| Yazarlar (3) |
Dr. Öğr. Üyesi Oğuz TAŞDEMİR
Kırşehir Ahi Evran Üniversitesi, Türkiye |
Mehmet Yeşilbudak
Nevşehir Hacı Bektaş Veli Üniversitesi, Türkiye |
|
Erdal Irmak
Gazi Üniversitesi, Türkiye |
| Özet |
| The escalating global energy demands and the environmental repercussions of fossil fuel utilization have given rise to a marked increase in the level of interest in renewable energy sources. Solar energy, in particular, is distinguished by its abundance and minimal environmental impact. This study sets out to compare three distinct hybrid models that are designed to enhance the forecasting accuracy of daily photovoltaic power prediction: JAYA-ANN, GA-ANN and PSO-ANN. The models were developed and tested using historical data on PV power output, including air temperature, PM10 levels, and solar irradiance. The study's findings indicated that the JAYA-ANN hybrid model exhibited superior performance, with a Mean Absolute Percentage Error (MAPE) of 7.38% and a Root Mean Squared Error (RMSE) of 681.71 kW for the test subset. The JAYA-ANN model demonstrated superior performance in comparison ... |
| Anahtar Kelimeler |
| Makale Türü |
Özgün Makale
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| Makale Alt Türü | SCOPUS dergilerinde yayınlanan tam makale |
| Dergi Adı | International Journal of Smart grid |
| Dergi ISSN | 2602-439X Scopus Dergi |
| Dergi Tarandığı Indeksler | SCOPUS |
| Makale Dili | İngilizce |
| Basım Tarihi | 12-2025 |
| Cilt No | 9 |
| Sayı | 4 |
| Sayfalar | 210 / 218 |
| DOI Numarası | 10.20508/ijsmartgrid.v9i4.550.g416 |
| Makale Linki | https://doi.org/10.20508/ijsmartgrid.v9i4.550.g416 |
| Atıf Sayıları |
