2014
DOI: 10.1155/2014/514962
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Design of Multijunction Photovoltaic Cells Optimized for Varied Atmospheric Conditions

Abstract: Band gap engineering provides an opportunity to not only provide higher overall conversion efficiencies of the reference AM1.5 spectra but also customize PV device design for specific geographic locations and microenvironments based on atmospheric conditions characteristic to that particular location. Indium gallium nitride and other PV materials offer the opportunity for limited bandgap engineering to match spectra. The effects of atmospheric conditions such as aerosols, cloud cover, water vapor, and air mass… Show more

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Cited by 10 publications
(4 citation statements)
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“…Due to the major interest for photovoltaic technology, the researchers have developed various types of photovoltaic cells, such as multijunction, perovskite, and quantum well [5][6][7][8][9]. Although these types of photovoltaic cells are very promising, the monocrystalline, polycrystalline, and the amorphous silicon photovoltaic cells and panels are still more widely used in terrestrial applications.…”
Section: Introductionmentioning
confidence: 99%
“…Due to the major interest for photovoltaic technology, the researchers have developed various types of photovoltaic cells, such as multijunction, perovskite, and quantum well [5][6][7][8][9]. Although these types of photovoltaic cells are very promising, the monocrystalline, polycrystalline, and the amorphous silicon photovoltaic cells and panels are still more widely used in terrestrial applications.…”
Section: Introductionmentioning
confidence: 99%
“…InxGa1-xN, which really has come under renewed interest as a candidate material of high-efficiency multi-junction PV devices due to bandgap engineering between 0.7eV and 3.4eV by varying the x [35][36][37][38][39] is used as an example. In this case a single bandgap material of In0.54Ga0.46N is analyzed.…”
Section: Methodsmentioning
confidence: 99%
“…Another promising avenue is the development of "tunable" multijunction cells that can be adapted to a local climate based on SMARTS simulations [16,108].…”
Section: Spectral Modellingmentioning
confidence: 99%