Title: Research on intelligent charging method of electric vehicles based on virtual power plants

Authors: Lianrong Pan; Jiayi Yang; Peikai Li

Addresses: Power Dispatch Control Centre of Guangxi Power Grid Co Ltd., Nanning, Guangxi, China ' Power Dispatch Control Centre of Guangxi Power Grid Co Ltd., Nanning, Guangxi, China ' Power Dispatch Control Centre of Guangxi Power Grid Co Ltd., Nanning, Guangxi, China

Abstract: The rising number of Electric Vehicles (EVs) requires new charging options to address grid integration and environmental concerns. Innovative charging methods are needed to reduce the burden on conventional infrastructure from electric automobiles. By applying these methods to VPPs, we can improve grid efficiency, electric car charging and energy sustainability. This research proposes the VPP-EV Charging Optimisation Framework (VPECOF) to evaluate the necessity and feasibility of an intelligent charging strategy for electric cars. A solution to the increased demand for electric vehicle charging infrastructure that meets grid stability and sustainable energy objectives is being developed using VPP technology and Smart Charging Optimisation Algorithms (SCOA). The suggested technique considers grid capacity, renewable energy availability and user preferences to improve charge schedules. This research simulates and analyses the intelligent charging strategy in the VPP framework, proving its efficacy and feasibility. The data may illuminate the benefits of synchronised electric car charging, such as peak demand reduction, grid resilience and renewable power integration. The study impacts transportation and energy regulators, utilities and stakeholders. The work improves electric car intelligent charging techniques and has consequences for their evolution.

Keywords: electric vehicles; virtual power plant; VPP-EV charging optimisation framework; grid efficiency; renewable energy sources; smart charging optimisation algorithm.

DOI: 10.1504/IJGEI.2025.149570

International Journal of Global Energy Issues, 2025 Vol.47 No.6, pp.580 - 600

Received: 27 May 2024
Accepted: 26 Nov 2024
Published online: 07 Nov 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article