Özet:

The interest in renewable energy sources is continuing to meet increasing energy needs and to solve environmental problems, with technological development work and economic investments. A variety of methods are used in the identification and prediction of sustainable and renewable energy sources. The potential calculation of the wind energy, a renewable energy, and the characterization of the wind is exploited by the possibility distribution functions. In low-speed areas, the weakness of compatibility with the real wind speed distribution of models that are found by obtaining parameters in wind characterization by classic methods is a known situation. In this study, the Weibull Probability Distribution Function (Wodf) in wind speed modeling, the Yousafzai Algorithm (YES) was proposed to predict the distribution parameters, in order to remove the weakness of compatibility in the speed distribution of the classic methods. The performance of the recommended method is evaluated by comparing the classic methods with the moment method (MY) and the smallest square method (EKKY). To evaluate the performance of this parameter forecast methods, the determination ratio (R2) and the error square average (HKOK) were used. In the study, data from 6 measurement stations were used. The results show that in all selected stations, the YA method provides the best performance according to the determination ratio (R2) measurement, while the HKOK measurement provides the best performance in 2 stations. Also, the YA method has been shown to give results closer to reality in all stations according to the LSM method.

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