Geo-Statistical Estimation and Temporal Distribution of Wind Speed Data of Karachi Airport

Abstract

Karachi city is a coastal city near the Arabian sea. Due to its location, wind speed may provide a sustainable small scale wind energy system as well as reduction in power shortage in the city. In this study, wind speed data of Karachi Airport station at 10m height is used to estimate wind speed in the surrounding area with reference to measured wind speed data of the station. This estimated wind speed will then be helpful to assess small scale wind power generation at the unsampled locations. Geo-Statics tool in ArcGIS version 10.1 software was utilised to estimate measured wind speed using different interpolation methods. Descriptive statistics were used to analyse and compare measured and estimated wind speed. The analysis summarises the effectiveness of the estimated wind speed. Time series variations of the wind speed data was also analysed. Temporal mapping showing seasonal variations of the wind speed. The descriptive statistics illustrated a high value of correlation coefficient ‘r’, coefficient of determination R2 which is 99.8% for Ordinary and Universal kriging interpolation methods, while it was calculated 99.6% for Simple kriging. A slightly higher coefficient of variation resulted in Ordinary and Universal kriging methods than the Simple kriging method. The results indicated that all three kriging methods performed better and are more effective to estimate wind speed and wind power in the surrounding area and for Temporal display.