A Probabilistic Model of Extrapolated Wind Speed Data for Wind Energy Prediction at Alangarapeta, Anantapur District, Andhra Pradesh, India

Abstract

The wind speed distribution determines the performance of wind energy systems for a given location and time quite well. When the wind speed probability distribution is known, the wind energy distribution can easily be obtained. Therefore, the probability distribution of wind speed is a very important piece of information needed in the assessment of wind energy potential. A proper analysis of statistical wind data is a very important step when performing a wind resource assessment campaign which supports a wind energy feasibility initiative. Wind speed data are available in most cases for only 10m and 25m height above the ground level using anemometer. Since wind speed normally increases with height above the ground, some means of estimating the wind speed at heights other than measurement height is needed. In this paper, a probabilistic model is fitted to the wind speed data recorded at Alangarapeta station at Anantapur District in state of Andhra Pradesh. Wind speeds are then extrapolated to height of 50m using power law equation with an exponent of 0.14. Data were analyzed using MINITAB statistical software to show the variability of wind speeds with time and height, and to determine the underlying probability model of the extrapolated wind speed data. The results show that wind speeds at Alangarapeta station vary cyclically over time; and they conform to the Weibull probability distribution to predict the wind energy.