Characterization Techniques and Optimization Principles for Multi-Junction Solar Cells and Maximum Long Term Performance of CPV Systems

• Main Author: Yandt, Mark
• Other Authors: Hinzer, Karin
• Language: en
• Published: Université d'Ottawa / University of Ottawa 2017
• Subjects: Photovoltaics; Solar Cells; Live IV curve; Shutter Technique; Representative Spectrum; Representative Atmospheric Parameters; Multi Junction Solar Cells; Solar Cell Optimization; Bandgap Optimisation; Concentrating Photovoltaic Systems
• Online Access: http://hdl.handle.net/10393/35870; http://dx.doi.org/10.20381/ruor-20153

Two related bodies of work are presented, both of which aim to further the rapid development of next generation concentrating photovoltaic systems using high efficiency multi junction solar cells. They are complementary since the characterization of commercial devices and the systematic application of design principles for future designs must progress in parallel in order to accelerate iterative improvements. First addressed, is the field characterization of state of the art concentrating photovoltaic systems. Performance modeling and root cause analysis of deviations from the modeling results are critical for bringing reliable high value products to the market. Two complementary tools are presented that facilitate acceleration of the development cycle. The “Dynamic real-time I V Curve Measurement System…” provides a live picture of the current-voltage characteristics of a CPV module. This provides the user with an intuitive understanding of how module performance responds under perturbation. The “Shutter technique for noninvasive individual cell characterization in sealed concentrating photovoltaic modules,” allows the user to probe individual cell characteristics within a sealed module. This facilitates non-invasive characterization of modules that are in situ. Together, these tools were used to diagnose the wide spread failure of epoxy connections between the carrier and the emitter of bypass diodes installed in sealed commercial modules. Next, the optimization principals that are used to choose energy yield maximizing bandgap combinations for multi-junction solar cells are investigated. It is well understood that, due to differences in the solar resource in different geographical locations, this is fundamentally a local optimization problem. However, until now, a robust methodology for determining the influences of geography and atmospheric content on the ideal design point has not been developed. This analysis is presented and the influence of changing environment on the representative spectra that are used to optimize bandgap combinations is demonstrated. Calculations are confirmed with ground measurements in Ottawa, Canada and the global trends are refined for this particular location. Further, as cell designers begin to take advantage of more flexible manufacturing processes, it is critical to know if and how optimization criteria must change for solar cells with more junctions. This analysis is expanded to account for the differences between cells with up to 8 subcell bandgaps. A number of software tools were also developed for the Sunlab during this work. A multi-junction solar cell model calibration tool was developed to determine the parameters that describe each subcell. The tool fits a two diode model to temperature dependent measurements of each subcell and provides the fitting parameters so that the performance of multi-junction solar cells composed of those subcells can be modeled for real world conditions before they are put on-sun. A multi-junction bandgap optimization tool was developed to more quickly and robustly determine the ideal bandgap combinations for a set of input spectra. The optimization process outputs the current results during iteration so that they may be visualized. Finally, software tools that compute annual energy yield for input multi-junction cell parameters were developed. Both a brute force tool that computes energy harvested at each time step, and an accelerated tool that first bins time steps into discrete bins were developed. These tools will continue to be used by members of the Sunlab.