Hussain, Shahid and Irshad, Reyazur Rashid and Pallonetto, Fabiano and Jan, Qasim and Shukla, Saurabh and Thakur, Subhasis and Breslin, John G. and Kim, Yun-Su and Rathore, Muhammad Ahmad and El-Sayed, Hesham (2023) Enhancing the Efficiency of Electric Vehicles Charging Stations Based on Novel Fuzzy Integer Linear Programming. IEEE Transactions on Intelligent Transportation Systems, 24 (9). pp. 9150-9164. ISSN 1524-9050

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Abstract

The electric vehicles (EVs) charging stations (CSs) at public premises have higher installation and power consumption costs. The potential benefits of public CSs rely on their efficient utilization. However, the conventional charging methods obligate a long waiting time and thereby deteriorate their efficiency with low utilization. This paper suggests a novel fuzzy integer linear programming and a heuristic fuzzy inference approach (FIA) for CSs utilization. The model introduces the underlying fuzzy inference system and a detailed formulation for obtaining the optimal solution. The developed fuzzy inference incorporates the uncertain and independent available power, required state-of-charge, and dwell time from the power grid and EVs domains and correlates them into weighted control variables. The FIA automates the service provision for the EVs with the most urgent requirements by resolving the objective function utilizing the weighted control variables, thereby optimizing the waiting time and the CSs utilization. To evaluate the effectiveness of the proposed FIA, several case studies were conducted, corresponding to different parking capacities and installations of CSs. Moreover, the simulations were conducted on EVs with varying battery capacities, and their performance was evaluated based on several metrics, including average waiting time, utilization of CSs, fairness, and execution time. The simulation results have confirmed that the effectiveness of the proposed FIA scheduling method is considerably higher than that of the other methods discussed.

Item Type:	Article
Keywords:	Charging stations; fuzzy integer linear programming; fuzzy inference system; utilization; waiting time;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI Faculty of Social Sciences > School of Business
Item ID:	18924
Identification Number:	https://doi.org/10.1109/TITS.2023.3274608
Depositing User:	Fabiano Pallonetto
Date Deposited:	24 Sep 2024 13:15
Journal or Publication Title:	IEEE Transactions on Intelligent Transportation Systems
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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