arrow
Return

Building simulation: Ten challenges

delete2018-04-12
delete154
delete
OA
AI
T
Tianzhen Hong *
J
Jared Langevin
K
Kaiyu Sun
DOI:10.1007/s12273-018-0444-xdelete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Buildings consume more than one-third of the world's primary energy. Reducing energy use and greenhouse-gas emissions in the buildings sector through energy conservation and efficiency improvements constitutes a key strategy for achieving global energy and environmental goals. Building performance simulation has been increasingly used as a tool for designing, operating and retrofitting buildings to save energy and utility costs. However, opportunities remain for researchers, software developers, practitioners and policymakers to maximize the value of building performance simulation in the design and operation of low energy buildings and communities that leverage interdisciplinary approaches to integrate humans, buildings, and the power grid at a large scale. This paper presents ten challenges that highlight some of the most important issues in building performance simulation, covering the full building life cycle and a wide range of modeling scales. The formulation and discussion of each challenge aims to provide insights into the state-of-the-art and future research opportunities for each topic, and to inspire new questions from young researchers in this field.
Keywords:
building energy use
energy efficiency
building performance simulation
energy modeling
building life cycle
zero-net-energy buildings
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Building Simulation cover
Building Simulation
IF:
5.9
Papers:
1.6K
Citations:
4.5K

Organization

U
united states department of energy (doe)
Scholars:
11.3W
Papers: 9.6W
Citations: 246
Cited Papers

Cited Papers

Bayesian calibration of building energy models with large datasets
err2017-11-01
err91
errOAAI
errChong, Adrian; Lam, Khee Poh; Pozzi, Matteo; Yang, Junjing
errShare
errSave
errShare
errSave
Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network
err2014-02-01
err274
PREAI
errCai, Baoping; Liu, Yonghong; Fan, Qian; Zhang, Yunwei; Liu, Zengkai; Yu, Shilin; Ji, Renjie
errShare
errSave
Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China
err2017-06-01
err76
errOAAI
errCui, Ying; Yan, Da; Hong, Tianzhen; Xiao, Chan; Luo, Xuan; Zhang, Qi
errShare
errSave
researcher View more