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. Among several types of detection algorithms considered, only the MCD shows high performance on both types of faults. / Dissertation/Thesis / M.S. Electrical Engineering 2012
| Identifer | oai:union.ndltd.org:asu.edu/item:14796 |
| Date | January 2012 |
| Contributors | Braun, Henry Carlton (Author), Tepedelenlioglu, Cihan (Advisor), Spanias, Andreas (Advisor), Turaga, Pavan (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 73 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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