DC-DC converter fault diagnostic in PV system

A. Adouni, Khawla Elmellah, D. Chariag, L. Sbita
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引用次数: 11

Abstract

The photovoltaic (PV) system productivity is a decisive factor. To achieve a high productivity, the system availability should be checked. So even under a faulty situation, the system should operate continuously. As a proposed solution, the fault tolerant control (FTC) is recommended. In advance of FTC strategy, the fault diagnosis should be achieved. This paper deals with the open circuit fault occurred in the DC-DC converter. The Artificial Neural Network (ANN) is used to estimate the current and the voltage feeding the resistive load. These signals are compared to the measured ones. So, the proposed approach allows generating different signals in order to detect and to isolate the open circuit fault. The signals are the residuals and the flags. The fault is successfully detected and isolated.
光伏系统DC-DC变换器故障诊断
光伏(PV)系统的生产率是一个决定性因素。为了实现高生产率,应该检查系统可用性。因此,即使在故障情况下,系统也应该持续运行。作为一种建议的解决方案,建议采用容错控制(FTC)。在实施FTC策略之前,必须实现故障诊断。本文研究了DC-DC变换器中出现的开路故障。采用人工神经网络(ANN)对馈送电阻性负载的电流和电压进行估计。将这些信号与测量到的信号进行比较。因此,该方法允许产生不同的信号,以检测和隔离开路故障。信号是残差和旗子。故障检测并隔离成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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