A three-stage decision-making process for cost-effective passive solutions in office buildings in the hot summer and cold winter zone in China

China, with the largest energy consumption system in the world, faces numerous challenges in achieving the government's commitment to reach a carbon-peak and carbon-neutral target. As the most common public building type in terms of floor area, office buildings have great potential for energy saving and emissions reduction. To meet this target, building designers target passive solutions that can meet the thermal comfort needs of occupants and also reduce energy consumption. This study aims to develop a decision-making method to select optimal solutions from among tens of thousands of design options considering the factors of energy consumption, comfort, and cost. We developed a novel optimization decision approach with the above-mentioned three objectives. The model consists of three stages: 1) the establishment of the reference building model, 2) sensitivity analysis to identify the main influencing variables and 3) the establishment of the optimization and decision-making model by applying NSGA-II and TOPSIS methods. By applying this three-stage decision-making model, this paper first proposes costeffective passive design solutions for office buildings throughout the Hot Summer and Cold Winter climate zone. Finally, an office building in Shanghai was chosen as a case study to demonstrate the practical implementation of the proposed solutions through a post-occupancy evaluation with a two-year energy auditing and thermal comfort survey. It is evident that the proposed solutions provide support for the new low energy building design guide for office buildings along with necessary revisions to the existing standards for the Hot Summer and Cold Winter climate zone in China. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This study aims to develop a decision-making method to select optimal passive design solutions for office buildings that can meet occupants' thermal comfort needs and reduce energy consumption. By establishing a decision model and applying advanced optimization techniques, the study proposes cost-effective design solutions and validates them through a case study in Shanghai.