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Signal processing for fault detection in photovoltaic arrays

Published on Mar 1, 2012 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
· DOI :10.1109/ICASSP.2012.6288220
Henry Braun6
Estimated H-index: 6
(ASU: Arizona State University),
S. T. Buddha3
Estimated H-index: 3
(ASU: Arizona State University)
+ 4 AuthorsT. Takehara2
Estimated H-index: 2
Abstract
Photovoltaics (PV) is an important and rapidly growing area of research. With the advent of power system monitoring and communication technology collectively known as the “smart grid,” an opportunity exists to apply signal processing techniques to monitoring and control of PV arrays. In this paper a monitoring system which provides real-time measurements of each PV module's voltage and current is considered. A fault detection algorithm formulated as a clustering problem and addressed using the robust minimum covariance determinant (MCD) estimator is described; its performance on simulated instances of arc and ground faults is evaluated. The algorithm is found to perform well on many types of faults commonly occurring in PV arrays.
  • References (9)
  • Citations (32)
References9
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