Abstract
Electric vehicles (EVs) are experiencing substantial investment and widespread acceptance. However, successful penetration of the global market is contingent upon the development of a strategic plan for the efficient allocation of EVs to optimal charging stations (CSs). This study combines several optimization models to systematically assign EVs to the optimal charging stations, with the goal of maximizing trading energy while simultaneously minimizing total response time. Factors taken into consideration include traveling distance, charging (V2G), and discharging (G2V) energy trading, total response time, and energy prices. The efficacy of the combined models is validated using GAMS and BARON solvers, with a focus on EV satisfaction factor, updated energy and response time, number of served EVs, and alleviation of range anxiety. The proposed models demonstrate 85% satisfaction factor for the majority of charging requests, reaching almost 99% for discharging requests. These results surpass those of contemporary models, underscoring the heightened effectiveness of the proposed approach.
| Original language | English |
|---|---|
| Article number | 123187 |
| Journal | Applied Energy |
| Volume | 364 |
| DOIs | |
| State | Published - 15 Jun 2024 |
Bibliographical note
Publisher Copyright:© 2024
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Keywords
- Charging station (CS)
- Electric vehicle (EV)
- Electric vehicle assignment
- G2V
- Optimization
- Smart city
- V2G
ASJC Scopus subject areas
- Building and Construction
- Renewable Energy, Sustainability and the Environment
- Mechanical Engineering
- General Energy
- Management, Monitoring, Policy and Law
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