Using sensitivity analysis to improve the efficiency of a net-zero energy vaccine warehouse design

A critical step in the design of a Net-Zero Energy building is the reduction of energy consumption, so that consumption can be cost-effectively offset by renewable energy production. In this paper, the researchers present a method to inform the design of Net-Zero Energy buildings through the identification of influential energy efficiency measures. A regression-based global sensitivity analysis is used to quantify the relative importance of both individual design parameters and bilinear interactions between parameters. This allows for the identification of the specific two-way interactions between parameter pairs, rather than an evaluation of the influence of interactions for each parameter in a lumped manner as is commonly used in building performance simulation. The relative importance of both building control and architectural design parameters are assessed, and are used to help evaluate the importance of utilizing an integrated design method for reducing building energy consumption. The case-study building investigated is a primary vaccine warehouse, a vital part of the vaccine cold chain in the developing world. As this building type has not received adequate attention in the field of building performance simulation, this paper makes a significant contribution towards an improved understanding of the energy efficient design of these warehouses.