Energy Maximization for Electric Vehicle Charging Scheduling: Meta-heuristic Approaches

This study delves into the electric vehicle charging scheduling problem within a public charging service station. The scheduling task entails managing charging demands from drivers, including arrival and departure times, current battery state-of-charge, and desired state-of-charge at departure. The...

Full description

Saved in:
Bibliographic Details
Published inInternational Conference on Control, Decision and Information Technologies (Online) pp. 1 - 6
Main Authors Azerine, Abdennour, Oulamara, Ammar, Zaidi, Imene, Basset, Michel, Idoumghar, Lhassane
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2024
Subjects
Batteries
Electric vehicle charging
Genetic algorithms
Genetics
Information technology
Maintenance
Metaheuristics
Search problems
Vehicles
Online AccessGet full text

Cover

More Information
Summary:This study delves into the electric vehicle charging scheduling problem within a public charging service station. The scheduling task entails managing charging demands from drivers, including arrival and departure times, current battery state-of-charge, and desired state-of-charge at departure. The scheduler must determine whether to accept or reject charging requests based on charger availability and the maximum grid capacity of the station. The primary objective is to minimize the cumulative discrepancy between the desired and final state-of-charge levels for all electric vehicles. To address this challenge, we introduce a novel architecture that harnesses the capabilities of population-based meta-heuristics as a promising method for identifying near-optimal solutions.
ISSN:2576-3555
DOI:10.1109/CoDIT62066.2024.10708620