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Supervision and fault detection system for photovoltaic installations based on classification algorithms

Author
Castellà, M.; Kampouropoulos, K.; Urbano, E.; Romeral, L.
Type of activity
Presentation of work at congresses
Name of edition
18th International Conference on Renewable Energies and Power Quality
Date of publication
2020
Presentation's date
2020-09-03
Book of congress proceedings
Renewable Energy and Power Quality Journal (RE&PQJ), Vol. 18, June 2020
First page
375
Last page
379
DOI
10.24084/repqj18.337
Repository
http://hdl.handle.net/2117/329963 Open in new window
URL
http://www.icrepq.com/icrepq20/337-20-castella.pdf Open in new window
Abstract
This article presents a methodology for the supervision and fault detection on photovoltaic installation, through the information gathered by their SCADA system. The proposed methodology consists of the use of a multi-clustering approach to analyse and classify the operating behaviour of the photovoltaic installations, using information of their DC voltage, generated current (per string), as well as information related to the climatic conditions of the park (i.e. solar irradiance, temperature). ...
Citation
Castellà, M. [et al.]. Supervision and fault detection system for photovoltaic installations based on classification algorithms. A: International Conference on Renewable Energies and Power Quality. "Renewable Energy and Power Quality Journal (RE&PQJ), Vol. 18, June 2020". 2020, p. 375-379. ISBN 2172-038X. DOI 10.24084/repqj18.337.
Keywords
Decision tree learning, Fault detection, Photovoltaics, Predictive maintenance
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre

Participants