Fault isolation based in Structural Analysis and EWMA of the set DFIG/Back-to-Back converter of a Wind Energy Conversion System

J. Mina, R. Pérez
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Abstract

This paper proposes a fault isolation system for the set Double Feed Induction Generator (DFIG)/Back-to-Back converter of an off-grid Wind Energy Conversion System (WECS). An a priori task is the fault diagnosability analysis of the system by means of Structural Analysis (SA), from which the redundant information is extracted - analytical redundant relations (ARR's). The residual generators for the isolation system make use of the ARR's and the explicit analytical equations of the system. Given that the system is based on a power electronic converter, the input signals to the residual generators are switched signals, which yield a bad performance of the ARR's. In order to enhance the performance and sensitivity of residuals under faulty conditions, an exponentially weighted moving average (EWMA) strategy is used on the raw residuals obtained from the ARR's. 26 faults are considered in the diagnosability analysis same which are tested on a WECS simulator created on Simulink/MatLab.
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基于结构分析和EWMA的风力发电机组DFIG/背靠背变流器故障隔离
本文提出了一种离网风电转换系统(WECS)双馈感应发电机(DFIG)/背靠背变流器的故障隔离系统。先验任务是利用结构分析(SA)对系统进行故障诊断分析,从中提取冗余信息——解析冗余关系(ARR)。隔离系统的剩余发生器利用了ARR和系统的显式解析方程。由于系统基于电力电子变换器,剩余发电机的输入信号为开关信号,导致ARR的性能较差。为了提高残差在故障条件下的性能和灵敏度,对ARR的原始残差采用指数加权移动平均(EWMA)策略。在Simulink/MatLab上建立的wcs仿真器上对26个故障进行了可诊断性分析。
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