Abstract
Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50 m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination ( R2), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density ( PD) was evaluated and it was found that Karachi has the highest wind speed and PD as 5.82 m/s and 162.69 W/m2, respectively, while Jiwani has the lowest wind speed and PD as 4.62 m/s and 76.76 W/m2, respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.
Highlights
In view of energy crisis, limited fossil fuel reserves, and deteriorated environmental impacts owing to the usage of fossil fuels (Sumair et al, 2020b; Baloch et al, 2016; Shoaib et al, 2017), harnessing of clean and renewable energy sources (RESs) is the need of hour
Following conclusions are drawn from this study: (i) At all locations, Weibull distribution has been found the most accurate and Rayleigh distribution as the least
(iii) Highest annual energy production (AEP) is at Karachi with Bonus 1300/62 while lowest is at Jiwani with Vestas V42
Summary
In view of energy crisis, limited fossil fuel reserves, and deteriorated environmental impacts owing to the usage of fossil fuels (Sumair et al, 2020b; Baloch et al, 2016; Shoaib et al, 2017), harnessing of clean and renewable energy sources (RESs) is the need of hour. In Pakistan, according to statistical studies conducted by Pakistan Meteorological Department (PMD), Alternative Energy Development Board (AEDB), and National Renewable Energy Laboratory, total theoretical installable wind power capacity is about 346 GW (Sumair et al, 2020a; Aized et al, 2019; Bhutto et al, 2013) To utilize this huge wind potential, site-specific wind resource assessment (WRA) is crucial. Along with WRA, an economic survey was performed to find the economic feasibility of installing wind turbines at that particular location From this analysis, the probable cost per kW h of electrical energy produced was found as US$0.0262. Significance of this work is twofold: first, it compares three probability distributions, i.e. two-parameter Weibull distribution, Rayleigh distribution, and lognormal distribution to model the wind data at all locations, and second it explores the wind potential of coastal belt of Pakistan using the best distribution found followed by economic feasibility analysis of wind energy harvesting
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