In this study, it was aimed to determine the most suitable model for predicting global solar radiation in the Lakes Region (Isparta, Burdur, Antalya). Through ATATEK-Solar software, a total of 15 models were tested, including 14 empirical models from the literature and a new artificial intelligence-supported model. Each model was analyzed with three different optimization algorithms (Nelder-Mead Simplex, Pattern Search, Simulated Annealing). In province-based evaluations, the Model 9 (RMSE: 0.1507, R²: 0.9990) for Isparta, and the Model 14 for Burdur and Antalya (RMSE: 0.1940, R²: 0.9992 and RMSE: 0.2218, R²: 0.9987, respectively) provided the most successful results. In regional analysis results, while the Model 5 (RMSE: 0.2626, R²: 0.9980) gave the lowest average error, the Model 13 (RMSE: 0.2649, R²: 0.9979, standard deviation: 0.0122) showed the highest consistency. These models were followed by the Model 6 (RMSE: 0.2646, R²: 0.9979, standard deviation: 0.0444). Although the Model 15 gave the best results in Burdur and Antalya, it had a high standard deviation value (0.2201) due to its low performance in Isparta. The characteristic features of the Lakes Region, including the presence of lake ecosystems, elevation differences, and the resulting microclimatic diversity, necessitate a regional approach in predicting global solar radiation. In this context, the Model 13 has been determined as the most suitable model that can be used throughout the region with its low error rate and high consistency. The obtained results can provide reliable predictions in evaluating the solar energy potential of the region and designing solar energy systems.
Primary Language | English |
---|---|
Subjects | Agricultural Energy Systems |
Journal Section | Research Articles |
Authors | |
Early Pub Date | December 26, 2024 |
Publication Date | December 28, 2024 |
Submission Date | November 17, 2024 |
Acceptance Date | December 18, 2024 |
Published in Issue | Year 2024 Volume: 8 Issue: 4 |
The International Journal of Agriculture, Environment and Food Sciences content is licensed under a Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 International License which permits third parties to share and adapt the content for non-commercial purposes by giving the appropriate credit to the original work. Authors retain the copyright of their published work in the International Journal of Agriculture, Environment and Food Sciences.
Web: dergipark.org.tr/jaefs E-mail: editor@jaefs.com WhatsApp: +90 850 309 59 27