This page describes selected literature available on Bandgap engineering of multijunction photovoltaic cells for spectral albedo of natural surfaces.

Variation in Spectral Irradiance and the Consequences for Multi-junction Concentrator Photovoltaic Systems[1]

Abstract: The most fundamental figure of merit for a solar collector is its power rating under a standard solar spectrum. For concentrator systems that employ highly efficient multi-junction solar cells, the rating of the panel becomes sensitive to the spectrum of the direct beam sunlight. By considering typical spectral conditions at a measurement site, we show that the power rating can vary by up to 16%. Further, we consider to what extent a single reference spectrum can be used to characterize the irradiance at a particular location. Electrical energy yields produced using both synthesized and standard reference spectra are compared, with standardized references shown to be unsuited for accurate energy yield predictions under realistic spectral conditions.

What Is an Air Mass 1.5 Spectrum?[2]]

Abstract: The origin of the AM 1.5 spectra, how they are related to actual outdoor spectral distributions, and the implications for outdoor PV (photovoltaic) performance predictions are explained. It is pointed out that the AM 1.5 spectra provide a reference point corresponding to a particular set of atmospheric conditions and a specific air mass. One can expect variations in outdoor PV device performance for different atmospheric conditions and air masses. The uncertainty in using AM 1.5 spectra to predict field performance depends on the particular PV device design and climate. The wavelength distribution of photon flux varies with respect to conditions such as water vapor and air mass, and this in turn influences current densities in PV devices, depending on such device characteristics as bandgap(s). Therefore, PV device design (e.g. optimization) should be based on a range of spectra representing various atmospheric conditions and air masses.

The Influence of Spectral Solar Irradiance Variations on the Performance of Selected Single-junction and Multijunction Solar Cells[3]

Abstract: The sensitivities of selected single-junction and multijunction cells to variations in solar irradiance are presented. The one-sun spectral irradiance is varied as a function of air mass, optical aerosol depth (turbidity) and amount of precipitable water vapor for direct-normal and global-normal geometries. Several devices, including one-, two- and three-junction devices with low and high bandgaps and either series- or independent-connection schemes, were investigated. The effects of air mass and turbidity on the consistency of high-bandgap device performance are shown to be greater than the effect of precipitable water vapor. Low-bandgap devices are less affected by variations in air mass and turbidity, but are more sensitive to high water-vapor conditions. The efficiency gained by redesigning a multijunction device for the latitude at which it is expected to be used is shown to be less than about 3% (relative).

Spectral effects on PV-device rating[4]

Abstract: A recently developed spectral model "SEDES2" is applied to study the effect of variations in solar spectral irradiance on the efficiency of seven particular solar cells. As a new feature, SEDES2 calculates hourly solar spectral irradiance for clear and cloudy skies from readily available site-specific meteorological data. Based on these hourly spectra, monthly and yearly efficiencies for the solar cells are derived. As a key result the efficiencies of amorphous silicon cells differ by 10% between winter and summer months because of spectral effects only. A second intention of this study is to analyse the sensitivity of power and energy rating methods to spectral irradiance but also to total irradiance and cell temperature. As an outcome, a multi-value energy rating scheme applying the concept of "critical operation periods" is proposed.

Outdoor measurement of multi-junction solar cells and modules based on the reference sunlight method[5]

Abstract: To evaluate the indoor measurement accuracy of multi-junction solar cells and modules experimentally, we have successfully used natural sunlight whose spectral irradiance is close to the reference sunlight. The reference sunlight for evaluating the performance of solar cells can be realized by choosing natural sunlight incident on a sun-facing 37° tilted surface at air mass of 1.5, when the atmosphere has turbidity of 0.27, precipitable water of 1.42 cm and so on. The measurement of atmospheric parameters was performed based mainly on the measurement of direct solar spectral irradiance and additionally on the measurements of irradiance and illuminance. In addition, measured values were compared with aerological observation data. The comparison of I–V characteristics measured outdoors and indoors shows that our pulsed-light solar simulator is capable of measuring multi-junction amorphous silicon alloy solar cells and modules accurately enough when its irradiance is set by an amorphous silicon reference cell. This fact is also confirmed by the examination of spectral irradiance on the test plane of the solar simulator. Moreover, we showed that irradiance (or illuminance) can be used instead of atmospheric turbidity and also water vapor content on a surface of the Earth can be used as a rough estimate of precipitable water for finding the reference sunlight conditions.

Photovoltaic module and array performance characterization methods for all system operating conditions[6]

Absract:This paper provides new test methods and analytical procedures for characterizing the electrical performance of photovoltaic modules and arrays. The methods use outdoor measurements to provide performance parameters both at standard reporting conditions and for all operating conditions encountered by typical photovoltaic systems. Improvements over previously used test methods are identified, and examples of the successful application of the methodology are provided for crystalline- and amorphous-silicon modules and arrays. This work provides an improved understanding of module and array performance characteristics, and perhaps most importantly, a straight-forward yet rigorous model for predicting array performance at all operating conditions. For the first time, the influences of solar irradiance, operating temperature, solar spectrum, solar angle-of-incidence, and temperature coefficients are all addressed in a practical way that will benefit both designers and users of photovoltaics.

Lattice-mismatched approaches for high-performance, III-V photovoltaic energy converters[7]

Abstract:We discuss lattice-mismatched (LMM) approaches utilizing compositionally step-graded layers and buffer layers that yield III-V photovoltaic devices with performance parameters equaling those of similar lattice-matched (LM) devices. Our progress in developing high-performance, LMM, InP-based GaInAs/InAsP materials and devices for thermophotovoltaic (TPV) energy conversion is highlighted. A novel, monolithic, multi-bandgap, tandem device for solar PV (SPV) conversion involving LMM materials is also presented along with promising preliminary performance results.

Spectrally-Selective Photonic Structures for PV Applications[8]

Abstract:Abstract: We review several examples of how spectrally-selective photonic structures may be used to improve solar cell systems. Firstly, we introduce different spectrally-selective structures that are based on interference effects. Examples shown include Rugate filter, edge filter and 3D photonic crystals such as artificial opals. In the second part, we discuss several examples of photovoltaic (PV) concepts that utilize spectral selectivity such as fluorescence collectors, upconversion systems, spectrum splitting concepts and the intermediate reflector concept. The potential of spectrally selective filters in the context of solar cells is discussed.

Efficiency of multijunction photovoltaic systems[9]

Abstract:In this paper, an expression for the PV system efficiency is derived that can be used in conjunction with measured device performance and detailed numerical modeling to analyze PV system performance. Such an analysis will help identify design trade-offs and also help to identify which system and cell design changes will be of greatest benefit to the enhancement of PV system performance.

Four-junction spectral beam-splitting photovoltaic receiver with high optical efficiency.[10]

Abstract:This paper presents a spectral beam splitting arrangement providing the basis for a four-junction photovoltaic receiver with virtually ideal band gap combination. A light trapping assembly in form of a 45 parallelepiped applying two spectrally selective beam splitters and three solar cells realizes an approach to reach very high solar-electrical conversion efficiency. The spectral beam splitters developed and used in this arrangement show nearly ideal broadband characteristics to split the solar spectrum into three parts. The solar cell selection includes III-V semiconductors and silicon. They were all fabricated at Fraunhofer ISE and assembled in the receiver setup. The experimental setup demonstrated an outdoor efficiency of more than 34 %.

Array Performance Characterization and Modeling for Real-Time Performance Analysis of Photovoltaic Systems.[13]

Abstract:Improvements in the methods used for photovoltaic (PV) system design, performance rating, and long-term monitoring are needed by the rapidly growing industry, as well as by the U.S. Department of Energy in evaluating progress by solar technology development initiatives. This paper describes an improved model for rating and monitoring PV array performance, discusses initial results from an outdoor laboratory designed to assist industry in optimizing system components and integration, and provides a brief discussion of the system performance metrics currently being used by the PV community.

Solar spectral irradiance under overcast skies [solar cell performance effects.[14]

Abstarct:The authors examine a particular aspect of cloudy-sky conditions that affects PV (photovoltaic) device performance, i.e. the solar spectral distribution under an overcast sky with respect to the spectral response of PV devices. The approach is to analyze several thousand measured spectral irradiance data that illustrate spectral shifts under cloud cover. The questions raised are how the transmission of clouds deviates from an assumed neutral density filter and whether the standard reference spectrum applied by the PV community to design and performance prediction is applicable for cloudy climates. Comparing the measurements with clear-sky simulations, the authors established a correlation between cloud thickness and alterations in the relative spectral transmission. Because of the approach used, these observed effects are true only for the statistical mean of a sufficiently large number of measurements

High efficiency photovoltaic conversion with spectrum splitting on GaAs and Si cells located in light confining cavities.][15]

Abstract:A high-efficiency photovoltaic conversion system based on spectrum splitting of concentrated light to fall on GaAs and Si cells placed inside light confining cavities is described and experimental results are reported: 29.4% at 180 suns (near AM1.5 direct spectrum), 22% contributed by the GaAs cell. The short-circuit current gain derived from the use of the cavities is 7-8% (relative increase). However, the system is believed to have immediate potential to achieve as much as 32% efficiency. Benefits compared to systems based on stacked cells are pointed out: (a) conventional cells based on developed fabrication techniques can be used, with minor design changes, (b) cell design can be independently optimized with the aim of achieving maximum efficiency, (c) cells can operate at different concentrations, (d) electrical power can be extracted independently from each cell, and (e) it is easy to make the electrical connections to each cell.

Estimating potential photovoltaic yield with r.sun and the open source Geographical Resources Analysis Support System.[16]

Abstract:he package r.sun within the open source Geographical Resources Analysis Support System (GRASS) can be used to compute insolation including temporal and spatial variation of albedo and solar photovoltaic yield. A complete algorithm is presented covering the steps of data acquisition and preprocessing to post-simulation whereby candidate lands for incoming solar farms projects are identified. The optimal resolution to acquire reliable solar energy outputs to be integrated into PV system design software was determined to be 1 square km. A case study using the algorithm developed here was performed on a North American region encompassing fourteen counties in South-eastern Ontario. It was confirmed for the case study that Ontario has a large potential for solar electricity. This region is found to possess over 935,000 acres appropriate for solar farm development, which could provide 90 GW of PV. This is nearly 60% of Ontario's projected peak electricity demand in 2025. The algorithm developed and tested in this paper can be generalized to any region in the world in order to foster the most environmentally-responsible development of large-scale solar farms.

Prediction of energy effects on photovoltaic systems due to snowfall events.[17]

Abstract:The accurate prediction of yields from photovoltaic systems (PV) is critical for their proper operation and financing, and in northern latitudes the effects of snowfall on yield can become significant. This work provides methods for identifying snowfall effects from commonly collected performance data, and recommends a model to allow for prediction of these effects based solely on meteorological time series. The model was validated with data from two large-scale (>;8MW) operational PV plants. For the low tilt angles most affected by snowfall, this analysis was able to accurately predict both daily and mean values of snow effects. This methodology will enable system operators to utilize performance data to accurately identify and predict snowfall losses, and will assist system designers to optimize for the effects of snowfall on new system designs.

Quality control of solar radiation data: Present status and proposed new approaches.[18]

Abstarct:During the past few decades, there has been a continual rise in interest in passive and active solar energy uses, not only in the governmental and commercial sectors, but also within the private sector. There is thus a need for taking measurements of solar irradiation and creating local and regional databases of irradiation and synoptic (meteorological) information. However, there is no guarantee of the quality of the data collected, as often due care is not exercised with respect to quality control of the measured dataset.

This article reviews the presently available procedures for quality assessment of the solar irradiation data. Furthermore, we propose a set of stringent physical and statistical measures to create a semi-automated procedure that is based on the creation of an envelope in the clearness index–diffuse to global irradiance ratio domain. The procedure is very general in nature and may be used with equal effectiveness for any terrestrial dataset.

Effects of snow physical parameters on spectral albedo and bidirectional reflectance of snow surface.[19]

Abstract:Observations of spectral albedo and bidirectional reflectance in the wavelength region of lambda = 0.35-2.5 mu m were made together with snow pit work on a flat snowfield in eastern Hokkaido, Japan. The effects of snow impurities, density, layer structure, and grain size attained by in situ and laboratory measurements were taken into account in snow models for which spectral albedos were calculated using a multiple-scattering model for the atmosphere-snow system. Comparisons of these theoretical albedos with measured ones suggest that the snow impurities were concentrated at the snow surface by dry fallout of atmospheric aerosols. The optically equivalent snow grain size was found to be of the order of a branch width of dendrites or of a dimension of narrower portion of broken crystals. This size was smaller than both the mean grain size and the effective grain size obtained from micrographs by image processing. The observational results for the. bidirectional reflection distribution function (BRDF) normalized by the radiance at the nadir showed that the anisotropic reflection was very significant in the near-infrared region, especially for lambda > 1.4 mu m, while the visible normalized BRDF (NBRDF) patterns were relatively flat. Comparison of this result with two kinds of theoretical NBRDFs, where one having been calculated using single-scattering parameters by Mie theory and the other using the same parameters except for Henyey-Greenstein (HG) phase function obtained from the same asymmetry factor as in the Mie theory, showed that the observed NBRDF agreed with the theoretical one using the HG phase function rather than with that using the Mie phase function, while the albedos calculated with both phase functions agreed well with each other.

- Study quantifies the effects of snow physical parameters in Japan for the 0.35 - 2.5 microns spectral range.
- Spectral albedo observed using a grating spectrometer, FieldSpec FR (ASD Inc, USA)with spetral resolution 3 - 10 nm.
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SPECTRAL ALBEDO MEASUREMENTS IN THE UV and VISIBLE REGION OVER DIFFERENT TYPES OF SURFACES.[20]

Abstract: The spectral albedo of the earth's surface, i.e. the ratio between spectral irradiance reflected by the ground to all directions and global irradiance, was measured by a spectroradiometer in the UV and visible region from 290 nm to 800 nm with a spectral resolution of 1.5 nm at steps of 2 nm in the UV (290–400 nm) and 10 nm in the visible (400–800 nm) region. The measurements were performed over bare fertile soil, sand at the beach, concrete (autobahn) and snow as well as over different types of vegetation (grass, oats, rye, sugar-beet, stubble). As the albedo increases with increasing wavelengths for most types of surfaces considered, it is smaller in the UV than in the visible region. In the UVB region (λ < 315 nm) the measured albedo is as small as 0.016-0.017 over vegetation, 0.04-0.05 over bare fertile soil, 0.07-0.10 over concrete ("autobahn") and 0.62-0.76% over polluted snow with a small wavelength dependence. A somewhat higher albedo occurs in the UVA region (315 < λ < 400 nm) with values ranging from 0.02 over vegetation to 0.05 to 0.08 over bare soil. The albedo over dry bright sand, which is typically found at the beach, is significantly higher (0.14 at 300 nm to 0.24 at 400 nm) than over other snow-free surfaces, thus leading to an enhanced dose of biologically effective radiation at the beach.

Experimental study of variations of the solar spectrum of relevance to thin film solar cells.[21]

Abstract:The influence of variations in the incident solar spectrum on solar cells is often neglected. This paper investigates the magnitude of this variation and its potential influence on the performance of thin film solar cells in a maritime climate. The investigation centres on the analysis of a large number of measurements carried out in Loughborough, UK, at 10 min intervals over a period of 30 months. The magnitude of the spectral variation is presented both on a daily and a seasonal basis. Of the different thin film materials studied, amorphous silicon is shown to be the most susceptible to changes in the spectral distribution, with the "useful fraction" of the light varying in the range +6% to −9% of the annual average, with the maximum occurring in summer time.

A method for modeling the current–voltage curve of a PV module for outdoor conditions," Progress in Photovoltaics: Research and Applications.[22]

Abstract:A method has been developed for modeling the current–voltage curve of a photovoltaic (PV) module for outdoor conditions. An indoor characterization procedure determines a PV module's temperature and irradiance correction factors, which are used in conjunction with equations to translate a reference curve to outdoor conditions of PV module temperature and irradiance. A PV technology's spectral response characteristics are accommodated in the equation for irradiance. The modeled and measured energy is compared for a one-year period for seven PV modules of different technologies. The results validate the method's use for modeling the hourly performance of PV modules, and for modeling daily energy production for PV module energy rating purposes.

Page data
Type Literature review Jephias Gwamuri, Chenlong Zhang 2013 CC-BY-SA-4.0 625 No lead section, No main image Jephias Gwamuri, Chenlong Zhang (2013). "Bandgap engineering of multijunction photovoltaic cells for spectral albedo of natural surfaces". Appropedia. Retrieved August 7, 2022.
1. Chan, N., T. Young, H. Brindley, B. Chaudhuri, and N.J. Ekins-Daukes. "Variation in Spectral Irradiance and the Consequences for Multi-junction Concentrator Photovoltaic Systems." In 2010 35th IEEE Photovoltaic Specialists Conference (PVSC), 003008 –003012, 2010
2. Riordan, C., and R. Hulstron."What Is an Air Mass 1.5 Spectrum?"Conference Record of the Twenty First IEEE Photovoltaic Specialists Conference, 1990, 1085 –1088 vol.2, 1990.
3. Faine, P., Sarah R. Kurtz, C. Riordan, and J.M. Olson. "The Influence of Spectral Solar Irradiance Variations on the Performance of Selected Single-junction and Multijunction Solar Cells." Solar Cells 31, no. 3 (June 1991): 259–278. doi:10.1016/0379-6787(91)90027-M
4. Nann, S., and K. Emery. "Spectral Effects on PV-device Rating." Solar Energy Materials and Solar Cells 27, no. 3 (August 1992): 189–216. doi:10.1016/0927-0248(92)90083-2.
5. Suzuki, Mamoru, Junta Nose, Akihiko Nakano, Yoshihiro Imura, and Makoto Igarashi. "Outdoor Measurement of Multi-junction Solar Cells and Modules Based on the Reference Sunlight Method." Solar Energy 60, no. 2 (February 1997): 63–70. doi:10.1016/S0038-092X(96)00164-8.
6. D. L. King, "Photovoltaic module and array performance characterization methods for all system operating conditions," AIP Conference Proceedings, vol. 394, no. 1, pp. 347–368, Feb. 1997.
7. M. W. Wanlass, S. P. Ahrenkiel, R. K. Ahrenkiel, D. S. Albin, J. J. Carapella, A. Duda, J. F. Geisz, S. Kurtz, T. Moriarty, R. J. Wehrer, and B. Wernsman, "Lattice-mismatched approaches for high-performance, III-V photovoltaic energy converters," in Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, 2005, 2005, pp. 530 – 535.
8. M. Peters, J. C. Goldschmidt, P. Löper, B. Groß, J. Üpping, F. Dimroth, R. B. Wehrspohn, and B. Bläsi, "Spectrally-Selective Photonic Structures for PV Applications," Energies, vol. 3, no. 2, pp. 171–193, Jan. 2010.
9. J. L. Gray, A. W. Haas, J. R. Wilcox, and R. J. Schwartz, "Efficiency of multijunction photovoltaic systems," in 33rd IEEE Photovoltaic Specialists Conference, 2008. PVSC '08, 2008, pp. 1 –6.
10. Mitchell, B., "Four-junction spectral beam-splitting photovoltaic receiver with high optical efficiency," Progress in Photovoltaics, vol. 19, no. Nr.1, pp. 61–72, 2011.
11. C. A. Gueymard, "Interdisciplinary applications of a versatile spectral solar irradiance model: A review," Energy, vol. 30, no. 9, pp. 1551–1576, Jul. 2005.
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13. D. L. King, G. M. Galbraith, W. E. Boyson, S. Gonzalez, A. T. Murray, J. W. Ginn, and W. I. Bower, "Array Performance Characterization and Modeling for Real-Time Performance Analysis of Photovoltaic Systems," in Conference Record of the 2006 IEEE 4th World Conference on Photovoltaic Energy Conversion, 2006, vol. 2, pp. 2308 –2311.
14. S. Nann and C. Riordan, "Solar spectral irradiance under overcast skies [solar cell performance effects]," in , Conference Record of the Twenty First IEEE Photovoltaic Specialists Conference, 1990, 1990, pp. 1110 –1115 vol.2.
15. A. Marti, P. A. Davies, J. Olivan, C. Algora, M. J. Terron, J. Alonso, J. C. Maroto, G. L. Araujo, J. C. Minano, G. Sala, and A. Luque, "High efficiency photovoltaic conversion with spectrum splitting on GaAs and Si cells located in light confining cavities," in , Conference Record of the Twenty Third IEEE Photovoltaic Specialists Conference, 1993, 1993, pp. 768 –773.
16. H. T. Nguyen and J. M. Pearce, "Estimating potential photovoltaic yield with r.sun and the open source Geographical Resources Analysis Support System," Solar Energy, vol. 84, no. 5, pp. 831–843, May 2010.
17. R. W. Andrews and J. M. Pearce, "Prediction of energy effects on photovoltaic systems due to snowfall events," in 2012 38th IEEE Photovoltaic Specialists Conference (PVSC), 2012, pp. 003386 –003391.
18. S. Younes, R. Claywell, and T. Muneer, "Quality control of solar radiation data: Present status and proposed new approaches," Energy, vol. 30, no. 9, pp. 1533–1549, Jul. 2005.
19. T. Aoki and M. Fukabori, "Effects of snow physical parameters on spectral albedo and bidirectional reflectance of snow surface," Journal of Geophysical Research, vol. 105, no. D8, pp. 10219–10236, 2000.
20. U. Feister and R. Grewe, "SPECTRAL ALBEDO MEASUREMENTS IN THE UV and VISIBLE REGION OVER DIFFERENT TYPES OF SURFACES," Photochemistry and Photobiology, vol. 62, no. 4, pp. 736–744, 1995.
21. R. Gottschalg, D. G. Infield, and M. J. Kearney, "Experimental study of variations of the solar spectrum of relevance to thin film solar cells," Solar Energy Materials and Solar Cells, vol. 79, no. 4, pp. 527–537, Sep. 2003.
22. B. Marion, "A method for modeling the current–voltage curve of a PV module for outdoor conditions," Progress in Photovoltaics: Research and Applications, vol. 10, no. 3, pp. 205–214, 2002.
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