A case study for sensitivity-based building energy optimization
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Date
2019-05-26
Journal Title
Journal ISSN
Volume Title
Publisher
ARCC Conference Repository
Abstract
Building design optimization process is associated with uncertainties due to
climate change, unpredictable occupant behavior, and physical degradation of building
material over time. The inherent uncertainties in the design process reduce the reliability and
robustness of the optimal design solution(s) and affect design decision-making results. This
research studies the capabilities of parametric design tools in adopting probabilistic methods
to handle uncertainties in building performance optimization. Variance-based methods, e.g.,
Monte Carlo sensitivity analyses are implemented to identify the most critical parameters in
design optimization problems and improve the efficiency of design optimization. The optimal
solutions achieved with variance-based methods are satisfying the design objectives more
efficiently, also remain robust to changes and uncertainties.
Description
Keywords
Building design optimization, Variance-based methods, Parametric design, Sensitivity analysis, Monte Carlo
Citation
Shahsavari, F., Yan, W., & Koosha, R. (2019). A Case Study for Sensitivity-Based Building Energy Optimization. ARCC Conference Repository, 1(1). Retrieved from https://www.arcc-repository.org/index.php/repository/article/view/644