Determining suitable region wind speed probability distribution using optimal score-radar map

Abstract

Determination of wind speed probability distribution is of considerable importance to the accurate wind energy assessment. This paper proposes an optimal score-radar map for determining the suitable region wind speed probability distribution from various candidate parametric distributions. Five typical fitting performance indices are calculated and transformed into standard scores. Optimal weight coefficients are obtained to consolidate the five standard scores into an integrated score, which minimizes the differences between multiple fitting performance indices. The optimal score-radar map consists of integrated scores visually presents the suitability of candidate parametric distribution to numerous wind farms, which enables easy, quick, and explicit determination of suitable candidate. The applicability, efficiency, and verification of the proposed map are demonstrated using ten years of collected wind speed data form sixty-six wind farms at North Dakota. The results show that the mixture Generalized Extreme Value-Weibull distribution has the minimum area of optimal score-radar map and presents satisfactory suitability to North Dakota. Also, such distribution accurately characterizes the mean value, standard deviation, and skewness of collected wind speed data. The wind energy of North Dakota is investigated using such distribution. An ideal wind farm and preferable wind turbine are found.