Wind Energy Production Estimation with ANN and ANFIS

Abstract

Electricity is a type of energy that cannot be stored and consumed as soon as it is generated. The supply-demand balance of electricity is constantly maintained by systems. Furthermore, elaborate plans are required to maintain this balance. It is possible to achieve this balance by coordinating production, transmission, and consumption moment to moment. For this reason, estimating electricity production is of great importance. In this study, the production of wind energy, which is a type of renewable energy, was estimated. The production data was estimated by considering the meteorological and geological data of a wind power plant (Renewable Energy Systems (RES) in the city of Adiyaman. In order to make the production estimation, feed forward back propagation artificial neural network (ANN) was used due to its success in predicting linear nonlinear models, which are artificial intelligence applications and Adaptive Network Based Fuzzy Inference System (ANFIS). It has been observed that the estimated production power values (MWh) are very close to the actual production power values. Estimates made by ANN and ANFIS and compared. In the future forecasting studies, it was shown that ANN and ANFIS can be applied successfully as an alternative to conventional methods.