4.6 Article

Determination of Optimal Parametric Distribution and Technical Evaluation of Wind Resource Characteristics for Wind Power Potential at Jhimpir, Pakistan

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 70118-70141

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3078511

Keywords

Wind power generation; Wind energy; Wind speed; Distribution functions; Renewable energy sources; Wind turbines; Capacity planning; Jhimpir Pakistan; parametric distribution; statistical analysis; Weibull distribution; wind power potential; wind speed and direction

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The research aimed to analyze wind characteristics and assess wind power potential in Jhimpir Sindh Pakistan by selecting the best fit probability distribution function. It found that Weibull and Rayleigh distributions closely represented the wind data in the region, with Weibull being the most suitable. Statistical tests were used to evaluate the accuracy of the selected distribution functions and results indicated the potential for wind power production in the studied site.
The objective of this research work is to analyze wind characteristics and to assess wind power potential by selecting the best fit probability distribution function of Jhimpir Sindh Pakistan. This type of detailed investigation helps wind power generation companies in selecting suitable wind turbine and provides information of wind characteristics of potential site. Eight probability distribution functions are tested on the wind speed data from January 2015 to July 2018. Frequency bins of Weibull and Rayleigh distribution with maximum probabilities of 0.1210 and 0.1143 are most closest representation of our data. In order to, quantitatively analysis which distribution function is best fitting the local wind regime, we have applied the coefficient-of-determination, Kolmogorov-Smirnov, Chi square, Cramer-von Mises, Anderson-Darling tests along with Akaike information and Bayesian information criterion. These statistical test are used to rank the empirical distribution functions in order to identify two distribution function better fitting the actual wind speed data. After selecting two best fitted distribution functions, we analyze wind power potential and compare the error of wind power density based on these distribution functions (Weibull and Rayleigh). The power densities reported varied from 73.67 to 648.73W/m(2). Results indicate that power densities of Weibull and Rayleigh for the candidate site are 84.67-698.65W/m(2) and 83.67-1021.4W/m(2), respectively. The highest error for Weibull and Rayleigh are 0.1850 and 0.5745, respectively. Whereas lowest error are 0.0178 and 0.0180, respectively. Complete analysis suggested that Weibull distribution function is the most suitable for Jhimpir Sindh Pakistan and the studied site is suitable for wind power production. In addition, comprehensive analysis of wind direction at the candidate site suggested that Eastern and Southeastern wind directions are predominant with 38.52% and 33.24% of the total time.

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