Estimating Wind Farm Transformers Rating through Lifetime Characterization Based on Stochastic Modeling of Wind Power

Abstract

This paper deals with the problem of the optimal rating of mineral-oil-immersed transformers in large wind farms. The optimal rating is derived based on the probabilistic analyses of wind power generation through the Ornstein–Uhlenbeck stochastic process and on thermal model of the transformer through the integration of stochastic differential equations. These analyses allow the stochastic characterization of lifetime reduction of the transformer and then its optimal rating through a simple closed form. The numerical application highlights the effectiveness and easy applicability of the proposed methodology. The proposed methodology allows deriving the rating of transformers which better fits the specific peculiarities of wind power generation. Compared to the conventional approaches, the proposed method can better adapt the transformer size to the intermittence and variability of the power generated by wind farms, thus overcoming the often-recognized reduced lifetime.

Research of Emergency Modes of Wind Power Plants Using Computer Simulation

“…The most efficient operation of wind farms requires knowledge about the performance of a wind farm and the turbine behavior on the grid, especially its power generation and voltage levels under different wind conditions. Factors necessary for the study of wind farm design are: selection of the power plant construction site, development of the power output scheme, selection of the generator type and turbines, and the study of the wind farm impact on emergency modes in the electrical network [12,13,[16][17][18][19][20][21][22][23]. As mentioned in [17], the configuration of a wind farm location largely affects the wind farm power output.…”