Work

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

Year: 2026

Type: article

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.

Source: Energies

DOI: 10.3390/en19092102

Authors: Madiha Chaudhary, Affaq Qamar, Muhammad Imran Akbar, Muhammad Noman

Institutions: US-Pakistan Center for Advanced Studies in Energy, University of Engineering and Technology Peshawar, Imam Mohammad ibn Saud Islamic University

Language: English

Topic: Optimal Power Flow Distribution

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $3,137