Photovoltaic system parameter estimation using marine predators optimization algorithm based on multilayer perceptron
Yükleniyor...
Dosyalar
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Ltd.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Solar and wind based renewable energy sources are highly variable according to unstable energy sources due to variable meteorological conditions. Providing a stable DC bus voltage to the inverter’s input by eliminating voltage fluctuations in the generated electrical energy is the main concern of researchers and is highly sensitive in the integration of distributed energy sources. In this study, in order to provide stable and sustainable output voltage at the output of a DC/DC converter, parametric simulation studies are carried out according to different input voltage, duty ratio, and switching frequency values of a DC/DC power converter circuit in a system fed with a solar energy source. Using this dataset obtained from a solar energy source, a parameter estimation in the smart grid structure is studied using artificial hybrid prediction intelligence techniques. Grey wolf and marine predators optimization algorithms are integrated to the multilayer perceptron in the stage of developing the hybrid prediction models. Then, the accuracy of the prediction processes is tested and verified with the power electronics circuit software. Thus, a data analysis approach based on parametric simulation studies in smart grid structures is reported in order to give clear ideas to researchers before designing a prototype.
Açıklama
WOS:000905811100003
Anahtar Kelimeler
Hybrid Artificial Intelligence Techniques, Modeling Of Power Converters, Parameter Estimating, Power Electronics, Renewable Energy Sources, Smart Grid
Kaynak
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
Sayı
Künye
Çolak, M., Balcı, S. (2022). Photovoltaic system parameter estimation using marine predators optimization algorithm based on multilayer perceptron. Electric Power Components and Systems, doi:10.1080/15325008.2022.2146234
