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<p>The rising global warming and increased carbon emissions have transformed the transportation sector. The conventional internal combustion engine vehicle (ICEV) and public transport buses are being replaced with the electric vehicles (EVs) and electrified buses. The additional power demand due to integration of EVs and electrified public transport has raised challenges for power distribution network operators. Renewable energy sources like Photo voltaic (PVs) and capacitor banks (CBs) are being introduced into the distribution networks to meet the increasing power demand and improve the network performance. The improper sizing and positioning of electric vehicle charging stations (EVCS), PVs, and CBs can worsen the network performance if not optimally placed. This paper introduces the Multi objective star fish optimization algorithm (MOSFOA) for the optimal sizing and placement of EVCS, PVs, and CBs across the standard IEEE-69 bus and a real 60-bus medium voltage distribution networks. The main objective of the proposed methodology is improving technical, economic and environmental aspects while considering the stochastic nature of EVs, intermittence nature of PVs, and the discrete nature of CBs simultaneously. The simulation results of the proposed strategy demonstrate the enhanced performance in technical, economic, and environmental benefits compared with other renowned optimization algorithms.</p>

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A Multi-Objective Strategy for Optimal Placement and Sizing of Electric Vehicle Charging Stations, Photovoltaic Systems and Capacitor Banks in Distribution Networks

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Maaz Ahmad

摘要

The rising global warming and increased carbon emissions have transformed the transportation sector. The conventional internal combustion engine vehicle (ICEV) and public transport buses are being replaced with the electric vehicles (EVs) and electrified buses. The additional power demand due to integration of EVs and electrified public transport has raised challenges for power distribution network operators. Renewable energy sources like Photo voltaic (PVs) and capacitor banks (CBs) are being introduced into the distribution networks to meet the increasing power demand and improve the network performance. The improper sizing and positioning of electric vehicle charging stations (EVCS), PVs, and CBs can worsen the network performance if not optimally placed. This paper introduces the Multi objective star fish optimization algorithm (MOSFOA) for the optimal sizing and placement of EVCS, PVs, and CBs across the standard IEEE-69 bus and a real 60-bus medium voltage distribution networks. The main objective of the proposed methodology is improving technical, economic and environmental aspects while considering the stochastic nature of EVs, intermittence nature of PVs, and the discrete nature of CBs simultaneously. The simulation results of the proposed strategy demonstrate the enhanced performance in technical, economic, and environmental benefits compared with other renowned optimization algorithms.