Full metadata
Title
Signal processing and robust statistics for fault detection in photovoltaic arrays
Description
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.
Date Created
2012
Contributors
- Braun, Henry (Author)
- Tepedelenlioğlu, Cihan (Thesis advisor)
- Spanias, Andreas (Thesis advisor)
- Turaga, Pavan (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
ix, 63 p. : ill. (some col.)
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.14796
Statement of Responsibility
by Henry Braun
Description Source
Viewed on March 8, 2013
Level of coding
full
Note
Partial requirement for: M.S., Arizona State University, 2012
Note type
thesis
Includes bibliographical references (p. 43-46)
Note type
bibliography
Field of study: Electrical engineering
System Created
- 2012-08-24 06:22:39
System Modified
- 2021-08-30 01:47:16
- 2 years 7 months ago
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