A New Artificial Neural Network Based Power Estimation Study for Wind Energy Systems

Year 2025, Volume: 17 Issue: 3, 567 - 576, 30.11.2025

Bahtiyar Taşdemir , Mustafa Yaz

https://doi.org/10.29137/ijerad.1672778

Abstract

Today, the demand for electrical energy is constantly increasing, primarily due to the advances in the industrial sector. This increase in demand has made wind energy a prominent option in the search for alternative energy sources due to its low investment costs and environmental friendliness. However, accurate forecasting methods are needed due to the variability of wind energy production affected by meteorological data. Including additional parameters besides the existing meteorological data could help improve the accuracy of these forecasts. This study explores the impact of the particulate matter (PM10) parameter on wind energy prediction through the employment of an artificial neural network (ANN) model. The comparison of prediction results based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) demonstrates that, when it comes to the daily wind power prediction of the PM10 parameter, the prediction model based on the artificial neural network (ANN) makes a significant contribution.

Keywords

Artificial neural network , forecasting , optimization , wind power generation

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