Transient Weighted Moving-Average Model of Photovoltaic Module Back-Surface Temperature

Matthew Prilliman, Joshua S. Stein, Daniel Riley, Govindasamy Tamizhmani

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Accurate modeling of photovoltaic (PV) performance requires the precise calculation of module temperature. Currently, most temperature models rely on steady-state assumptions that do not account for the transient climatic conditions and thermal mass of the module. On the other hand, complex physics-based transient models are computationally expensive and difficult to parameterize. In order to address this, a new approach to transient thermal modeling was developed, in which the steady-state predictions from previous timesteps are weighted and averaged to accurately predict the module temperature at finer time scales. This model is informed by 3-D finite-element analyses, which are used to calculate the effect of wind speed and module unit mass on module temperature. The model, in application, serves as an added filter over existing steady-state models that smooths out erroneous values that are a result of intermittency in solar resource. Validation of this moving-Average model has shown that it can improve the overall PV energy performance model accuracy by as much as 0.58% over steady-state models based on mean absolute error improvements and can significantly reduce the variability between the model predictions and measured temperature times series data.

Original languageEnglish (US)
Article number9095219
Pages (from-to)1053-1060
Number of pages8
JournalIEEE Journal of Photovoltaics
Volume10
Issue number4
DOIs
StatePublished - Jul 2020

Keywords

  • Performance analysis
  • photovoltaics (PV)
  • renewable Energy
  • thermal modeling

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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