Parametric Methodology to Optimize the Sizing of Solar Collector Fields in Series-Parallel Arrays

The analysis of solar thermal systems through numerical simulation is of great importance, since it allows predicting the performance of many configurations in any location and under different climatic conditions. Most of the simulation tools are commercial and require different degrees of training; therefore, it is important to develop simple and reliable methodologies to obtain similar results. This study presents a parametric methodology to size stationary solar collector fields, with operating temperatures up to 150 °C. The costs of the collector loop piping and the pumping power of different series–parallel arrays is considered. The proposed tool was validated with experimental data and through simulations using commercial software. The tool allows establishing series–parallel arrays and calculates the volume of the storage tank according to the thermal load. The calculation is based on the system energy balance, where the mass flow and the heat losses in the interconnections of the collectors are taken into account. The number of collectors and the optimal series–parallel array were determined. The results show deviations lower than 7% in the relative error of the temperature profiles and in the solar fraction, with respect to the results obtained by dynamic simulations.

[1]  Lixia Xu,et al.  Thermal Performance of Parabolic Trough Solar Collectors under the Condition of Dramatically Varying DNI , 2015 .

[2]  David James Wojcicki.  The application of the Typical Day Concept in flat plate solar collector models , 2015 .

[3]  Mario Adam,et al.  Storage in Solar Process Heat Applications , 2014 .

[4]  Roberto Fedrizzi,et al.  Demonstration of three large scale solar process heat applications with different solar thermal collector technologies , 2012 .

[5]  Harald Drück,et al.  Monitoring Results of a Solar Process Heat System Installed at a Textile Company in Southern Germany , 2015 .

[6]  Christian Zahler,et al.  Solar Process Heat for Sustainable Automobile Manufacturing , 2012 .

[7]  Theocharis Tsoutsos,et al.  Solar assisted heat pump on air collectors: A simulation tool , 2010 .

[8]  Christoph Brunner,et al.  Manufacture of Malt and Beer with Low Temperature Solar Process Heat , 2014 .

[9]  Simon Furbo,et al.  A numerical model to evaluate the flow distribution in a large solar collector field , 2017 .

[10]  Richárd Kicsiny.  Simplified multiple linear regression based model for solar collectors , 2014 .

[11]  Martín Picón-Núñez,et al.  Design of solar collector networks for industrial applications , 2013 .

[12]  Soteris A. Kalogirou,et al.  The potential of solar industrial process heat applications , 2003 .

[13]  Vinod Kumar,et al.  Modeling and simulation of solar water heater: A TRNSYS perspective , 2017 .

[14]  Aránzazu Fernández-García,et al.  Modeling and co-simulation of a parabolic trough solar plant for industrial process heat , 2013 .

[15]  S. Bandyopadhyay,et al.  Determination of design space and optimization of solar water heating systems , 2007 .

[16]  Huan Zhang,et al.  Comparison of different heat transfer models for parabolic trough solar collectors , 2015 .

[17]  P. Ineichen,et al.  A new simplified version of the perez diffuse irradiance model for tilted surfaces , 1987 .

[18]  Vitor V. Lopes,et al.  Dynamic testing of systems – Use of TRNSYS as an approach for parameter identification , 2014 .

[19]  M. Berenguel,et al.  Thermo-economic design optimization of parabolic trough solar plants for industrial process heat applications with memetic algorithms , 2014 .

[20]  Rahman Saidur,et al.  Solar process heat in industrial systems – A global review , 2018 .

[21]  Klaus Vajen,et al.  The potential of solar heat for industrial processes in Germany , 2012 .

[22]  Simon Furbo,et al.  Simulation of a Solar Collector Array Consisting of two Types of Solar Collectors, with and Without Convection Barrier☆ , 2015 .

[23]  Bastian Schmitt,et al.  System analysis of a low-temperature solar process heat system , 2014 .