Energy Management System for Hybrid Renewable Energy-Based Electric Vehicle Charging Station

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Karmaker, Ashish Kumar
Hossain, Md Alamgir
Pota, Hemanshu Roy
Onen, Ahmet
Jung, Jaesung
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2023
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Abstract

This paper introduces an energy management algorithm for a hybrid solar and biogas-based electric vehicle charging station (EVCS) that considers techno-economic and environmental factors. The proposed algorithm is designed for a 20-kW EVCS and uses a fuzzy inference system in MATLAB SIMULINK to manage power generation, EV power demand, charging periods, and existing charging rates to optimize real-time charging costs and renewable energy utilization. The results show that the proposed algorithm reduces energy costs by 74.67% compared to existing flat rate tariffs and offers lower charging costs for weekdays and weekends. The integration of hybrid renewables also results in a significant reduction in greenhouse gas emissions, with payback periods for charging station owners being relatively short, making the project profitable.

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IEEE Access

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11

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

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Engineering

Information and computing sciences

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Computer Science, Information Systems

Engineering, Electrical & Electronic

Telecommunications

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Karmaker, AK; Hossain, MA; Pota, HR; Onen, A; Jung, J, Energy Management System for Hybrid Renewable Energy-Based Electric Vehicle Charging Station, IEEE Access, 2023, 11, pp. 27793-27805

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