Assessment of wind energy potential using wind energy conversion system. (10th April 2019)

• Record Type: Journal Article
• Authors: Shoaib, Muhammad; Siddiqui, Imran; Rehman, Shafiqur; Khan, Shamim; Alhems, Luai M.
• Is Part Of: Journal of cleaner production. Volume 216(2019)
• Page Start: 346
• Page End: 360
• Publication Date: 2019-04-10
• Subjects: Jhampir -- Weibull function -- Wind power density -- Wind turbine -- Wind energy; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2019.01.128
• Languages: English
• ISSNs: 0959-6526

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 ( R 2 ), and Chi-Square (χ 2 ) tests. In all three data analysis periods, RMSE values varied between 10 −2 and 10 −4 . Similarly, R 2 values varied between 0.989 and 0.996 and χ 2 -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 χ 2 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. Graphical abstract: Image 1022610 Highlights: Weibull function is used to analyze wind speed data. Suitability is assessed using well known methods RMSE, R 2, and goodness-of-fit. Directional power densities are calculated to find optimum directional efficiency. Annual yield of 10054.27 kWh may be realized from a 2500 kW rated wind turbine. The site under investigation is found to be suitable for wind farm development.