, "Scheduling Strategy for Charging and Discharging of Electric Vehicles to Reduce the Cost based on Hybrid Local Optimum and Global Optimum Scheme," SSRG International Journal of Electronics and Communication Engineering, vol. 12,  no. 3, pp. 79-87, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I3P107

Abstract:

The growing usage of EVs has led to considerable progress in eco-friendly transportation. However, the effective administration of EV charging and discharging continues to be a vital challenge for personal vehicle owners and the stability of the larger electrical grid. This document introduces an innovative scheduling approach that utilizes quadratic programming to enhance the charging and discharging of electric vehicles, aiming primarily at reducing costs. The various factors involved in this scheduling technique are stations, EVs, city infrastructure, and the EV coverage area. The main aim of this research is to minimize the cost and make it most effective so that it can reduce the problem that occurs during a quadratic programming optimization task; the approaches that are utilized for this process are hybrid local and global optimum approaches. The properties of this scheduling approach are that it ensures that EVs can get changed at the time of off-peak hours so that it can optimize energy consumption because the electricity prices are lower at the time of off-peak hours. The experimental demonstration of the proposed scheduling strategy is performed in MATLAB/Simulink, and the efficiency of the proposed scheduling strategy is validated for the EVs.

Keywords:

Electric Vehicles (EVs), Global optimum scheme, Scheduling strategy, Energy consumption, Cost reduction.

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