Title | ||
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Distributed Bayesian Estimation With Low-Rank Data: Application To Solar Array Processing |
Abstract | ||
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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 |
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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 Ramakrishna | 1 | 6 | 3.65 |
Anna Scaglione | 2 | 2559 | 225.41 |
Andreas S. Spanias | 3 | 528 | 87.90 |
Cihan Tepedelenlioglu | 4 | 263 | 42.24 |