A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy

In this study, we proposed a novel multiobjective optimization technique for electric vehicles’ (EVs) charging and vehicle-to-grid (V2G) scheduling. The ring seal search (RSS) algorithm ensures the optimum compatibility of the EV charging and discharging profiles revolving around multiple objectives...

Full description

Saved in:
Bibliographic Details
Main Authors: Muhammad Aurangzeb, Yifei Wang, Sheeraz Iqbal, Md Shafiullah, Sultan Alghamdi, Zahid Ullah
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:International Transactions on Electrical Energy Systems
Online Access:http://dx.doi.org/10.1155/etep/1192925
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849314599401160704
author Muhammad Aurangzeb
Yifei Wang
Sheeraz Iqbal
Md Shafiullah
Sultan Alghamdi
Zahid Ullah
author_facet Muhammad Aurangzeb
Yifei Wang
Sheeraz Iqbal
Md Shafiullah
Sultan Alghamdi
Zahid Ullah
author_sort Muhammad Aurangzeb
collection DOAJ
description In this study, we proposed a novel multiobjective optimization technique for electric vehicles’ (EVs) charging and vehicle-to-grid (V2G) scheduling. The ring seal search (RSS) algorithm ensures the optimum compatibility of the EV charging and discharging profiles revolving around multiple objectives, such as cost of charging, peak load demand reduction, and grid stability. The proposed algorithm is tested on the distribution model through the IEEE 33-bus system. A comprehensive model with real-time data from EV charging station operators (CSOs) is also ported in this research so that the EVs can be illustrated in the power distribution network. A convenient energy management strategy (EMS) called multiobjective optimization has been introduced to provide practical solutions for CSOs and EV users. The strategy had been developed based on multiple objectives to counter different trade-offs, including EV charging and discharging profiles suitable for numerous objectives encompassing charging costs, peak load demand reduction, and grid stability. The efficiency of the deterministic approach has been verified via extensive simulations and analysis, and the outcomes incorporate a definite enhancement in metrics since the RSS algorithm considerably optimized EV charging and V2G scheduling. The EV charging and discharging profiles had been optimized to take better advantage of available resource requirements by accommodating priority-based scheduling. The RSS will be able to investigate the modified parameter and the modified real system, which tells about the versatility and adaptability of the proposed method, i.e., it will be able to incorporate the changing implementation and its real-world efficacy, which is an immense merit for the adaptation of the real system. The proposed method offers a comprehensive, advanced EV charging and V2G scheduling solution. It addresses the limitations of previous methods by considering multiple objectives, utilizing a novel optimization algorithm, handling uncertainties, promoting renewable energy integration, and providing ancillary grid support. These enhancements make our method more effective, flexible, and capable of supporting the transition to a sustainable and efficient energy system.
format Article
id doaj-art-fb96cd4e109b4783af73ef779dd21c9f
institution Kabale University
issn 2050-7038
language English
publishDate 2025-01-01
publisher Wiley
record_format Article
series International Transactions on Electrical Energy Systems
spelling doaj-art-fb96cd4e109b4783af73ef779dd21c9f2025-08-20T03:52:24ZengWileyInternational Transactions on Electrical Energy Systems2050-70382025-01-01202510.1155/etep/1192925A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling StrategyMuhammad Aurangzeb0Yifei Wang1Sheeraz Iqbal2Md Shafiullah3Sultan Alghamdi4Zahid Ullah5School of Electrical EngineeringSchool of Electrical EngineeringInterdisciplinary Research Center for Sustainable Energy Systems (IRC-SES)Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES)Center of Research Excellence in Renewable Energy and Power SystemsDipartimento di Elettronica, Informazione e BioingegneriaIn this study, we proposed a novel multiobjective optimization technique for electric vehicles’ (EVs) charging and vehicle-to-grid (V2G) scheduling. The ring seal search (RSS) algorithm ensures the optimum compatibility of the EV charging and discharging profiles revolving around multiple objectives, such as cost of charging, peak load demand reduction, and grid stability. The proposed algorithm is tested on the distribution model through the IEEE 33-bus system. A comprehensive model with real-time data from EV charging station operators (CSOs) is also ported in this research so that the EVs can be illustrated in the power distribution network. A convenient energy management strategy (EMS) called multiobjective optimization has been introduced to provide practical solutions for CSOs and EV users. The strategy had been developed based on multiple objectives to counter different trade-offs, including EV charging and discharging profiles suitable for numerous objectives encompassing charging costs, peak load demand reduction, and grid stability. The efficiency of the deterministic approach has been verified via extensive simulations and analysis, and the outcomes incorporate a definite enhancement in metrics since the RSS algorithm considerably optimized EV charging and V2G scheduling. The EV charging and discharging profiles had been optimized to take better advantage of available resource requirements by accommodating priority-based scheduling. The RSS will be able to investigate the modified parameter and the modified real system, which tells about the versatility and adaptability of the proposed method, i.e., it will be able to incorporate the changing implementation and its real-world efficacy, which is an immense merit for the adaptation of the real system. The proposed method offers a comprehensive, advanced EV charging and V2G scheduling solution. It addresses the limitations of previous methods by considering multiple objectives, utilizing a novel optimization algorithm, handling uncertainties, promoting renewable energy integration, and providing ancillary grid support. These enhancements make our method more effective, flexible, and capable of supporting the transition to a sustainable and efficient energy system.http://dx.doi.org/10.1155/etep/1192925
spellingShingle Muhammad Aurangzeb
Yifei Wang
Sheeraz Iqbal
Md Shafiullah
Sultan Alghamdi
Zahid Ullah
A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy
International Transactions on Electrical Energy Systems
title A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy
title_full A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy
title_fullStr A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy
title_full_unstemmed A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy
title_short A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy
title_sort novel multiobjective optimization approach for ev charging and vehicle to grid scheduling strategy
url http://dx.doi.org/10.1155/etep/1192925
work_keys_str_mv AT muhammadaurangzeb anovelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT yifeiwang anovelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT sheeraziqbal anovelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT mdshafiullah anovelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT sultanalghamdi anovelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT zahidullah anovelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT muhammadaurangzeb novelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT yifeiwang novelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT sheeraziqbal novelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT mdshafiullah novelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT sultanalghamdi novelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy
AT zahidullah novelmultiobjectiveoptimizationapproachforevchargingandvehicletogridschedulingstrategy