ArticleScientific reports2025
Optimal scheduling of solar powered EV charging stations in a radial distribution system using opposition-based competitive swarm optimization.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Efficient management of EV charging stations and DSTATCOM in distribution systems through POA-DTRSRN approach.Scientific reports · 2026Article
- Development of a solar-integrated energy management system for grid-to-vehicle and vehicle-to-grid power exchange.Scientific reports · 2025Article
- A scalable cloud-integrated AI platform for real-time optimization of EV charging and resilient microgrid energy management.Scientific reports · 2025Article
- Optimizing solar farm interconnection networks using graph theory and metaheuristic algorithms with economic and reliability analysis.Scientific reports · 2025Article
- Optimal allocation of STATCOM for multi-objective ORPD problem on thermal wind solar hydro scheduling using driving training based optimization.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Solar-powered EV charging stations offer a sustainable and reliable alternative to traditional charging infrastructure, significantly alleviating stress on legacy grid systems. However, the intermittent nature of renewable energy sources poses a challenge for energy management in power distribution networks. To address this, optimal charge/discharge scheduling of EVs becomes crucial. This paper introduces an innovative Opposition-based Competitive Swarm Optimization (OCSO) technique to minimize the total charging cost of EVs in the IEEE 33-bus distribution system. Five strategically placed solar-powered charging stations on distinct buses are evaluated under three charging modes: dumb charging, smart grid-to-vehicle (G2V) charging, and smart vehicle-to-grid (V2G) charging. Comprehensive analyses are performed on critical parameters, including bus voltage stability, EV charging load profiles, electricity cost profiles, state-of-charge (SOC) dynamics, and the thermal performance of distribution transformers. Notably, total power losses are reduced by 13.7% and 21.6% in smart G2V and smart V2G modes, respectively, compared to dumb charging. Furthermore, the cumulative ageing factor of distribution transformers under smart V2G charging is reduced by 11.86%, indicating extended transformer lifespan. These findings demonstrate that solar-powered EV charging stations, coupled with advanced energy management strategies, can effectively mitigate grid impacts, enhance operational efficiency, and contribute to reducing net carbon emissions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.