Sensor Fault-detection Algorithm on a AC/DC Converters for Microgrids based on Principal Component Analysis

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Resumen

The present academic research work proposes a method based on Principal Component Analysis (PCA) for the detection of failures in sensors related to local control of AC/ DC voltage converters in a micro-grid (MR) with the possibility of coupling to the net. In order to achieve the aforementioned, a simulation of a micro-grid is carried out with a variety of loads (linear and non-linear) and both conventional and renewable generators, as well as storage elements that together have DC and AC systems with their respective converters. The researchers propose two failure scenarios and a normal operating scenario that serves as a reference to carry out the analyzes. As a result of the, an algorithm has been implemented that, based on the main components of the mentioned cases, calculates differences between the spaces obtained from a total of 195 variables collected in all the bars of the system, in addition to the sensing for local control. The observations obtained are around 145000 value takes.

Idioma originalInglés
Número de artículo36
PublicaciónRevista Internacional de Metodos Numericos para Calculo y Diseno en Ingenieria
Volumen38
N.º4
DOI
EstadoPublicada - 2022

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