LAPSE:2020.0259
Published Article
LAPSE:2020.0259
Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters
February 24, 2020
This paper deals with the monitoring of the performance of a photovoltaic plant, without using the environmental parameters such as the solar radiation and the temperature. The main idea is to statistically compare the energy performances of the arrays constituting the PV plant. In fact, the environmental conditions affect equally all the arrays of a small-medium-size PV plant, because the extension of the plant is limited, so any comparison between the energy distributions of identical arrays is independent of the solar radiation and the cell temperature, making the proposed methodology very effective for PV plants not equipped with a weather station, as it often happens for the PV plants located in urban contexts and having a nominal peak power in the 3÷50 kWp range, typically installed on the roof of a residential or industrial building. In this case, the costs of an advanced monitoring system based on the environmental data are not justified, consequently, the weather station is often also omitted. The proposed procedure guides the user through several inferential statistical tools that allow verifying whether the arrays have produced the same amount of energy or, alternatively, which is the worst array. The procedure is effective in detecting and locating abnormal operating conditions, before they become failures.
Keywords
ANOVA, Bartlett’s test, Hartigan’s dip test, Jarque-Bera’s test, Kruskal-Wallis’ test, Mood’s Median test, residential buildings, Tukey’s test, urban context
Suggested Citation
Vergura S. Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters. (2020). LAPSE:2020.0259
Author Affiliations
Vergura S: Department of Electrical and Information Engineering, Polytechnic University of Bari, st. E. Orabona 4, I-70125 Bari, Italy [ORCID]
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Journal Name
Energies
Volume
11
Issue
3
Article Number
E485
Year
2018
Publication Date
2018-02-25
Published Version
ISSN
1996-1073
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Original Submission
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PII: en11030485, Publication Type: Journal Article
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LAPSE:2020.0259
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doi:10.3390/en11030485
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Feb 24, 2020
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CC BY 4.0
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[v1] (Original Submission)
Feb 24, 2020
 
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Feb 24, 2020
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https://psecommunity.org/LAPSE:2020.0259
 
Original Submitter
Calvin Tsay
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