Evaluation of Probability Distribution Functions For Wind Speed Analysis: A Case Study of Addis Ababa

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Addis Ababa University


Selection of best fit probability distribution model to the wind data sets is very important for reducing uncertainties in the extreme wind speed modeling at a given site. This study presents extreme wind speed analyses by using two approaches: The Block Maxima and Peaks Over Threshold, and compare of the results of both methods for the data from Addis Ababa; Bole wind speed recording station. Wind data collected include wind speed and wind direction, recorded for 63 years (1954-2016) with three-hours’ time interval. Seven Two-parameter, five Three-parameter, four Four-parameter, and Five-parameter Wakeby distributions are fitted to the Block Maximum data series, and Generalized Pareto distribution is fitted to the Peaks Over Threshold series. Three parameter estimation techniques were considered for estimating parameters involved with these distributions namely, Maximum Likelihood, L-moments, and Methods of Moments. The best fit models to the data are selected by examining ProbabilityProbability Plots and four goodness-of-fit statistics: Root Mean Square Error, Coefficient of Determination, Kolmogorov-Smirnov, and Cramer-VonMises, at 95 percent confidence level. The L-Moments estimation method has performed better for calculating the parameters of most of the distributions while the Method of Moments is the preferred method for obtaining the parameters of the JohnsonSB and Kumaraswamy distributions. The results showed that the JohnsonSB distribution gives a best fit to the block maximum series. The Peaks Over Threshold method with 2 peaks per year gave better results than the Block Maximum method; as a result, Peaks Over Threshold method is recommended for design. Wind direction analysis along with a wind rose chart for the study area is also provided. Analysis showed that most of the winds come from the East and East-Southeast direction with the maximum magnitude of 3.60- 5.70 m/s. Finally, the selected distribution model is used for forecasting the extreme wind speeds for return periods of 5, 10, 20, 50 and 100 years.



Block Maximum, Extreme Wind Speed, Goodness-of-Fit, L-Moments, Maximum Likelihood, Peaks Over Threshold, Probability Distribution Model