Wind Potential Assessment Analysis of Jhampir, District Thatta Sindh, Pakistan

Aftab Ahmad; Fareed Husssain Mangi; Yasir Fazlani; Athar Chachar; Kashif Khan

doi:10.22581/muet1982.1903.04

Aftab Ahmad Department of Energy System Engineering, Sukkur IBA University, Sukkur, Pakistan.
Fareed Husssain Mangi Department of Energy System Engineering, Sukkur IBA University, Sukkur, Pakistan
Yasir Fazlani Department of Energy System Engineering, Sukkur IBA University, Sukkur, Pakistan
Athar Chachar Department of Energy System Engineering, Sukkur IBA University, Sukkur, Pakistan.
Kashif Khan Institute of Environmental Engineering and Management, Mehran University of Engineering and Technology , Jamshoro, Pakistan.

DOI: https://doi.org/10.22581/muet1982.1903.04

Abstract

Wind potential analysis is analyzing how much wind energy is available in particular region. It is most important step because the economics of project depends on the site wind resources. Wind plant depends on the variation of long-term mean wind speed and other characteristics which vary from a distance to distance. This study discusses the wind speed characteristics and wind potential analysis using three years 2014-2016 wind data of Jhampir located in district Thatta, situated in the Southeast of Sindh province. The numerical Weibull distribution approach is used to estimate parameters. The correct estimation of wind parameters and class is essential before developing any wind project in the region. The data used in this study is measured at 80 m height. The region is classified as from class 1-7. The results show that monthly mean speed values lie between 4.79-10.96 m/s. The annual mean scale and shape parameters lie in the range of 7.42-7.59. The wind power density was found in a range of 303.31355.64. This study is related to the decision-making process on a significant wind project in Thatta or nearby region. The stable wind energy pattern is observed in the region for harnessing wind energy almost throughout the year. The Weibull probability density curves also indicate a trend of a boost in the chances of observing wind from 2014-2016.