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A review on simulation-based optimization methods applied to building performance analysis

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  • Nguyen, Anh-Tuan
  • Reiter, Sigrid
  • Rigo, Philippe

Abstract

Recent progress in computer science and stringent requirements of the design of “greener” buildings put forwards the research and applications of simulation-based optimization methods in the building sector. This paper provides an overview on this subject, aiming at clarifying recent advances and outlining potential challenges and obstacles in building design optimization. Key discussions are focused on handling discontinuous multi-modal building optimization problems, the performance and selection of optimization algorithms, multi-objective optimization, the application of surrogate models, optimization under uncertainty and the propagation of optimization techniques into real-world design challenges. This paper also gives bibliographic information on the issues of simulation programs, optimization tools, efficiency of optimization methods, and trends in optimization studies. The review indicates that future researches should be oriented towards improving the efficiency of search techniques and approximation methods (surrogate models) for large-scale building optimization problems; and reducing time and effort for such activities. Further effort is also required to quantify the robustness in optimal solutions so as to improve building performance stability.

Suggested Citation

  • Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    • Handle: RePEc:eee:appene:v:113:y:2014:i:c:p:1043-1058
    DOI: 10.1016/j.apenergy.2013.08.061
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    1. Kalogirou, Soteris A., 2004. "Optimization of solar systems using artificial neural-networks and genetic algorithms," Applied Energy, Elsevier, vol. 77(4), pages 383-405, April.
    2. Chantrelle, Fanny Pernodet & Lahmidi, Hicham & Keilholz, Werner & Mankibi, Mohamed El & Michel, Pierre, 2011. "Development of a multicriteria tool for optimizing the renovation of buildings," Applied Energy, Elsevier, vol. 88(4), pages 1386-1394, April.
    3. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    4. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Chunfa, 2010. "Particle swarm optimization for redundant building cooling heating and power system," Applied Energy, Elsevier, vol. 87(12), pages 3668-3679, December.
    5. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    6. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    7. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    8. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    9. Goia, Francesco & Haase, Matthias & Perino, Marco, 2013. "Optimizing the configuration of a façade module for office buildings by means of integrated thermal and lighting simulations in a total energy perspective," Applied Energy, Elsevier, vol. 108(C), pages 515-527.
    10. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    11. Sarker, Ruhul & Liang, Ko-Hsin & Newton, Charles, 2002. "A new multiobjective evolutionary algorithm," European Journal of Operational Research, Elsevier, vol. 140(1), pages 12-23, July.
    12. Diakaki, Christina & Grigoroudis, Evangelos & Kabelis, Nikos & Kolokotsa, Dionyssia & Kalaitzakis, Kostas & Stavrakakis, George, 2010. "A multi-objective decision model for the improvement of energy efficiency in buildings," Energy, Elsevier, vol. 35(12), pages 5483-5496.
    13. Ren, Hongbo & Gao, Weijun & Ruan, Yingjun, 2009. "Economic optimization and sensitivity analysis of photovoltaic system in residential buildings," Renewable Energy, Elsevier, vol. 34(3), pages 883-889.
    14. Rezvan, A. Taghipour & Gharneh, N. Shams & Gharehpetian, G.B., 2012. "Robust optimization of distributed generation investment in buildings," Energy, Elsevier, vol. 48(1), pages 455-463.
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