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Statistical modeling, parameter estimation and measurement planning for PV degradation

By Dazhi Yang, Licheng Liu, Carlos David Rodríguez-Gallegos, Zhen Ye and Li Hong Idris Lim

Abstract

Photovoltaics (PV) degradation is a key consideration during PV performance evaluation.\ud Accurately predicting power delivery over the course of lifetime of PV is vital\ud to manufacturers and system owners. With many systems exceeding 20 years of operation\ud worldwide, degradation rates have been reported abundantly in the recent years.\ud PV degradation is a complex function of a variety of factors, including but not limited\ud to climate, manufacturer, technology and installation skill. As a result, it is difficult to\ud determine degradation rate by analytical modeling; it has to be measured.\ud As one set of degradation measurements based on a single sample cannot represent\ud the population nor be used to estimate the true degradation of a particular PV\ud technology, repeated measures through multiple samples are essential. In this chapter,\ud linear mixed effects model (LMM) is introduced to analyze longitudinal degradation\ud data. The framework herein introduced aims to address three issues: 1) how to model\ud the difference in degradation observed in PV modules/systems of a same technology\ud that are installed at a shared location; 2) how to estimate the degradation rate and quantiles based on the data; and 3) how to effectively and efficiently plan degradation\ud measurements

Publisher: Nova Science Publishers, Inc.
OAI identifier: oai:eprints.gla.ac.uk:129322
Provided by: Enlighten

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