Off-Grid Hybrid Microgrid Sizing Optimization Using The Bezier Curve Optimization Algorithm
14th International Conference on Smart Grid, icSmartGrid 2026, Suceava, Romanya, 6 - 09 Temmuz 2026, ss.678-683, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/icsmartgrid70882.2026.11680897
- Basıldığı Şehir: Suceava
- Basıldığı Ülke: Romanya
- Sayfa Sayıları: ss.678-683
- Anahtar Kelimeler: bezier curve optimization, glider snake optimization, gray langur optimization, hybrid microgrid, optimal sizing
- Gazi Üniversitesi Adresli: Evet
Özet
This study investigates the problem of optimally sizing a hybrid off-grid microgrid system consisting of photovoltaic (PV), wind turbine (WT), diesel generator (DG), and battery energy storage system (BESS) components for the Gökçeada/Türkiye settlement. This problem was solved using Bezier curve optimization (BCO), glider snake optimization (GSO), and gray langur optimization (GLO) algorithms. These algorithms were evaluated under three different scenarios: economic, balanced, and environmental. Real meteorological data and a synthetic load profile obtained from the NASA POWER database were used in the analyses. The results showed that the BCO algorithm produced more accurate results compared to other algorithms by providing the lowest average objective function and standard deviation values in all scenarios. In the best design results obtained with BCO, the renewable energy ratio ranged from 92.49% to 97.95%, while carbon emissions were reduced from 635383 kg/year to 178506 kg/year. In contrast, energy costs ranged from $0.2700 to $0.3268 per kWh. Based on the results obtained, it was concluded that BCO produces effective, consistent, and reliable solutions in hybrid microgrid sizing optimization and can be used confidently in optimal microgrid design problems.