A new method for simulation-based sensitivity analysis of building efficiency for optimal building energy planning: a case study of Iran

Abstract

This work provides a Simulation-Based Sensitivity Analysis (SBSA) framework for optimal building energy planning during the conceptual design phase. The innovative approach integrates EnergyPlus with local sensitivity analysis (LSA) and global sensitivity analysis (GSA) algorithms, thereby facilitating direct sensitivity analysis (SA) capabilities without reliance on external plugins or third-party tools. The effectiveness of this approach is exemplified through its application to a residential building situated in a hot semi-arid climate region of Iran. The efficacy of the developed approach is demonstrated by applying it to a residential building located in a hot semi-arid climate region in Iran. The study utilizes four primary building performance criteria as output variables: annual heating energy consumption (AHC), annual cooling energy consumption (ACC), annual lighting energy consumption (ALC), and the predicted percentage of dissatisfied (PPD). The study employs one-at-a-time (OAT) analysis for LSA and Sobol’s analysis for GSA to investigate the behavior of output variables in response to changes in building design parameters. In the LSA approach, a newly developed sensitivity indicator, termed the Dispersion Index (DI), is introduced to precisely measure the overall sensitivity of outputs to inputs (

S_T

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). Results indicate that annual AHC is most sensitive to the heating setpoint (

S_T

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= 80%) and solar absorptance of exterior walls (S_T = 79%), while annual cooling consumption (ACC) is primarily influenced by the cooling setpoint (

S_T

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= 72%) and solar absorptance of exterior walls (S_T = 63%). Additionally, window-to-wall ratio (WWR), visible transmittance of window glass, and building rotation significantly affect annual lighting consumption (ALC) (S_T = 33%, 25%, and 21% respectively). Furthermore, cooling and heating setpoints, solar absorptance of exterior walls, and WWR play crucial roles in PPD (S_T = 81%, 40%, 36%, and 21% respectively). Notably, ALC shows no dependence on variable air volume (VAV) setpoint temperatures and thermophysical properties of walls and windows. Besides, the proposed DI in OAT-based LSA shows strong alignment with the results achieved by the Sobol-based GSA. This systematic approach, termed SBSA, empowers building designers and decision-makers to pinpoint critical design parameters early in the conceptual phase, ensuring optimal building performance. The flexibility of the SBSA framework accommodates diverse building configurations, facilitating comprehensive SA without constraints.

Keywords

Sensitivity analysis / Integration framework / OAT analysis / Sobol’s analysis / Building performance

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The Joint Center on Global Change and Earth System Science of the University of Maryland and Beijing Normal University