In recent years, studies on wind energy have accelerated, due to developments and incentives in renewable energy. Wind speed has a significant role in generating electricity through wind energy. Wind speed estimation poses an important issue in determining the electric potential to be generated and in bringing the wind plants into an interconnected system. In this study, the use of Adaptive Neuro Fuzzy Inference System (ANFIS) and three artificial neural networks, namely feedback Levenberg-Marquardt learning algorithm (BPLM) and Radial Basis Network (RBN) models, were used for wind speed estimation in the Siverek district of the province of Şanlıurfa in the Southeastern Anatolia region of Turkey. In this application, meteorological data, including temperature, humidity, pressure, and wind speed in Siverek district were received from Turkish General Directorate of Meteorology and simulated in the MATLAB program..............
Author Keywords:-
Artificial neural networks, Adaptive Neuro-Fuzzy Inference System, Backpropagation, Radial Basis Network, Wind speed estimates
e-ISSN: 2319-183X, p-ISSN: 2319-1821 Source Type: Journal
Original Language: English
Document Type: Article
Number of pages: 13
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