Modeling predictive assessment of wind energy potential as a power generation sources at some selected locations in Pakistan

Abstract

The present paper aims to investigate the wind power potential at seven selected locations, namely, Gujranwala, Islamabad Capital Territory, Jhimpir, Kati Bandar, Khanewal, Multan and Sialkot in Pakistan. Wind speeds were collected over a period of 2005–2016 and measured at 10 m height. In this study, ten distribution functions were applied to analyze the wind speed characteristics of these selected locations and estimate the wind power density. The results showed that Kati Bandar has the highest annual wind speed of 4.04 m/s in comparison to other locations, while the lowest value of 1.33 m/s was obtained in Islamabad Capital Territory. During the investigation period, it is observed that the maximum power density of 258.75 W/m2 is occurred in July at Kati Bandar, while the lowest minimum wind power density of 1.68 W/m2 occurred in September at Islamabad at 10 m height. The analysis result of the wind power and energy density as functions of tower height shows that higher tower height will produce higher wind power and energy density. Therefore, it is concluded that the wind power density values in the locations (Gujranwala, Islamabad Capital Territory, Khanewal, Multan, and Sialkot) are substantial and can be utilized using small-scale wind turbines for generating electricity. Consequently, the performances of four small-scale wind turbines were evaluated. Based on the results, the Pitch wind/30 kW Grid wind turbine had the highest annual capacity factor of 56.366%, whereas, WS-12/8 kW wind turbine had a minimum at 15.416%. The Minimum and the Maximum annual electricity cost in the studied locations are 0.005 $/kW h and 0.032 $/kW h using Pitch wind/30 kW Grid and WS-12/8 kW, respectively.