Forecasting electrical power generated from solar pv systems by innovative DL principles
[ X ]
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This master’s research is implemented to examine and explore the significant contributions
and substantial relevances of novel DL algorithms in making predictions with considerable
effectiveness, accuracy, reliability, and trustworthiness. The work addressed a case study
comprising two solar PV systems in India. Datasets were defined, and two performance
evaluation approaches were used to examine the accuracy of the three DL models: LSTM,
CNN, and LSTM-CNN. The numerical simulations and mathematical analysis in this work
revealed that the LSTM, CNN, and hybrid LSTM-CNN models offered higher accuracy in
forecasting clean electrical power produced from the two solar PV systems. Nonetheless,
the accuracy of the hybrid scheme provided the most significant accuracy rates compared
with the first two algorithms. The research findings also indicated that the values of MAE
linked to the training of the three algorithms were more considerable than the MAE amounts
related to the testing process across all the epoch ranges. Besides, it was found that the MAE
connected with training for the three algorithms started at a maximum value. Then, it
declines until it reaches a lower value steadily for a more extended epoch range. However,
the MAE value after declination was still larger than the MAE rates of the testing process.
Further, the numerical outputs confirmed that the RMSE value of the training and testing
procedures for the three algorithms had similar behavior to the MAE in forecasting the clean
electrical power of the two solar PV systems.
Açıklama
Anahtar Kelimeler
Solar Energy, Electricity Production, Forecasting, Accuracy, Performance, Intelligent Algorithms, DL Arinciples
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Abbas, A. S. (2023). Forecasting electrical power generated from solar pv systems by innovative DL principles. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.
