Journal article Open Access

Wind Resource Assessment using Machine Learning Algorithm

Stanly Abraham S,; Meenal R,; Abishekkevin K,; Pravina M,; Belsha Jackline Princess J

Sponsor(s)
Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)

The wind speed prediction is very important for wind resource assessment, renewable energy integration in to the electricity grid, electricity marketing and so on. Because of the arbitrary fluctuation characteristics of wind, the prediction results may change quickly. This enhances the significance of the accurate wind speed prediction The objective of this paper is to predict the wind speed for Tamil Nadu cities using machine learning algorithm. There are three broad categories of wind forecasting models namely physical model, statistical and computational models and hybrid models. Artificial Neural Network is the most commonly used method for wind speed prediction. Recently machine learning and deep learning algorithms are widely used for forecasting applications. In this work wind speed is predicted for Tamil Nadu cities using decision tree regression algorithm. The Machine Learning (ML) model is trained using measured wind speed data for six cities of India collected from India Meteorological Department (IMD), Pune. The ML model based on decision tree regression algorithm is good in prediction with better performance metrics of MSE in the range of 0.3 to 1.2 m/s and R2 =0.87.

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