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Outlier identification in outdoor measurement data: effects of different strategies on the performance descriptors of photovoltaic modules

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conference contribution
posted on 14.06.2010 by Jiang Zhu, Yingning Qiu, Tom Betts, Ralph Gottschalg
Outdoor measurement campaigns of PV module performance are normally affected by a relatively large number of outliers. The aim of this paper is to develop a statistically sound approach of obtaining a dataset that allows one to analyse continuously monitored devices for use of high volume data measurements. This paper uses ISC as a self-reference parameter to measure the incident irradiance on the module, which largely eliminates the error due to differences in spectral and angular response between test and reference detector. The outlier identification procedure is based on statistical distribution analysis of different performance descriptors and it assures 0.99 confidence level and the same skewness for the remaining data. This approach can be applied to whole datasets as well as for data in specific irradiance-temperature bins. The developed methodology will be used to analyze outdoor data from different devices at different locations with reduced uncertainty. It is shown that this approach is particularly useful for obtaining lower uncertainties in low irradiance measurements.
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School

  • Mechanical, Electrical and Manufacturing Engineering

Research Unit

  • Centre for Renewable Energy Systems Technology (CREST)

Citation

ZHU, J. ... et al, 2009. Outlier identification in outdoor measurement data: effects of different strategies on the performance descriptors of photovoltaic modules. Proceedings of the 34th IEEE Photovoltaic Specialists Conference, 7-12 June 2009, pp.000828-000833.

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© IEEE

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VoR (Version of Record)

Publication date

2009

Notes

This conference paper is also available at: http://ieeexplore.ieee.org/ © 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

9781424429493

ISSN

0160-8371

Language

en

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