Spectral binning for energy production calculations and multijunction solar cell design

Currently, most solar cells are designed for and evaluated under standard spectra intended to represent typical spectral conditions. However, no single spectrum can capture the spectral variability needed for annual energy production (AEP) calculations, and this shortcoming becomes more significant for series-connected multijunction cells as the number of junctions increases. For this reason, AEP calculations are often performed on very detailed yearlong sets of data, but these pose 2 inherent challenges: (1) These data sets comprise thousands of data points, which appear as a scattered cloud of data when plotted against typical parameters and are hence cumbersome to classify and compare, and (2) large sets of spectra bring with them a corresponding increase in computation or measurement time. Here, we show how a large spectral set can be reduced to just a few proxy spectra, which still retain the spectral variability information needed for AEP design and evaluation. The basic spectral binning methods should be extensible to a variety of multijunction device architectures. In this study, as a demonstration, the AEP of a 4-junction device is computed for both a full set of spectra and a reduced proxy set, and the results show excellent agreement for as few as 3 proxy spectra. This enables much faster (and thereby more detailed) calculations and indoor measurements and provides a manageable way to parameterize a spectral set, essentially creating a spectral fingerprint, which should facilitate the understanding and comparison of different sites.