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Assessment of wind energy potential using wind energy conversion system

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Abstract Wind energy, as a renewable resource, is the most rapidly growing source that produces electrical energy using wind turbines. Such a wind energy conversion system is both economical and… Click to show full abstract

Abstract Wind energy, as a renewable resource, is the most rapidly growing source that produces electrical energy using wind turbines. Such a wind energy conversion system is both economical and is environmental friendly. It requires understanding of wind conditions at the site under study. With this intent, wind characteristics of Jhampir (district Thatta Sindh, Pakistan) are investigated and wind energy potential is determined. The study is conducted using 10-min averaged wind speed data obtained from Alternate Energy Development Board of Pakistan for a period of three years (2007–2010). Monthly, seasonal, and yearly analysis is performed by fitting measured wind speed data to a Weibull distribution function. Weibull shape and scale parameters are determined numerically using Maximum Likelihood Method, Modified Maximum Likelihood Method, and Energy Pattern Factor Methods. The suitability of the fit is assessed using goodness-of-fit tests, such as, Root Mean Square Error, Coefficient of Determination (R2), and Chi-Square (χ2) tests. In all three data analysis periods, RMSE values varied between 10−2 and 10−4. Similarly, R2 values varied between 0.989 and 0.996 and χ2-test between 10−4 and 10−8. For entire data set, all the tests showed better performance of Maximum Likelihood and Modified Maximum Likelihood Methods compared to Energy Pattern Factor. In case of monthly analysis, Maximum Likelihood Method performed better compared to Modified Maximum Likelihood Method and Energy Pattern Factor according to root mean square error and χ2 tests results. Seasonal performance of all the methods is found to be similar with marginal superiority of MLM over other methods. A very good agreement is observed between standard deviation values for measured wind speed data distribution and fitted Weibull distribution using Maximum Likelihood Method estimator. Additionally, to understand the optimum directional efficiency, directional wind power densities are calculated. Finally, a wind turbine is used to the seasonal and yearly wind speed data to determine the actual wind energy potential of the site. Extracted wind energy values for four seasons are found to be 1691, 2851, 4572, and 916 kWh with an annual yield of 10054 kWh. Wind energy values obtained for different periods and directions suggest that Jhampir is a suitable site for developing the wind power plant.

Keywords: maximum likelihood; wind energy; energy potential; energy

Journal Title: Journal of Cleaner Production
Year Published: 2019

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