Design of solar thermal systems under uncertainty

Abstract Uncertainties are involved in every part of a solar thermal system due to tolerances in design parameters, tolerances in system parts, and the random nature of variables like solar radiation and thermal demand. Current design practices in solar engineering do not incorporate these uncertainties into the design process, despite the fact that their magnitude and combined effect are often large enough to make the result of the calculations very dependent on the assumptions about the true values of the input data. This paper proposes the application of reliability analysis methods to design solar thermal systems, in order to take into account the true stochastic nature of the problem. This approach allows designers to quantify the probability that the system will achieve the desired performance in the face of uncertainty. The methodology followed in the paper consists in applying uncertainty bands to the input data. Monte Carlo techniques are then used to propagate these uncertainties, calculate the reliability of the system and determine its sensitivity to each uncertain factor. The practical application of the proposed design methodology is illustrated with a case study, in which a typical solar hot water thermal system is dimensioned.

[1]  J. Duffie,et al.  A methodology for the synthesis of hourly weather data , 1991 .

[2]  Felix A. Peuser,et al.  Solar Thermal Systems: Successful Planning and Construction , 2002 .

[3]  Terje Aven,et al.  Interpretations of alternative uncertainty representations in a reliability and risk analysis context , 2011, Reliab. Eng. Syst. Saf..

[4]  Joseph Andrew Clarke,et al.  Applying uncertainty considerations to energy conservation equations , 2007 .

[5]  W. Beckman,et al.  Solar Engineering of Thermal Processes , 1985 .

[6]  I. N. Egorov,et al.  Stochastic Optimization of Parameters and Control Laws of the Aircraft Gas-Turbine Engines – A Step to a Robust Design , 2002 .

[7]  Niels C. Lind,et al.  Methods of structural safety , 2006 .

[8]  Jose Manuel Cejudo-Lopez,et al.  Uncertainty in peak cooling load calculations , 2010 .

[9]  Carl-Eric Hagentoft,et al.  Reliability analysis in building physics design. , 2008 .

[10]  Ren-Jye Yang,et al.  Design for six sigma through robust optimization , 2004 .

[11]  Alain Finkel,et al.  World Scientific Publishing Company , 2013 .

[12]  Henrik Brohus,et al.  Application of sensitivity analysis in design of sustainable buildings , 2009 .

[13]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[14]  D. G. Robinson A survey of probabilistic methods used in reliability, risk and uncertainty analysis: Analytical techniques 1 , 1998 .

[15]  Jon C. Helton,et al.  Survey of sampling-based methods for uncertainty and sensitivity analysis , 2006, Reliab. Eng. Syst. Saf..

[16]  Harvey M. Wagner,et al.  Global Sensitivity Analysis , 1995, Oper. Res..

[17]  Ramana V. Grandhi,et al.  Reliability-based Structural Design , 2006 .

[18]  André I. Khuri,et al.  Response Surface Methodology and Related Topics , 2007 .

[19]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[20]  Paul Strachan,et al.  Practical application of uncertainty analysis , 2001 .

[21]  William H. Press,et al.  Numerical Recipes: FORTRAN , 1988 .