Reconfigurable Patterns of Photovoltaic Cells to Reduce Power Loss due to Detrimental Shading Conditions

Authors

  • Alexander Eick Federal University of Minas Gerais (UFMG) - Brazil
  • Joao Paulo Hanke de Faria Federal University of Minas Gerais (UFMG) - Brazil
  • Davies William de Lima Monteiro Federal University of Minas Gerais (UFMG) - Brazil https://orcid.org/0000-0002-9925-2392

DOI:

https://doi.org/10.29292/jics.v15i3.134

Keywords:

photovoltaic array, recoreconfigurable photovoltaics, smart photovoltaics, algorithm, BIPV

Abstract

Poorly illuminated or defective photovoltaic cells (PV cells) affect the performance of the whole panel. In this work, we propose a methodology to discover the best connection pattern among cells in a panel under unfavorable shading conditions. It is, therefore, assumed that the target PV module allows internal disconnection and reconnection of neighboring cells. In order to manage the reconfiguration of the cells on the array, the developed algorithm searches for the connection pattern that yields the least power loss, taking into account the cell model in silicon and the effect of shading. Three progressive shading schemes have been applied to mimic possible hard shading on a 36-cell panel. For each case, the algorithm analyzed the IV-characteristics of the panel and suggested the best cell-connection pattern to achieve the highest power output under each condition. When less than 15 of the 36 PV cells were affected by shading, the algorithm was able to  present up to 30% reduction in power loss when compared to the standard configuration, and up to 20% reduction when compared to complex fixed connection patterns. For shading patterns where 15 or more PV cells were affected, reconnection of the cells did not result in a reduction of power loss. However, if the PV panel is properly installed, only marginal hard shading should be expected and the algorithm would represent a promising tool to be deployed dynamically by means of switches and a management unit coupled to the panel.

Additional Files

Published

2020-12-03