A novel approach to Weibull distribution for the assessment of wind energy speed

The latest power sources trend is renewable energy. Numerous researchers, innovators, and technicians work diligently to exploit renewable power. The effectiveness of wind speed data is crucial when estimating wind energy production from a wind turbine. For evaluating wind possibilities, there are several studies on the four generally utilized wind speed distribution models. However, there isn't enough research to determine how sensitive these models are to the observed wind speed data quality. The current research aims to demonstrate wind speed data distribution using Weibull distribution. Researchers discover that the statistical data of the changes among consecutive points of the anticipated wind speed information may drastically deviate from the characteristics of the observed wind. Firstly, the variables of Weibull distribution are estimated using modified maximum likelihood (MML) methods, Energy Pattern Factor and method of moment (MOM). The suggested approach is based on an algorithm that compares the statistical characteristics of the produced and actual wind speeds to get a more precise estimation. Therefore, the findings show that using Weibull distribution to represent wind speed modelling is feasible, precise, and efficient.

Automated summary

The latest trend in power sources is towards renewable energy. Researchers, innovators, and technicians are working diligently to harness renewable power. This research focuses on the distribution of wind speed data using the Weibull distribution. The findings show that the statistical characteristics of anticipated wind speed data may deviate drastically from the observed wind, highlighting the need for more precise estimation methods.