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Performance Evaluation of Six Methods for Estimating Weibull Distribution Parameters for Wind Energy: Applications to Three Sites in Morocco

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Wind power offers a clean and viable solution for generating electricity, but its effective utilization demands a thorough analysis of wind characteristics and precise wind energy forecasting at the study location. In this study, wind speed distributions are examined to calculate two Weibull parameters (shape and scale) using the Matlab software, which is frequently employed for modeling and offers accurate estimates of wind resources. These parameters are derived from a year of measured wind speed data collected in El Fnidek, Dakhla, and Essouira, Morocco. Six methods are presented for estimating the Weibull parameters: the Empirical Method of Justus (EMJ), the Empirical Method of Lysen (EML), Wind Energy Pattern Factor Method (WEPFM), the Graphical method (GRAPH), Alternative Maximum Likelihood Method (AMLM), and Method of Four Moments Mixture (MFMM). The comparison of these methods is based on four scoring criteria to assess goodness-of-fit, including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Chi-square (X2), and Correlation Coefficient (R2). The results indicate that the AMLM, GRAPH, and EMJ methods are the most successful in computing Weibull parameters. Additionally, the Annual Energy Production (AEP) and the economic analysis were calculated by using RETScreen software. The wind turbine models used in this study are the Sinovel 1500/77 and the Guodian Power UP77/1500, which have been considered for the production of 60 MW of electric power from the wind energy farm installed in three cities in Morocco: Dakhla, El Fnidek, and Essouira. According to the study results, the Guodian Power UP77/1500 has higher annual production with lower installation costs, making it a more favorable option. The resource analysis highlights Dakhla as a location with good potential for wind farm deployment compared to other sites. The comprehensive assessment of wind data, Weibull parameters, and economic aspects contributes valuable insights to the field of wind energy forecasting and decision-making for renewable energy projects.
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Weibull Parameters; Wind Power; MATLAB Software; RETScreen Software; Sinovel 1500/77; Guodian Power UP77/1500; Annual Energy Production; Economic Analysis

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