Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Ameer A. Kareim Al-Sahlawi (), Shahrin Md. Ayob (), Chee Wei Tan, Hussein Mohammed Ridha and Dhafer Manea Hachim
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Ameer A. Kareim Al-Sahlawi: Division of Electrical Power Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM, Skudai 81310, Johor, Malaysia
Shahrin Md. Ayob: Division of Electrical Power Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM, Skudai 81310, Johor, Malaysia
Chee Wei Tan: Division of Electrical Power Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM, Skudai 81310, Johor, Malaysia
Hussein Mohammed Ridha: Advanced Lightning, Power and Energy Research (ALPER), Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Dhafer Manea Hachim: Engineering Technical College/Najaf, Al-Furat Al-Awsat Technical University, Najaf 31001, Iraq

Sustainability, 2024, vol. 16, issue 6, 1-35

Abstract: Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid ( E S O L D ). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × 10 − 2 USD/kWh, the GCF is equal to 7.34 × 10 − 5 kWh, and the E S O L D is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development.

Keywords: renewable energy sources; grid-connected; V2G; multi-objective optimization; arithmetic optimization algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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