Probabilistic computation of wind farm power generation based on wind turbine dynamic modeling

Herman Bayem (1) , Yannick Phulpin (1) , Philippe Dessante (1) , Julien Bect (2)

1 SUPELEC-Campus Gif
2 E3S - Supélec Sciences des Systèmes

This paper addresses the problem of predicting a wind farm's power generation when no or few statistical data is available. The study is based on a time-series wind speed model and on a simple dynamic model of a DFIG wind turbine including cut-off and cut-in behaviours. The wind turbine is modeled as a stochastic hybrid system with three operation modes. Numerical results, obtained using Monte-Carlo simulations, provide the annual distribution of a wind farm's active power generation. For different numbers of wind turbines, we compare the numerical results obtained using the dynamic model with those obtained considering the wind turbine's steady-state power curve. Simulations show that the wind turbine's dynamics do not need to be considered for analyzing the annual distribution of a wind farm generation.

Mots clés: wind farm; stochastic hybrid system; cut-off behaviour

Domaines: Energie électrique; Applications [stat.AP]

Herman Bayem, Yannick Phulpin, Philippe Dessante, Julien Bect. Probabilistic computation of wind farm power generation based on wind turbine dynamic modeling. PMAPS 2008, May 2008, Puerto Rico. pp.N.A. ⟨hal-00215958v1⟩