| Yazarlar (2) |
Öğr. Gör. Şaban FINDIK
Kırşehir Ahi Evran Üniversitesi, Türkiye |
Dr. Öğr. Üyesi Salih ERMİŞ
Kırşehir Ahi Evran Üniversitesi, Türkiye |
| Özet |
| The rapid increase in global energy demand, driven by industrialization, population growth, and technological advances, has emphasized the importance of the transition to renewable energy sources. In addition, renewable energy, especially photovoltaic (PV) systems, has become a widespread energy source in agricultural applications to meet the energy needs in agricultural irrigation. However, the efficiency of PV systems varies depending on meteorological and environmental factors such as solar radiation and temperature. Therefore, predictability of energy production is a critical requirement for the effective operation of irrigation systems. In this study, the Ant Colony Optimization (ACO) algorithm is implemented to estimate the power output of PV systems using historical solar radiation, temperature, and actual power production data. Inspired by the foraging behavior of ants, the ACO algorithm optimizes the estimation process by iteratively refining the solutions based on pheromone trails and adaptive learning. The proposed method is evaluated using a case study on a solar power plant located in the Central Anatolian region of Türkiye. The accuracy of the model is evaluated by comparing the predicted values with the actual measurements at various time periods including hourly, daily, weekly, monthly and seasonal forecasts. The results show that the ACO based forecast model provides high accuracy in predicting the PV power output, with the Mean Absolute Percentage Error (MAPE) values improving as the forecast period increases. The findings of this study suggest that ACO is a robust and efficient optimization technique to improve PV … |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayınlanan tam makale |
| Dergi Adı | Türk Tarım ve Doğa Bilimleri Dergisi |
| Dergi Tarandığı Indeksler | TR |
| Makale Dili | İngilizce |
| Basım Tarihi | 07-2025 |
| Cilt No | 12 |
| Sayı | 3 |
| Sayfalar | 653 / 665 |
| Doi Numarası | 10.30910/turkjans.1683035 |
| Makale Linki | https://doi.org/10.30910/turkjans.1683035 |
| Atıf Sayıları |
