An Enhanced Hybrid TLBO--ANN Framework for Accurate Photovoltaic Power Prediction Under Varying Environmental Conditions
Yazarlar (2)
Dr. Öğr. Üyesi Salih ERMİŞ Kırşehir Ahi Evran Üniversitesi, Türkiye
Dr. Öğr. Üyesi Oğuz TAŞDEMİR Kırşehir Ahi Evran Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Applied Sciences Switzerland (Q2)
Dergi ISSN 2076-3417 Dergi Bilgileri (2026)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 01-2026
Cilt / Sayı / Sayfa 16 / 1 / 157–0 DOI 10.3390/app16010157
Makale Linki https://doi.org/10.3390/app16010157
UAK Araştırma Alanları
Yapay Zeka Yenilenebilir Enerji Sistemleri Elektrik Tesisleri
Özet
This study presents an enhanced hybrid TLBO--ANN model for daily photovoltaic (PV) power generation prediction. By combining the strong nonlinear modeling capacity of Artificial Neural Networks (ANN) with the robust optimization capability of the Teaching--Learning-Based Optimization (TLBO) algorithm, the proposed framework effectively improves prediction accuracy and generalization performance. The model was trained using real meteorological and power generation data and validated on a grid-connected PV power plant in Türkiye. Results indicate that the hybrid TLBO--ANN approach outperforms the conventional ANN by achieving 39.97% and 37.46% improvements on the test subset and overall dataset, respectively. The improved convergence behavior and avoidance of local minima by TLBO contribute to this enhanced accuracy. Overall, the proposed hybrid model provides a powerful and practical tool for reliable PV power forecasting, which can facilitate better grid integration, operational planning, and energy management in renewable energy systems.
Anahtar Kelimeler
grid integration | hybrid TLBO–ANN model | intelligent optimization | photovoltaic power forecasting | renewable energy systems
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 1
Scopus 1
Google Scholar 1
An Enhanced Hybrid TLBO--ANN Framework for Accurate Photovoltaic Power Prediction Under Varying Environmental Conditions

Paylaş

İletişim
  • Kırşehir Ahi Evran Üniversitesi Bağbaşı Yerleşkesi, 40100, KIRŞEHİR \ TÜRKİYE
  • unis@ahievran.edu.tr
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