Optimizing Solar-Powered EV Charging: A Techno-Economic Assessment Using Horse Herd Optimization

Krishan Chopra, M. K. Shah, K. R. Niazi, Gulshan Sharma () and Pitshou N. Bokoro
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Krishan Chopra: Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur 302017, India
M. K. Shah: Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur 302017, India
K. R. Niazi: Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur 302017, India
Gulshan Sharma: Department of Electrical and Electronics Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa
Pitshou N. Bokoro: Department of Electrical and Electronics Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa

Energies, 2025, vol. 18, issue 17, 1-21

Abstract: Mass market adoption of EVs is critical for decreasing greenhouse gas emissions and dependence on fossil fuels. However, this transition faces significant challenges, particularly the limited availability of public charging infrastructure. Expanding charging stations and renewable integrated EV parking lots can accelerate the adoption of EVs by enhancing charging accessibility and sustainability. This paper introduces an integrated optimization framework to determine the optimal siting of a Residential Parking Lot (RPL), a Commercial Parking Lot (CPL), and an Industrial Fast Charging Station (IFCS) within the IEEE 33-bus distribution system. In addition, the optimal sizing of rooftop solar photovoltaic (SPV) systems on the RPL and CPL is addressed to enhance energy sustainability and reduce grid dependency. The framework aims to minimize overall power losses while considering long-term technical, economic, and environmental impacts. To solve the formulated multi-dimensional optimization problem, Horse Herd Optimization (HHO) is used. Comparative analyses on IEEE-33 bus demonstrate that HHO outperforms well-known optimization algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) in achieving lower energy losses. Case studies show that installing a 400-kW rooftop PV system can reduce daily energy expenditures by up to 51.60%, while coordinated vehicle scheduling further decreases energy purchasing costs by 4.68%. The results underscore the significant technical, economic, and environmental benefits of optimally integrating EV charging infrastructure with renewable energy systems, contributing to more sustainable and resilient urban energy networks.

Keywords: electric vehicle; renewable; charging infrastructure; parking lots; charging stations (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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