Series resistance in pc1d
In the final case try setting the fraction of the cell affected by R s to 0.1. The try setting the fraction to 0.5, it produces a rounding around the maximum power point similar to a high J02. It sill follows the simple one dimensional case. the simple case where R s affects the whole cell) and adjusting the internal R s. In the simulation below try setting the fraction to 1 (i.e.
With only part of the cell affected by R s a variety of curves are produced.
#SERIES RESISTANCE IN PC1D SERIES#
Solar cell in which only part of the cell is affected by series resistance. Here only part of the cell is affected by a series resistance as shown in the figure below: The simplest way to demonstrate the problems caused by the deviations from the one dimensional model is with the model shown below 3. Curve fitting only works so long as the externally seen Rs is constant, which is rarely the case in practice. The blue points are measured data and the blue line is a double diode fit. A Thévenin or Norton equivalent circuit can only be constructed in the absence of non-linear elements such as diodes. As the level of current changes so does the apparent series resistance. The main impact of series resistance is to reduce the fill factor, although excessively high values may also reduce the short-circuit current. A solar cell is a three dimensional device and can be thought of as a network of resistors and diodes. One of the biggest problems is that the cell series resistance is a lumped parameter composed of many resistances within the device. While this is conceptually very simple there are often problems in practice. The simplest way to measure series resistance is to fit the illuminated IV curve with either the ideal diode equation or the double diode equation. There are several methods to measure series resistance and the comparisons of the accuracy for specific cell types. The series resistance of a solar cell dominates fill factor losses, especially in large area commercial solar cells, so an accurate measurement is vital in quantifying losses.