Estimation of wind energy potential using finite mixture distribution models

In this paper has been investigated an analysis of wind characteristics of four stations (Elazig, Elazig-Maden, Elazig-Keban, and Elazig-Agin) over a period of 8 years (1998–2005). The probabilistic distributions of wind speed are a critical piece of information needed in the assessment of wind energy potential, and have been conventionally described by various empirical correlations. Among the empirical correlations, there are the Weibull distribution and the Maximum Entropy Principle. These wind speed distributions can not accurately represent all wind regimes observed in that region. However, this study represents a theoretical approach of wind speed frequency distributions observed in that region through applications of a Singly Truncated from below Normal Weibull mixture distribution and a two component mixture Weibull distribution and offer less relative errors in determining the annual mean wind power density. The parameters of the distributions are estimated using the least squares method and Statistica software. The suitability of the distributions is judged from the probability plot correlation coefficient plot R2, RMSE and χ2. Based on the results obtained, we conclude that the two mixture distributions proposed here provide very flexible models for wind speed studies.