Monthly Reference Frequency Distributions of Hourly Relative Wind Speed Data from Burundian Stations

Abstract

In previous research works on one hand, terrain, meteorological and wind speed data from various Burundian sites have been processed in order to bring efficient tools for the planning and installation of wind energy conversion systems (WECSs) at those sites. On another hand, sunshine duration and global solar radiation data, respectively from different Burundian sites, have been used to implement monthly reference distributions of data at those sites for the next two dimensionless random variables: the daily relative sunshine duration and the daily clearness index. Those distributions were deemed to be important inputs in projects for setting solar energy conversion systems (SECSs) at the relevant sites. The present study comes out as a continuation of the afore-said works and it intends to further contribute to bringing useful help in projects for setting WECSs at selected Burundian localities. Using a 4-years period’s hourly wind speed, ν values from four Burundian stations as primary data, the specific objective of the study is three-fold. Firstly, to set up for each station frequency distributions, means and variances of the 12 monthly samples and the 48 sub-samples of hourly relative wind speed, v r (another dimensionless random variable) data extracted from the primary wind speed values. Secondly, to use a suitable statistical test in order to ascertain whether or not, for each station, monthly samples of relative wind speed data for which mean values, v ¯ r fall within a same interval with the width equal to 0.05, have also the same variance, originate from the same population and thus possess the same statistical distribution. Thirdly, to build such a distribution referred to as a monthly reference frequency distribution of relative wind speed data, for any of the identified mean relative wind speed ( v ¯ r ) intervals of interest and for each station. All the three objectives have been attained. Especially, the use of the one-way ANOVA conditions and the F-test has led to accept the null hypothesis for the following numbers of intervals of interest: 3 out of 3 for Bujumbura, 2 out of 3 for Gitega, 2 out of 2 for Kirundo, 4 out of 4 for Musasa, and thus 11 out of 12 for the four stations. With the view to building the monthly reference frequency distribution for each identified v ¯ r interval of interest, the v r data of the relevant samples have been put together in a group. Then, the absolute, relative and cumulative relative frequency distributions of those data, respectively, have been inferred, and curves of the two last kinds of distribution have been plotted. Altogether, the obtained 11 monthly reference frequency distributions of hourly v r data should be used as inputs into projects for setting WECSs at the relevant stations.