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Sensitivity analysis for robust design of building energy systems

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  • Ashouri, Araz
  • Petrini, Flavio
  • Bornatico, Raffaele
  • Benz, Michael J.

Abstract

The comprehensive design of building systems incorporates the tasks of selection, sizing and control of devices. A simultaneous acquirement of these tasks is a necessity to achieve an overall optimal design. However, such mutual optimizations become a complex problem, implying a high computational effort. A greater challenge appears once the uncertainties of boundary conditions such as weather conditions, user demands and energy costs are taken into account. A common approach to protect the suggested system configuration against the possible uncertainties is a stochastic optimization which results in a robust design.

Suggested Citation

  • Ashouri, Araz & Petrini, Flavio & Bornatico, Raffaele & Benz, Michael J., 2014. "Sensitivity analysis for robust design of building energy systems," Energy, Elsevier, vol. 76(C), pages 264-275.
    • Handle: RePEc:eee:energy:v:76:y:2014:i:c:p:264-275
    DOI: 10.1016/j.energy.2014.07.095
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    7. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    8. Majewski, Dinah Elena & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "TRusT: A Two-stage Robustness Trade-off approach for the design of decentralized energy supply systems," Energy, Elsevier, vol. 118(C), pages 590-599.
    9. Yokoyama, Ryohei & Tokunaga, Akira & Wakui, Tetsuya, 2018. "Robust optimal design of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 153(C), pages 159-169.
    10. Cheng, Qi & Wang, Shengwei & Yan, Chengchu & Xiao, Fu, 2017. "Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings," Applied Energy, Elsevier, vol. 185(P2), pages 1613-1624.
    11. Cheng, Qi & Wang, Shengwei & Yan, Chengchu, 2017. "Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability," Energy, Elsevier, vol. 118(C), pages 489-501.
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