The Use of Markov Chain Model for Rating Location Based Turbine Performance

Abstract

It is shown how a 12-state Markov chain model can be used in rating turbine performance in a given location. A 1.8 MW wind turbine exposed to wind speed in San Angelo, USA is used for illustration. The model fits the data. As such, features of the model are used in providing indices for rating the performance of the turbine in this location. Probability distribution of the wind speed in this location is introduced into each of the traditional methods of computing average power output from the turbine power curve and expected extract-able power. The estimates obtained are 937 kW and 826 kW, respectively.