Parameter estimation of photovoltaic system using marine predators optimization algorithm-based multilayer perceptron
Yükleniyor...
Dosyalar
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Solar irradiation data is an essential input for solar-thermal and photovoltaic systems. In this case, the coherence parameter estimation is a fundamental level in solar energy applications. For this purpose, a PV system has been modeled by the parametric solver of ANSYS-Electronics software and a data set has been created for the output voltage value depending on different input variables. In this paper, marine predators' algorithm is integrated to the multilayer perceptron algorithm in order to estimate the parameter. In the estimation level, air temperature, thermal coefficient and diffuse horizontal solar radiation parameters are evaluated in 2-tupled and 3-tupled input systems. In addition, the accuracy of the hybrid forecasting model developed is also tested on the basis of the hyperbolic tangent, sinus and sigmoid activation functions employed in the multilayer perceptron algorithm. Estimation results show that marine predators-based multilayer perceptron model is appropriate to parameter estimation, efficiently.
Açıklama
Anahtar Kelimeler
Artificial Neural Network, Estimation, Metaheuristic Optimization, Parametric Dataset, Solar Energy
Kaynak
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Çolak, M., Balcı, S. (2022). Parameter estimation of photovoltaic system using marine predators optimization algorithm-based multilayer perceptron. Paper presented at the 11th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2022, 540-545. doi:10.1109/ICRERA55966.2022
