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Automated Optimization of Solar-Thermal Systems Using Software in a Loop

Received: 11 November 2017    Accepted: 28 November 2017    Published: 17 January 2018
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Abstract

Making solar thermal systems less expensive, often results in a lower system efficiency. However, the cost-benefit ratio is relevant from the perspective of the consumer. The complex impact of component-related and system-related design parameters on the economics of a complete system makes the evaluation and economical optimization difficult. Therefore, a complete simulation environment has been developed, which can automatically optimize solar-thermal systems, including collector and system parameters. The main collector module consists of a one-dimensional thermal model that was validated with a commercial solar collector. The efficiency curve and the production cost were calculated as a function of several design and construction parameters. The collector module was linked to the commercial software Polysun®, so that parametric studies can be performed with minimal effort. Optimization problems can be solved by using the Matlab® optimization toolbox. The simulation environment was used for sensitivity studies and optimization problems in order to analyze the impact of collector design-parameters with respect to system cost, system yield and economic values. We will demonstrate how a collector can be optimized and how the ideal system parameters like collector number and storage volume can be easily calculated. Finally, we will show how the optimizer is used for a given system in order to find ideal values for the absorber-sheet thickness and the number of pipes. Due to the holistic approach, the application of this tool set can be used for collector development as well as for system planning.

Published in American Journal of Energy Engineering (Volume 5, Issue 6)
DOI 10.11648/j.ajee.20170506.11
Page(s) 50-56
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Solar-Thermal, Collector, Modelling, Optimization

References
[1] J. A. Duffie, William A. Beckman; Solar Engineering of Thermal Processes; Wiley, 1991.
[2] W. Eisenmann, K. Vajen et al., On the correlations between collector efficiency factor and material content of parallel flow flatplate solar collectors. Sol. Energy 76 (4), 2004.
[3] V. Badescu, Optimum fin geometry in flat plate solar collector systems. Energy Conversion Manage. 47 (15–16), 2006.
[4] R. Eismann, Thermohydraulische Dimensionierung von Solaranlagen: Theorie und Praxis der kostenoptimierenden Anlagenplanung; Springer, 2017.
[5] J. Koke, M. Kuhr, M. Althoff; U. Clement, M. Köhler, H. Boedeker; „Ganzheitliche Kostenoptimierung solarthermischer Systeme für Hersteller und Entwickler mittels Simulation“; Proceedings 26. Symposium Thermische Solarenergie, Bad Staffelstein, Germany, 2016.
[6] J. Koke, M. Kuhr, U. Clement; Software in a loop - Polysun und Matlab zur Optimierung solarthermischer Systeme; Proceedings SIGES 2016, Winterthur, Switzerland, 2016.
[7] R. Eismann, H. M. Prasser; Correction for the absorber edge effect in analytical models of flat plate solar collectors; Solar Energy 95, 2013.
[8] K. G. T. Hollands, G. D. Raithby, L. Konicek; Correlation equations for free convection heat transfer in horizontal layers of air and water. Int. J. Heat Mass Transf. 18 (7–8), 1975.
[9] K. G. T. Hollands, K. G. T., T. E. Unny, G. D. Raithby, L. Konicek; Free convective heat-transfer across inclined air layers. J. Heat Transf. – Trans. ASME 98 (2), 1976.
[10] R. Eismann; Accurate analytical modeling of flat plate solar collectors: Extended correlation for convective heat loss across the air gap between absorber and cover plate; Solar Energy 122, 2015.
[11] German Energy Saving Ordinance; Bundesgesetzblatt, Verordnung über energiesparenden Wärmeschutz und energiesparende Anlagen-technik bei Gebäuden (Energieeinsparverordnung – EnEV; ), dated: 24.10.2015.
[12] The Association of German Engineers (VDI); Standard VDI 6002, part 1, Solar heating for potable water - Basic principles - System technology and application in residential buildings; 2014.
Cite This Article
  • APA Style

    Johannes Koke, Matthias Kuhr, Uwe Clement. (2018). Automated Optimization of Solar-Thermal Systems Using Software in a Loop. American Journal of Energy Engineering, 5(6), 50-56. https://doi.org/10.11648/j.ajee.20170506.11

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    ACS Style

    Johannes Koke; Matthias Kuhr; Uwe Clement. Automated Optimization of Solar-Thermal Systems Using Software in a Loop. Am. J. Energy Eng. 2018, 5(6), 50-56. doi: 10.11648/j.ajee.20170506.11

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    AMA Style

    Johannes Koke, Matthias Kuhr, Uwe Clement. Automated Optimization of Solar-Thermal Systems Using Software in a Loop. Am J Energy Eng. 2018;5(6):50-56. doi: 10.11648/j.ajee.20170506.11

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  • @article{10.11648/j.ajee.20170506.11,
      author = {Johannes Koke and Matthias Kuhr and Uwe Clement},
      title = {Automated Optimization of Solar-Thermal Systems Using Software in a Loop},
      journal = {American Journal of Energy Engineering},
      volume = {5},
      number = {6},
      pages = {50-56},
      doi = {10.11648/j.ajee.20170506.11},
      url = {https://doi.org/10.11648/j.ajee.20170506.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajee.20170506.11},
      abstract = {Making solar thermal systems less expensive, often results in a lower system efficiency. However, the cost-benefit ratio is relevant from the perspective of the consumer. The complex impact of component-related and system-related design parameters on the economics of a complete system makes the evaluation and economical optimization difficult. Therefore, a complete simulation environment has been developed, which can automatically optimize solar-thermal systems, including collector and system parameters. The main collector module consists of a one-dimensional thermal model that was validated with a commercial solar collector. The efficiency curve and the production cost were calculated as a function of several design and construction parameters. The collector module was linked to the commercial software Polysun®, so that parametric studies can be performed with minimal effort. Optimization problems can be solved by using the Matlab® optimization toolbox. The simulation environment was used for sensitivity studies and optimization problems in order to analyze the impact of collector design-parameters with respect to system cost, system yield and economic values. We will demonstrate how a collector can be optimized and how the ideal system parameters like collector number and storage volume can be easily calculated. Finally, we will show how the optimizer is used for a given system in order to find ideal values for the absorber-sheet thickness and the number of pipes. Due to the holistic approach, the application of this tool set can be used for collector development as well as for system planning.},
     year = {2018}
    }
    

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    JF  - American Journal of Energy Engineering
    JO  - American Journal of Energy Engineering
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    AB  - Making solar thermal systems less expensive, often results in a lower system efficiency. However, the cost-benefit ratio is relevant from the perspective of the consumer. The complex impact of component-related and system-related design parameters on the economics of a complete system makes the evaluation and economical optimization difficult. Therefore, a complete simulation environment has been developed, which can automatically optimize solar-thermal systems, including collector and system parameters. The main collector module consists of a one-dimensional thermal model that was validated with a commercial solar collector. The efficiency curve and the production cost were calculated as a function of several design and construction parameters. The collector module was linked to the commercial software Polysun®, so that parametric studies can be performed with minimal effort. Optimization problems can be solved by using the Matlab® optimization toolbox. The simulation environment was used for sensitivity studies and optimization problems in order to analyze the impact of collector design-parameters with respect to system cost, system yield and economic values. We will demonstrate how a collector can be optimized and how the ideal system parameters like collector number and storage volume can be easily calculated. Finally, we will show how the optimizer is used for a given system in order to find ideal values for the absorber-sheet thickness and the number of pipes. Due to the holistic approach, the application of this tool set can be used for collector development as well as for system planning.
    VL  - 5
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Author Information
  • Faculty of Management, Culture and Technology, Osnabrueck University of Applied Sciences, Osnabrueck, Germany

  • Faculty of Management, Culture and Technology, Osnabrueck University of Applied Sciences, Osnabrueck, Germany

  • Bosch Thermotechnik GmbH, Wernau, Germany

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