Title
Distributed Bayesian Estimation With Low-Rank Data: Application To Solar Array Processing
Abstract
In this paper, we present a distributed array processing algorithm to analyze the power output of solar photo-voltaic (PV) installations, leveraging the low rank structure inherent in the data to estimate possible faults. Our multi-agent algorithm requires near-neighbor communications only and is also capable of jointly estimating the common low rank cloud profile and local shading of panels. To illustrate the workings of our algorithm, we perform experiments to detect shading faults in solar PV installations within a single ZIP code. Additionally, we also derive a Bayesian lower hound on the shading parameter's mean squared estimation error. The results are promising and show that we can successfully estimate the fraction of partial shading in solar installations that can usually go unnoticed.
Year
DOI
Venue
2019
10.1109/icassp.2019.8682854
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Distributed array processing, Bayesian estimation, solar panel monitoring, partial shading
Array processing,Pattern recognition,Computer science,Upper and lower bounds,Algorithm,Artificial intelligence,Attenuation,Bayes estimator,Photovoltaic system,Shading,Cloud computing,Bayesian probability
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Raksha Ramakrishna163.65
Anna Scaglione22559225.41
Andreas S. Spanias352887.90
Cihan Tepedelenlioglu426342.24