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Probabilistic Wind Farms Generation Model for Reliability Studies applied to Brazilian Sites Carmen Borges 1 , Andrea Leite 2 , Djalma Falcão 1 1 Federal University of Rio de Janeiro, 2 ELETROBRÁS - Brazilian Electrical Company This paper presents a computer model for the probabilistic representation of wind farms generation for reliability studies, which can provide an annual estimation of energy production and calculate several performance indices. The model combines the stochastic characteristics of wind speed with the operational information of the turbines, such as the failure and repair rates, representing the wind farm by a Markov process. The simulations are made with real time series of wind speed of several Brazilian regions and actual turbine models. The influence of some wind farm and installation site characteristics on the results are evaluated, such as the wind speed statistical clustering technique, the number and type of the turbines and the failure and repair rates. The results obtained reproduce successfully the behavior of the components considered in the model. 1-4244-1298-6/07/$25.00 ©2007 IEEE.

[IEEE 2007 IEEE Power Engineering Society General Meeting - Tampa, FL, USA (2007.06.24-2007.06.28)] 2007 IEEE Power Engineering Society General Meeting - Probabilistic Wind Farms Generation

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Probabilistic Wind Farms Generation Model for Reliability Studies applied to Brazilian Sites Carmen Borges1, Andrea Leite2, Djalma Falcão1 1Federal University of Rio de Janeiro, 2ELETROBRÁS - Brazilian Electrical Company This paper presents a computer model for the probabilistic representation of wind farms generation for reliability studies, which can provide an annual estimation of energy production and calculate several performance indices. The model combines the stochastic characteristics of wind speed with the operational information of the turbines, such as the failure and repair rates, representing the wind farm by a Markov process. The simulations are made with real time series of wind speed of several Brazilian regions and actual turbine models. The influence of some wind farm and installation site characteristics on the results are evaluated, such as the wind speed statistical clustering technique, the number and type of the turbines and the failure and repair rates. The results obtained reproduce successfully the behavior of the components considered in the model.

1-4244-1298-6/07/$25.00 ©2007 IEEE.