Enhancing Wind Power Estimation for Dakhla, Morocco: A Comparative Exploration of Four Numerical Methods Leveraging the Weibull Distribution

Abstract

during the purpose for estimating wind energy potential as well as effectively utilizing wind power, wind speed modelling is crucial. The accuracy of the wind speed evaluation on an effectiveness of a probability distribution function (PDF) Applied to characterize a frequency distribution for recorded wind speed works. In this work, four methods: the empirical method of Justus (EMJ), the empirical method of Lysen (EML), wind energy Pattern Factor method (WEPFM), or alternative maximum likelihood method (AMLM), are employed for estimate Weibull parameters (Shape and Scale). A values were calculated during one year to another of wind speed data gathered in Dakhla, Morocco. The calculation for these parameters are carried out using matlab software. To compare the methods, and assess the precision of their parameter estimates, four different analytical approaches are examined; Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Chi-square (X <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), or Correlation Coefficient (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). The outcome show which AMLM method is incredibly adept at computing Weibull parameters.