Study on wind energy potential by eight numerical methods of Weibull distribution

In this study, eight different numerical methods have been investigated to identify more effective methods for efficiently determining the value of Weibull factors (k and c) to estimate wind energy potential. To achieve the goal, the study used nine statistical test tools including relative percentage of error, root mean square error, mean percentage of error, mean absolute percentage of error, chi-square error, and analysis of variance to precisely rank the methods. The method of moment, least square method, and empirical method were found to be better methods for calculating Weibull factors in this specific application. The statistical fittings of the measured and calculated wind speed data by Weibull functions are assessed and results are graphically represented to provide better understanding. The monthly variations of available power, energy density, energy intensity, etc. have been analyzed for the selected wind sites. This analysis used 10-min time series wind speed data obtained by the United Nations Development Programme (UNDP) wind project at four wind monitoring stations in Bangladesh. Further study is needed for long-term wind data analysis for a prospective windy site and a suitable design of wind turbine for that site. © 2017 Elsevier Inc. All rights reserved.