AI Summary & Key Takeaways
AI InsightThe results show that the ML estimators obtained using GA presentsuperiority over MoM and the ML estimators obtained using NR.
📌 3 Key Takeaways
Abstract
Renewable energy has become a prominent subject for researchers since fossil fuelreserves have been decreasing and are not promising to meet the energy demandof the future. Wind takes an important place in renewable energy resources andthere is extensive research on wind speed modeling. Herein, one of the mostcommonly used distributions for wind speed modeling is the Weibull distributionwith its simplicity and flexibility. Maximum likelihood (ML) method is the mostfrequently used technique in Weibull parameter estimation. Iterative techniquessuch as Newton-Raphson (NR) use random initial values to obtain the MLestimators of the parameters of the Weibull distribution. Therefore, the success ofthe iterative techniques highly depends on the initial value selection. In order todeliver a solution to the initial value problem, genetic algorithm (GA) isconsidered to obtain the estimators of the model parameters. The ML estimatorsobtained using the GA and NR techniques are compared with the method ofmoments (MoM) estimators via Monte Carlo simulation and wind speedapplications. The results show that the ML estimators obtained using GA presentsuperiority over MoM and the ML estimators obtained using NR.