Calculation of the cell temperature of a high concentrator photovoltaic (HCPV) module: A study and comparison of different methods

Abstract Ascertaining the operating cell temperature of a high concentrator photovoltaic (HCPV) module is critical because its electrical parameters are influenced by this factor. However, measuring the cell temperature of an HCPV module is a complex task due to the unique features of such a module. This paper calculates the cell temperature in an HCPV module by using different methods to address this important issue. We conducted a comparative study of four methods used to estimate the cell temperature of an HCPV module, including the IEC 60904-5 method, a method based on thermal resistance proposed by the Instituto de Sistemas Fotovoltaicos de Concentracion, the Lineal method and an artificial neural network-based method introduced in this paper. The complete procedures, parameters and coefficients required to estimate the cell temperature with each method are provided. The results show that methods based on direct measurements of the HCPV module perform better than methods based on atmospheric parameters. However, all of the studied methods can be used to estimate cell temperatures with an acceptable margin of error.

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

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

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

[4]  Richard M. Swanson,et al.  The promise of concentrators , 2000 .

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

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

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

[8]  Jorge Aguilera,et al.  Generation of hourly irradiation synthetic series using the neural network multilayer perceptron , 2002 .

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

[10]  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.

[11]  Eduardo F. Fernández,et al.  Models for the electrical characterization of high concentration photovoltaic cells and modules: A review , 2013 .

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

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

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

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

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

[17]  Jorge Aguilera,et al.  A tool for obtaining the LOLP curves for sizing off-grid photovoltaic systems based in neural networks , 2003, 3rd World Conference onPhotovoltaic Energy Conversion, 2003. Proceedings of.

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

[19]  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 .

[20]  Eduardo F. Fernández,et al.  A simplified method for estimating direct normal solar irradiation from global horizontal irradiation useful for CPV applications , 2012 .

[21]  G. Peharz,et al.  Investigations on the temperature dependence of CPV modules equipped with triple‐junction solar cells , 2011 .

[22]  F. Rubio,et al.  Deploying CPV power plants - ISFOC experiences , 2008, 2008 33rd IEEE Photovoltaic Specialists Conference.

[23]  Jorge Aguilera,et al.  Recurrent Neural Supervised Models for Generating Solar Radiation Synthetic Series , 2001, J. Intell. Robotic Syst..

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