ESTIMATION OF WIND ENERGY PRODUCTION BY ARTIFICIAL NEURAL NETWORKS AND ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM
Keywords:
Artificial Neural Networks, Wind Energy, Estimation of Production, ModelingAbstract
Wind power provides a clean and feasible solution to generate electricity. The development of wind power applications requires a deep analysis of wind profiles and an accurate prediction of wind energy at a study site. This study estimated generation of wind energy as a sort of renewable energy. The geological and meteorological data of a wind power plant were taken into account to estimate the production data (RES) in Adıyaman. To conduct this estimation, the feedforward backpropagation artificial neural network (ANN) and Adaptive Network Based Fuzzy Inference System (ANFIS), and were used because of its successful prediction of linear-nonlinear models, as one of the applications of artificial intelligence. In the study, it was observed that the estimated production value of energy production (MWh) was rather close to actual values of energy production. In future studies on prediction, artificial intelligence applications can be employed successfully as a substitute of traditional methods.
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