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Study on LVRT of DFIG Based on Fuzzy-Neural D-STATCOM
Xueqin ZHENG Xiaoxiong CHEN Tung-Chin PAN
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2017/12/01
Online ISSN: 1745-1337
Type of Manuscript: PAPER
Category: Systems and Control
fuzzy-neural D-STATCOM, asymmetrical grid fault, crowbar, LVRT,
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This paper aims to improve the ability of low voltage ride through (LVRT) of doubly-fed induction generation (DFIG) under the asymmetric grid fault. The traditional rotor of the Crowbar device requires a large reactive support during the period of protection, which causes large fluctuations to the reactive power of the output grid while cut in and off for Crowbar. This case would influence the quality and efficiency of entire power system. In order to solve the fluctuation of reactive power and the stability of the wind power system, this paper proposes the coordinated control of the fuzzy-neural D-STATCOM and the rotor of the Crowbar. The simulation results show that the system has the performance of the rotor current with faster decay and faster dynamic response, high steady-state characteristic during the grid fault, which improve the ability of LVRT of DFIG.