Wind Speed Dataset for Deep Learning Applications
Description
The data used in this study were obtained from the India NREL Wind Speed Dataset provided through the National Renewable Energy Laboratory (NREL). The dataset was developed to provide meteorological conditions for applications of wind energy. It has a temporal resolution of 5 min and a spatial resolution of 3 km, with the year 2014. The India Wind Dataset contains simulated wind speed, wind direction, temperature, and atmospheric pressure parameters at multiple heights above ground level, including 40, 80, 100, and 120 m where available. For the current study, the extracted dataset contains the variables height, air pressure, wind direction, temperature, and wind speed. The wind-speed variable, expressed in m/s, is used as the primary, while height, atmospheric pressure, wind direction, and temperature are considered explanatory meteorological variables. The original dataset contains 315,362 wind-speed observations. The dataset is particularly suitable for this study because its 5-min temporal resolution provides a high-resolution representation of wind-speed variability. The availability of meteorological variables together with wind speed also enables the investigation of data-driven and signal-decomposition-based approaches for wind-speed prediction.