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arXiv · 0804.1422

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

Herman Bayem·Yannick Phulpin·Philippe Dessante·Julien Bect
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Abstract

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.

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Herman Bayem, Yannick Phulpin, Philippe Dessante, Julien Bect. 2008-04-13. Probabilistic computation of wind farm power generation based on wind turbine dynamic modeling. https://arxiv.org/abs/0804.1422

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