Short-circuit Current-based Parametrically Identification for Doubly Fed Induction Generator
Yong Zhu,
Yongwei Tao,
Zequn Li
Abstract:Recently, deep learning has provided a new opportunity to achieve high precision and real-time parameter identification of the doubly-fed induction generator (DFIG) in the event of short-circuit fault. However, deep learning algorithms based on data training are facing the challenge of relying on a large amount of training data and poor generalization performance. In order to improve these shortcomings, we embed the forward calculation model of three-phase short-circuit current (SCC) into the neural network, a… Show more
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