Maximum Power Point Estimation for Photovoltaic Strings Subjected to Partial Shading Scenarios

Jieming Ma*, Haochuan Jiang, Ziqiang Bi, Kaizhu Huang, Xingshuo Li, Huiqing Wen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

Partial shading is an unavoidable complication in the field of photovoltaic (PV) generation. Bypass diodes have become a standard feature of solar cell arrays to improve array performance under partial shading scenarios (PSS). However, the current-voltage and power-voltage characteristic data vary with different shading patterns. In this paper, a shading pattern detection algorithm is first proposed to estimate the number of shaded modules in a PV string. The result is then fed to a field-support vector regression (F-SVR) model, in which the measured features are transferred into a style-free high-dimension space prior to data training. The process of style-normalized transformation enables the features to be independent and identically distributed. Both simulations and experiments are conducted to evaluate the F-SVR model's ability to estimate the voltage at maximum power points. The results show that the proposed maximum power point estimation method can evidently reduce prediction errors.

Original languageEnglish
Article number8540929
Pages (from-to)1890-1902
Number of pages13
JournalIEEE Transactions on Industry Applications
Volume55
Issue number2
DOIs
Publication statusPublished - 1 Mar 2019

Keywords

  • Field support vector regression (F-SVR)
  • PV power generation system
  • maximum power point (MPP) estimation
  • partial shading scenarios (PSS)
  • photovoltaic (PV) cells

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