Optimal integration of electric vehicle charging stations into a renewable-supported multi-energy system

Electric Power Systems Research · Ekim 2025

YÖKSİS Kayıtları

Electric Power Systems Research · 2025 SCI-Expanded

Dr. Öğr. Üyesi MEHMET ÇEÇEN →

YÖKSİS Kayıtları — ISSN Eşleşmesi

A fast hybrid PLL with an adaptive all-pass filter under abnormal grid conditions

2020 ISSN: 0378-7796 SCI-Expanded

Dr. Öğr. Üyesi FEHMİ SEVİLMİŞ →

10.1016/j.epsr.2020.106303

A fast hybrid PLL with an adaptive all-pass filter under abnormal grid conditions

2020 ISSN: 0378-7796 SCI-Expanded Q2

Dr. Öğr. Üyesi FEHMİ SEVİLMİŞ →

10.1016/j.epsr.2020.106303

Optimal integration of electric vehicle charging stations into a renewable-supported multi-energy system

2025 ISSN: 0378-7796 SCI-Expanded Q2

Dr. Öğr. Üyesi MEHMET ÇEÇEN →

10.1016/j.epsr.2025.111832

Makale Bilgileri

Dergi Electric Power Systems Research

ISSN03787796

Yayın TarihiEkim 2025

Cilt / Sayfa247

DOI10.1016/j.epsr.2025.111832

Scopus ID2-s2.0-105004645053

Özet This study examines optimal allocation approaches for electric vehicle charging stations (EVCSs) with and without distributed generation (DGs) systems in renewable-supported multi-energy systems (RSMES). A hybrid approach combining Grey Wolf Optimization (GWO) and Dynamic Fitness-Distance Balance (dFDB) (dFDBGWO) algorithms addresses two objectives: minimizing active power losses and voltage deviations. Validated through IEEE 33-bus and 69-bus test systems, the proposed dFDBGWO algorithm significantly outperforms conventional methods, achieving up to a 66.02% reduction in active power losses and substantial improvements in voltage profiles. The results demonstrate that the coordinated placement of EVCSs and DGs significantly enhances grid stability, reduces voltage deviations to near-nominal values, and improves overall system efficiency. This integration strategy effectively supports the growing electric vehicles (EVs) infrastructure while contributing to a more sustainable energy landscape.