Models for the electrical characterization of high concentration photovoltaic cells and modules: A review

High concentration photovoltaic technology promises the large-scale generation of clean-renewable energy with competitive costs. Like any other systems for electricity generation, it is important to know the electrical characteristics of the system. However, while there is a wide experience in modeling the behavior of traditional photovoltaic systems, not every model for flat-plate solar cells or modules is directly applicable to high concentration photovoltaic cells or modules because of the special features of these devices (use of multijunction cells, use of optics for high concentration, etc.). So, in recent years, the scientific community has devoted considerable efforts in developing models that reproduce the electrical behavior of high concentration cells and modules. These models allow calculating the main electrical parameters of the device from its operating conditions (irradiance, cell temperature, spectral distribution of the radiation, etc.). In this paper, a comprehensive review of existing models for the electrical characterization of high concentration photovoltaic cells and modules is presented with the aim of helping the photovoltaic professionals and researchers in the design, monitoring and energy prediction tasks.

[1]  Yukiharu Uraoka,et al.  Evaluation of InGaP/InGaAs/Ge Triple-Junction Solar Cell under Concentrated Light by Simulation Program with Integrated Circuit Emphasis , 2004 .

[2]  Andreas Gombert,et al.  Temperature Dependent Measurement And Simulation Of Fresnel Lenses For Concentrating Photovoltaics , 2010 .

[3]  Florencia Almonacid,et al.  A new method for estimating angular, spectral and low irradiance losses in photovoltaic systems using an artificial neural network model in combination with the Osterwald model , 2012 .

[4]  David L. King,et al.  Photovoltaic module and array performance characterization methods for all system operating conditions , 1996 .

[5]  G. Peharz,et al.  Energy harvesting efficiency of III-V triple-junction concentrator solar cells under realistic spectral conditions , 2010 .

[6]  Eduardo F. Fernández,et al.  Relation between the cell temperature of a HCPV module and atmospheric parameters , 2012 .

[7]  Antonio J. Rivera,et al.  Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks , 2013, Expert Syst. Appl..

[8]  Harry A. Atwater,et al.  Future technology pathways of terrestrial III–V multijunction solar cells for concentrator photovoltaic systems , 2010 .

[9]  Eduardo F. Fernández,et al.  A two subcell equivalent solar cell model for III–V triple junction solar cells under spectrum and temperature variations , 2013 .

[10]  Eduardo F. Fernández,et al.  Temperature coefficients of monolithic III-V triple-junction solar cells under different spectra and irradiance levels , 2012 .

[11]  Carl R. Osterwald,et al.  Practical considerations in tandem cell modeling , 1989 .

[12]  Eduardo F. Fernández,et al.  Estimating the maximum power of a High Concentrator Photovoltaic (HCPV) module using an Artificial Neural Network , 2013 .

[13]  Carlos Algora,et al.  Extended Triple‐Junction Solar Cell 3D Distributed Model: Application to Chromatic Aberration‐Related Losses , 2011 .

[14]  I. Antón,et al.  Multijunction solar cell model for translating I–V characteristics as a function of irradiance, spectrum, and cell temperature , 2010 .

[15]  G. Almonacid,et al.  High Concentrator PhotoVoltaics efficiencies: Present status and forecast , 2011 .

[16]  H. Takakura,et al.  Uniqueness verification of solar spectrum index of average photon energy for evaluating outdoor performance of photovoltaic modules , 2009 .

[17]  Eduardo Fernández Fernández,et al.  Modelización y caracterización de células solares III-V multiunión y de módulos de concentración , 2012 .

[18]  A. T. Young,et al.  Revised optical air mass tables and approximation formula. , 1989, Applied optics.

[19]  Gerald Siefer,et al.  Realistic power output modeling of CPV modules , 2012 .

[20]  William E. Boyson,et al.  Photovoltaic array performance model. , 2004 .

[21]  Geoffrey S. Kinsey,et al.  METAMORPHIC III-V MATERIALS, SUBLATTICE DISORDER, AND MULTIJUNCTION SOLAR CELL APPROACHES WITH OVER 37% EFFICIENCY , 2004 .

[22]  D. L. King,et al.  Measuring solar spectral and angle-of-incidence effects on photovoltaic modules and solar irradiance sensors , 1997, Conference Record of the Twenty Sixth IEEE Photovoltaic Specialists Conference - 1997.

[23]  Manuel Fuentes,et al.  Characterisation of Si-crystalline PV modules by artificial neural networks , 2009 .

[24]  Pedro Pérez-Higueras,et al.  Analysis of the Energy of a PV Generator Using Artificial Neural Network , 2009 .

[25]  Abraham Kribus,et al.  Cogeneration With Concentrating Photovoltaic Systems , 2005 .

[26]  F. Dimroth,et al.  High‐efficiency solar cells from III‐V compound semiconductors , 2006 .

[27]  Joseph Appelbaum,et al.  Estimation of multi‐junction solar cell parameters , 2012 .

[28]  Carlos Algora del Valle,et al.  Extended Triple-Junction Solar Cell 3D Distributed Model: Application to Chromatic Aberration-Related Losses , 2011 .

[29]  L. Hontoria,et al.  Estimation of the energy of a PV generator using artificial neural network , 2009 .

[30]  Gerald Siefer,et al.  A method for using CPV modules as temperature sensors and its application to rating procedures , 2011 .

[31]  Martin A. Green,et al.  Solar cell efficiency tables (version 39) , 2012 .

[32]  P. Hebert,et al.  Concentrator multijunction solar cell characteristics under variable intensity and temperature , 2008 .

[33]  Eduardo F. Fernandez,et al.  Monolithic III-V triple-junction solar cells under different temperatures and spectra , 2011, Proceedings of the 8th Spanish Conference on Electron Devices, CDE'2011.

[34]  Yasuyuki Ota,et al.  Detailed Analysis of Temperature Characteristics of an InGaP/InGaAs/Ge Triple-Junction Solar Cell , 2010 .

[35]  Guk-Rwang Won American Society for Testing and Materials , 1987 .

[36]  Clay Mayberry,et al.  Multijunction solar cell iso-junction dark current study , 2000, Conference Record of the Twenty-Eighth IEEE Photovoltaic Specialists Conference - 2000 (Cat. No.00CH37036).

[37]  Thomas R. Betts,et al.  Modelling long-term module performance based on realistic reporting conditions with consideration to spectral effects , 2003, 3rd World Conference onPhotovoltaic Energy Conversion, 2003. Proceedings of.

[38]  G. Peharz,et al.  A simple method for quantifying spectral impacts on multi-junction solar cells , 2009 .

[39]  Lewis Fraas Larry Partain Solar Cells and Their Applications , 2010 .

[40]  H. R. Wilson,et al.  A new approach for the performance evaluation of solar cells under realistic reporting conditions , 1990, IEEE Conference on Photovoltaic Specialists.

[41]  G. Almonacid,et al.  Calculation of cell temperature in a HCPV module using Voc , 2013, 2013 Spanish Conference on Electron Devices.

[42]  K. Emery,et al.  Spectral corrections based on optical air mass , 2002, Conference Record of the Twenty-Ninth IEEE Photovoltaic Specialists Conference, 2002..

[43]  C. Gueymard Parameterized transmittance model for direct beam and circumsolar spectral irradiance , 2001 .

[44]  W. Warta,et al.  Solar cell efficiency tables (Version 45) , 2015 .

[45]  D. L. King,et al.  Sandia National Laboratories , 2000 .

[46]  Frank Dimroth,et al.  A validated SPICE network simulation study on improving tunnel diodes by introducing lateral conduction layers , 2012 .

[47]  L. Hontoria,et al.  Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods , 2010 .

[48]  Andreas Gombert,et al.  Development of FLATCON® modules using secondary optics , 2009, 2009 34th IEEE Photovoltaic Specialists Conference (PVSC).

[49]  D. L. King,et al.  Temperature coefficients for PV modules and arrays: measurement methods, difficulties, and results , 1997, Conference Record of the Twenty Sixth IEEE Photovoltaic Specialists Conference - 1997.

[50]  Gerald Siefer,et al.  Analysis of temperature coefficients for III–V multi‐junction concentrator cells , 2014 .

[51]  K. Edmondson,et al.  Spectral response and energy output of concentrator multijunction solar cells , 2009 .

[52]  Eduardo F. Fernández,et al.  Quantifying the effect of air temperature in CPV modules under outdoor conditions , 2012 .

[53]  Keith Emery,et al.  Spectral effects on PV-device rating , 1992 .

[54]  M. Z. Shvarts,et al.  DISTRIBUTED RESISTANCE EFFECTS SIMULATION IN CONCENTRATOR MJ SCS USING 3D-NETWORK MODEL , 2010 .

[55]  Pedro Pérez-Higueras,et al.  Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks , 2011 .

[56]  S. Kurtz,et al.  The influence of spectral solar irradiance variations on the performance of selected single-junction and multijunction solar cells , 1991 .

[57]  Florencia Almonacid,et al.  Generation of ambient temperature hourly time series for some Spanish locations by artificial neural networks , 2013 .

[58]  P. G. Vidal,et al.  Outdoor evaluation of concentrator photovoltaic systems modules from different manufacturers: first results and steps , 2013 .

[59]  Abraham Kribus,et al.  Equivalent circuit models for triple-junction concentrator solar cells , 2012 .