Adaptive transient overvoltage control strategy for wind farm based on data-driven method

Abstract

To achieve the transient overvoltage suppression of doubly fed induction generator (DFIG) terminals and the point of common coupling (PCC) in the wind farm (WF), an adaptive overvoltage control strategy based on data-driven approach is proposed. Firstly, the PCC reactive power demand and DFIG overvoltage threshold are derived, respectively. Secondly, three regression models are developed through surface fitting to determine three variables: the maximum overvoltage of each DFIG, the PCC maximum overvoltage, and the reactive power demand of each DFIG. Subsequently, the K-means clustering method is adopted to group all DFIGs, and then the reactive power requirement of the PCC is proportionally distributed to each group of DFIGs. Lastly, a coordinated control strategy of DFIGs and static var generator (SVG) is designed based on the values of three regression models, which can adaptively adjust the reactive power absorbed by each DFIG and SVG. In particular, the de-load control is adopted to enlarge the maximum reactive power capacity of DFIG. The simulation results show that the proposed control strategy can timely and effectively restore the transient overvoltage of the wind farm to the normal range during the gird failure, ensuring the stable operation of the wind farm.