Multi-Objective Optimization of an Islanded Green Energy System Utilizing Sophisticated Hybrid Metaheuristic Approach
Yazarlar (4)
Doç. Dr. Aykut Fatih GÜVEN Yalova Üniversitesi, Türkiye
Prof. Dr. Nuran Yörükeren Kocaeli Üniversitesi, Türkiye
Elsayed Tag Eldin Faculty Of Engineering & Technology, Mısır
Mohamedmahmoud Samy
Faculty Of Engineering, Mısır
Faculty Of Engineering, Mısır
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | IEEE Access (Q2) | ||
| Dergi ISSN | 2169-3536 Dergi Bilgileri (2023) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2023 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-01-2023 |
| Cilt / Sayı / Sayfa | 11 / 1 / 103044–103068 | DOI | 10.1109/ACCESS.2023.3296589 |
| Makale Linki | http://dx.doi.org/10.1109/access.2023.3296589 | ||
| UAK Araştırma Alanları |
Akıllı Elektrik Şebekeleri
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| Özet |
| Responding to the global call for sustainable renewable energy sources amidst growing energy demands, exhaustion of fossil fuels, and increasing greenhouse gas emissions, this study introduces a multi-objective optimization of an islanded green energy system. The focus is on the implementation of a sophisticated hybrid metaheuristic approach in a Hybrid Renewable Energy System (HRES) specifically designed for a university campus in Turkey. The developed HRES combines an array of technologies, including Photovoltaic (PV) panels, wind turbines, batteries, diesel generators, and inverters. One of the novel aspects of our work is the deployment of a rule-based Energy Management Scheme for effectively orchestrating the power flow between different system components. We employed various algorithms, namely Genetic Algorithm (GA), Firefly Algorithm (FA), Particle Swarm Optimization (PSO), and a … |
| Anahtar Kelimeler |
| Energy management | hybrid energy system | hybrid firefly particle swarm optimization algorithms | microgrid sizing | renewable energy | techno economic optimization |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 80 |
| Scopus | 123 |
| Google Scholar | 149 |