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PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING

Abstract: 

We apply convolutional neural networks (CNN) for monitoring the
operation of photovoltaic panels. In particular, we predict the daily
electrical power curve of a photovoltaic panel based on the power
curves of neighboring panels. An exceptionally large deviation between
predicted and actual (observed) power curve indicates a malfunctioning
panel. The problem is challenging because the power
curve depends on many factors such as weather conditions and the
surrounding objects causing shadows with a regular time pattern. We
demonstrate, by means of numerical experiments, that the proposed
method is able to accurately detect malfunctioning panels. Moreover,
the proposed approach outperforms existing approaches based
on simple interpolation filters.

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Paper Details

Authors:
Submitted On:
1 June 2018 - 8:12am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Timo Huuhtanen
Paper Code:
1079
Document Year:
2018
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Document Files

huuhtanen01.pdf

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[1] , "PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3228. Accessed: Dec. 10, 2018.
@article{3228-18,
url = {http://sigport.org/3228},
author = { },
publisher = {IEEE SigPort},
title = {PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING},
year = {2018} }
TY - EJOUR
T1 - PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3228
ER -
. (2018). PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING. IEEE SigPort. http://sigport.org/3228
, 2018. PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING. Available at: http://sigport.org/3228.
. (2018). "PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING." Web.
1. . PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3228