EFRI-SEED: Risk Conscious Design and Retrofit of Buildings for Low Energy

EFRI-SEED研究的目的是识别和量化在不同系统尺度和不同模型类型下影响建筑性能的参数的不确定性分布。本研究将分析和归纳参数分布，并将其与建筑类型、年龄、系统设计、建筑设计特征、形态参数、技术的实验性质、城市背景和居住者组织类型相关联。建筑性能不确定性的不同来源将被仔细描述和统计验证。使用来自240个监测建筑物的数据，将在五个不同的系统尺度上进行不确定性的建模和校准：气象-城市-建筑系统-居住者。它们对结果的影响将与城市和建筑设计参数相关，例如空间和包络复杂性。这项工作将提供理论和模型来支持这种方法，并将在两个受到公众强烈关注的应用中证明这一点：（1）大规模能源改造，（2）净零能源建筑（NZEB）的设计。此外，它将开发一种环境，在这种环境中，拟议的能源系统可以在不确定的情况下在整个建筑规模上进行基准测试。该环境将提供给其他获奖的EFRI-SEED项目，以测试他们的系统在现实生活中，不确定的系统属性和条件下。这将从当前通常基于单一最佳估计预测的有缺陷的决策制定中消除有害的障碍。业主会要求更好的保证，一定的预测节能将完成。 所提出的方法将具体说明不确定性如何影响决策，以及如何以风险意识的方式判断额外投资和节能之间的权衡。 这项研究需要建筑建模和仿真专家，系统设计理论家，统计学家，建筑和城市设计师，能源技术专家和审计专家之间的高度跨学科的方法。研究团队结合了所有这些学科。来自GT校园三个不同研究实验室（建筑，机械工程，工业和系统工程）的学生将在他们的研究生和研究生教育中受益于这个跨学科的组成部分。该教育计划旨在培养一批在计算能源建模、建筑设计理论与实践、统计方法、系统工程和数值分析等方面具有扎实背景的学生。2010财年支持该项目的EFRI-SEED主题由美国国家科学基金会（NSF）工程理事会（ENG）赞助，数学和物理科学（MPS）和社会，行为和经济科学（SBE），计算机&信息科学与工程与美国能源部（DOE）和美国环境保护署（EPA）合作。

The objective of this EFRI-SEED research is to identify and quantify uncertainty distributions of parameters affecting building performance at different system scales and in different model types. The research will analyze and generalize the parameter distributions and correlate them with building type, age, system design, architectural design characteristics, morphological parameters, experimental nature of technologies, urban context, and type of occupant organization. The different sources of uncertainty in building performance will be carefully characterized and statistically validated. Using data from 240 monitored buildings, the modeling and calibration of uncertainties will be conducted at five distinct system scales: Meteorological-Urban-Building-System-Occupant. Their effect on outcomes will be correlated to urban and architectural design parameters, such as spatial and envelope complexity. This work will provide the theory and models to support this approach and will demonstrate this in two applications which are receiving strong public interest: (1) a large scale energy retrofit, and (2) design of a net-zero energy building (NZEB). In addition, it will develop an environment in which proposed energy systems can be benchmarked at whole building scale under uncertainty. This environment will be offered to other awarded EFRI-SEED projects to test their systems under real-life, uncertain system properties and conditions.A new approach to the design of low-energy buildings and energy retrofits is offered. This will remove a detrimental barrier from current deficient decision making typically based on single best estimate predictions. Owners will ask for better guarantees that a certain predicted energy saving will be accomplished. The proposed approach will specifically show how uncertainty influences decisions and how tradeoffs between extra investments and energy saving can be judged in a risk-conscious way. This research requires a highly interdisciplinary approach between building modeling and simulation experts, systems design theorists, statisticians, architectural and urban designers, energy technologists, and auditing experts. The research team combines all of these disciplines. Students from three different research labs on the GT campus (in Architecture, Mechanical Engineering, and Industrial and Systems Engineering) will profit from this cross-disciplinary component in their graduate and postgraduate education. The education plan in the proposed effort will result in rigorous training of a diverse group of students with solid backgrounds in computational energy modeling, architectural design theory and practice, statistical methods, systems engineering, and numerical analysis.The FY 2010 EFRI-SEED Topic that supports this project was sponsored by the US National Science Foundation (NSF) Directorates for Engineering (ENG), Mathematical and Physical Sciences (MPS) and Social, Behavioral and Economic Sciences (SBE), and Computer & Information Science and Engineering in collaboration with the US Department of Energy (DOE) and the US Environmental Protection Agency (EPA).