Estimation of wind speed with artificial neural networks method for Isparta using meteorological measurement data

Year 2021, , 65 - 69, 30.06.2021

Fatih Gemici , Arzu Şencan Şahin

https://doi.org/10.31593/ijeat.895362

Cited By: 1

Abstract

Renewable energy sources are of great importance for our country. Wind energy is a renewable energy source. Today, wind energy is mostly used in electricity generation. The electrical energy to be produced from a wind turbine is directly related to the wind speed in that region.
In this study, the wind speed for Isparta between 1st of January 2019, and 31st of December 2019 has been estimated using an artificial neural network (ANN) depending on average air temperature (°C), air pressure (mb), relative humidity (%), solar radiation (W/m2). MATLAB programming language is used. RMSE (Root-Mean-Square Error) was found to be 6,946427364, and R2 value as 0.9479, cov coefficient of variation as 0.1609336. It has been observed that these values are at an acceptable level. Therefore, it has been seen that the artificial neural networks model can be used in wind speed estimation.

Keywords

Artificial neural network, Matlab, Wind speed, Prediction

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