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April 30, 2026Energies0 citationsOpen Access

Two-Stage Stochastic Optimization of Renewable-Integrated EV Charging Stations in Loop-Distribution Networks

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MCMadiha ChaudharyUniversity of Engineering and Technology PeshawarAQAffaq QamarImam Mohammad ibn Saud Islamic UniversityMAMuhammad Imran Akbar

Key Points

  • The study aims to optimize the integration of electric vehicle charging stations and renewable energy systems in power distribution networks.
  • Developed an optimal allocation framework using a looped configuration of the IEEE 33-bus system.
  • Employed Improved Grey Wolf Optimizer and Metaheuristic COOT-Based Optimization for siting and sizing.
  • Focused on minimizing active power losses and enhancing voltage stability.
  • MCBO algorithm achieved a maximum reduction of 82.49% in active power losses with standalone PV integration.
  • Wind turbine generator integration resulted in up to 85.74% loss reduction without EVCSs.

Abstract

The accelerating adoption of electric vehicles (EVs) alongside renewable distributed generators (RE-DGs), particularly solar photovoltaic (PV) and wind-based systems, is reshaping the operational and planning paradigms of modern power distribution networks. In this study, an optimal allocation framework is developed for the simultaneous integration of EV charging stations (EVCSs) and RE-DGs within a looped configuration of the IEEE 33-bus distribution system. Two advanced metaheuristic techniques—Improved Grey Wolf Optimizer (IGWO) and Metaheuristic COOT-Based Optimization (MCBO)—are employed to determine the optimal siting and sizing of these resources. The optimization objectives focus on minimizing active power losses while enhancing voltage stability and reducing overall voltage deviation across the network. Simulation results reveal that the MCBO algorithm demonstrates superior performance, yielding a maximum reduction of 82.49% in active power losses with the integration of standalone PV, and 78.14% when PV is deployed in conjunction with EVCSs. Similarly, wind turbine generator (WTG) integration resulted in a loss reduction of 85.74% without EVCSs and 81.57% with EVCS integration using the same approach. The findings further indicate that looped network configurations consistently outperform traditional radial systems in both loss reduction and voltage profile enhancement, underscoring their suitability for accommodating future EV and renewable energy penetrations in smart distribution grids.

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Cite This Study

Chaudhary et al. (2026) studied this question.

synapsesocial.com/papers/69f2a4da8c0f03fd67763e68https://doi.org/10.3390/en19092102
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