TY - GEN
T1 - An 18 kW solar array research facility for fault detection experiments
AU - Rao, Sunil
AU - Ramirez, David
AU - Braun, Henry
AU - Lee, Jongmin
AU - Tepedelenlioglu, Cihan
AU - Kyriakides, Elias
AU - Srinivasan, Devarajan
AU - Frye, Jeffrey
AU - Koizumi, Shinji
AU - Morimoto, Yoshitaka
AU - Spanias, Andreas
N1 - Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2016/6/20
Y1 - 2016/6/20
N2 - Monitoring utility-scale solar arrays was shown to minimize cost of maintenance and help optimize the performance of the array under various conditions. In this paper, we describe the design of an 18 kW experimental facility that consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. Research planned at this stage includes developing machine learning methods for fault detection. Preliminary simulation results on fault detection using machine learning are given in this paper.
AB - Monitoring utility-scale solar arrays was shown to minimize cost of maintenance and help optimize the performance of the array under various conditions. In this paper, we describe the design of an 18 kW experimental facility that consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. Research planned at this stage includes developing machine learning methods for fault detection. Preliminary simulation results on fault detection using machine learning are given in this paper.
KW - Machine learning
KW - Photovoltaics(PV)
KW - Solar Panel Monitoring
UR - http://www.scopus.com/inward/record.url?scp=84979277006&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979277006&partnerID=8YFLogxK
U2 - 10.1109/MELCON.2016.7495369
DO - 10.1109/MELCON.2016.7495369
M3 - Conference contribution
AN - SCOPUS:84979277006
T3 - Proceedings of the 18th Mediterranean Electrotechnical Conference: Intelligent and Efficient Technologies and Services for the Citizen, MELECON 2016
BT - Proceedings of the 18th Mediterranean Electrotechnical Conference
A2 - Mavromoustakis, Constandinos
A2 - Louca, Soulla
A2 - Pattichis, Constantinos S.
A2 - Georgiou, Julius
A2 - Michael, Despina
A2 - Paschalidou, A.
A2 - Kyriacou, Efthyvoulos
A2 - Vassiliou, Vasos
A2 - Panayiotou, Christos
A2 - Kyriakides, Elias
A2 - Ellinas, Georgios
A2 - Hadjichristofi, George
A2 - Loizou, C.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th Mediterranean Electrotechnical Conference, MELECON 2016
Y2 - 18 April 2016 through 20 April 2016
ER -