| dc.creator | McConnell, Stephen C. | |
| dc.date.accessioned | 2017-10-10T20:25:30Z | |
| dc.date.available | 2017-10-10T20:25:30Z | |
| dc.date.created | 2014-05 | |
| dc.date.issued | 2013-12-02 | |
| dc.date.submitted | May 2014 | |
| dc.identifier.uri | https://hdl.handle.net/1969.1/164421 | |
| dc.description.abstract | Electric arcs cause fires. The ability to detect an electric arc successfully, reliably, and quickly enables mitigation of arc-induced fires before they start. Within photovoltaic systems, in particular, the detection of an arc poses a significant engineering challenge. To date, arc detecting technologies frequently encounter trouble distinguishing between actual arc-fault scenarios and electrical noise from opening contactors, or power electronics such as the solar inverter or DC/DC optimizer. This paper seeks to investigate the efficacy of a new method for arc-fault detection. | en |
| dc.format.mimetype | application/pdf | |
| dc.subject | photovoltaic, arc-fault, detection, wavelet | en |
| dc.title | Photovoltaic Arc-Fault Detection | en |
| dc.type | Thesis | en |
| thesis.degree.department | Electrical and Computer Engineering | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Undergraduate Research Scholars Program | en |
| dc.contributor.committeeMember | Balog, Robert S | |
| dc.type.material | text | en |
| dc.date.updated | 2017-10-10T20:25:30Z | |
