Assessment of wind power potential as a renewable energy source in Western Cape, South Africa

Abstract

The worldwide utilisation of renewable energy in electric power systems is growing rapidly due to concerns about the environment and the depletion of the sources of conventional power generation. The Weibull distribution is a widely used distribution, especially for modelling the random variable of the wind speed. In this respect, the authors present a comparative analysis of a number of methods used for estimating Weibull parameters. Results for a real – word database, are presented in a case study format. The techniques require historical Wind speed data, collected over a particular time interval, to establish the parameters of wind speed distribution for a specific location, namely Cape Town, South Africa. As can be observed, the scale and shape parameters, from the whole database and from seasonal values, have the best estimation in case of maximum likelihood (MLE). Thus, it can be summarised that the maximum likelihood (MLE) is the best method used to estimate the parameters for the two-parameter Weibull distributions taking into consideration the mean bias error (MBE) and the root mean squares error (RMSE) as measurements of comparison, while the maximum likelihood (MLE) method is the least accurate method.