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Energies 2018, 11(3), 485; https://doi.org/10.3390/en11030485

Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters

Department of Electrical and Information Engineering, Polytechnic University of Bari, st. E. Orabona 4, I-70125 Bari, Italy
Received: 28 January 2018 / Revised: 18 February 2018 / Accepted: 22 February 2018 / Published: 25 February 2018
(This article belongs to the Special Issue PV System Design and Performance)
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Abstract

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. View Full-Text
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 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
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Vergura, S. Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters. Energies 2018, 11, 485.

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