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Eliciting information regarding available energy in the wind resource is intricately linked to the viability of a wind power project. The energy output of wind power plant is affected primarily by the wind speed characteristics. Probability distributions have proved to be useful for stochastic modeling of the wind resource and power potential estimation. This work fits ten most popular wind speed marginal distributions and four mixture distributions to 80 m mast measured 10-min averaged wind speed data in Odisha, India. The yearly mean wind speed is found to be 5.95 m/s with a coefficient of variation of 52% whereas the highest monthly mean wind speed of 9.14 m/s occurs in May. It is found that only generalized extreme value distribution could fit the yearly wind speed whereas a number of marginal and mixture distributions are found suitable for modeling monthly and seasonal wind speeds. The best fitted Weibull shape and scale parameters are 2.00 and 6.72 m/s, respectively. The annual wind power density (WPD) of 247  W/m2  with a very high summer WPD of 414  W/m2  confirms the feasibility of commercial wind power development.

Probabilistic Modelling of 80 m Mast Measured Wind Resource: A case study