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A Statistical Tool to Detect and Locate Abnormal Operating Conditions in Photovoltaic Systems

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  • Silvano Vergura

    (Department of Electrical and Information Engineering, Polytechnic University of Bari, St. E. Orabona 4, I-70125 Bari, Italy)

Abstract

The paper is focused on the energy performance of the photovoltaic systems constituted by several arrays. The main idea is to compare the statistical distributions of the energy dataset of the arrays. For small-medium-size photovoltaic plant, the environmental conditions affect equally all the arrays, so the comparative procedure is independent from the solar radiation and the cell temperature; therefore, it can also be applied to a photovoltaic plant not equipped by a weather station. If the procedure is iterated and new energy data are added at each new run, the analysis becomes cumulative and allows following the trend of some benchmarks. The methodology is based on an algorithm, which suggests the user, step by step, the suitable statistical tool to use. The first one is the Hartigan’s dip test that is able to discriminate the unimodal distribution from the multimodal one. This stage is very important to decide whether a parametric test can be used or not, because the parametric tests—based on known distributions—are usually more performing than the nonparametric ones. The procedure is effective in detecting and locating abnormal operating conditions, before they become failures. A case study is proposed, based on a real operating photovoltaic plant. Three periods are separately analyzed: one month, six months, and one year.

Suggested Citation

  • Silvano Vergura, 2018. "A Statistical Tool to Detect and Locate Abnormal Operating Conditions in Photovoltaic Systems," Sustainability, MDPI, vol. 10(3), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:608-:d:133724
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    References listed on IDEAS

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    1. Klaassen, Chris A. J. & Mokveld, Philip J. & van Es, Bert, 2000. "Squared skewness minus kurtosis bounded by 186/125 for unimodal distributions," Statistics & Probability Letters, Elsevier, vol. 50(2), pages 131-135, November.
    2. Rohatgi, Vijay K. & Székely, Gábor J., 1989. "Sharp inequalities between skewness and kurtosis," Statistics & Probability Letters, Elsevier, vol. 8(4), pages 297-299, September.
    3. Leloux, Jonathan & Narvarte, Luis & Trebosc, David, 2012. "Review of the performance of residential PV systems in France," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1369-1376.
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    1. Fuster-Palop, Enrique & Vargas-Salgado, Carlos & Ferri-Revert, Juan Carlos & Payá, Jorge, 2022. "Performance analysis and modelling of a 50 MW grid-connected photovoltaic plant in Spain after 12 years of operation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).

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