Comprehensive Building Performance Monitoring: Supporting Outcome-Based Design and Construction Provisions

全面的建筑性能监控：支持基于结果的设计和施工规定

• 批准号: RGPIN-2016-06324
• 负责人: Touchie, Marianne
• 金额: $ 1.75万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709734
• 关键词: Comprehensive; Building; Performance; Monitoring; Supporting

Building energy use is responsible for 28% of Canada's greenhouse gas emissions. To reduce the environmental impact of buildings as well as improve occupant health and comfort, codes and standards governing building design are becoming increasingly stringent. Compliance with these provisions is assessed before the building is occupied and so we assume buildings perform exactly as designed, but this is not the case. The impact of construction, operation and occupant behavior contribute to a gap between specified and actual performance. This performance gap has serious consequences including impeding regulatory efforts to reduce the environmental impact of buildings, affecting the credibility of high performance building rating systems and creating uncertainty for the owners about building performance and the long-term value of their investment. To eliminate performance gaps, innovative research to further code development is required. Research to support the development of outcome-based energy codes, where compliance is based on actual post-occupancy performance data, is a priority. This outcome-based approach can also be extended to other standards governing occupant comfort and indoor air quality. A key barrier to implementing this regulatory approach is the lack of building performance data. These data, demonstrating the performance resulting from current provisions, are essential to set specific and realistic performance goals for outcome-based approaches. Toronto is in the midst of a housing boom and the largest proportion of new dwellings is currently provided by high-rise condominiums. While built to conform to current provisions, these highly-glazed buildings are uncomfortable for occupants and some buildings are already experiencing performance issues. Given the extraordinary growth and investment in this sector, Toronto's newly constructed high-rise condominiums will be the focus of this research. However, the findings are applicable in urban regions around the globe where population densities are increasing. The aim of the proposed research is to determine the gaps between actual and specified performance of different building components by developing and analyzing comprehensive long-term monitoring data from suite-based sensors and energy sub-meters in case study buildings, to create outcome-based codes and standards. This research will result in data and recommendations to support policy makers with the development of a more robust model of building design based on actual rather than projected performance. Other stakeholders in the design community (energy modelers, engineers and architects) will benefit by having access to component-level performance data on which to base their models. Owners and occupants will benefit from a more comfortable and healthy indoor environment that reliably performs to the level set by codes and standards.

建筑能源使用造成加拿大温室气体排放的28％。 为了减少建筑物的环境影响，并改善居住者的健康和舒适性，管理建筑设计的代码和标准越来越严格。 在建筑物被占用之前，对这些规定进行了遵守，因此我们假设建筑物的性能完全按设计，但事实并非如此。施工，操作和乘员行为的影响导致指定和实际绩效之间的差距。 这种绩效差距会带来严重的后果，包括阻碍监管工作，以减少建筑物的环境影响，影响高性能建筑评级系统的信誉，并使所有者对建筑绩效及其投资的长期价值造成不确定性。 为了消除绩效差距，需要创新的研究以进一步的代码开发。 支持基于结果的能源代码的开发的研究是优先的。 这种基于结果的方法也可以扩展到其他有关居住者舒适和室内空气质量的标准。 实施这种监管方法的关键障碍是缺乏建筑绩效数据。 这些数据证明了当前规定所产生的绩效，对于为基于结果的方法设定特定而现实的绩效目标至关重要。 多伦多正处于住房繁荣之中，而新的住宅中最大的比例是高层公寓提供的。 虽然为符合当前的规定而建造，但这些高层建筑对于居住者来说是不舒服的，一些建筑物已经遇到了绩效问题。 鉴于该行业的非凡增长和投资，多伦多新建的高层公寓将成为这项研究的重点。 但是，这些发现适用于人口密度增加的全球城市地区。 拟议的研究的目的是通过开发和分析案例研究建筑物中基于套件的传感器和能量子仪的全面的长期监控数据，以创建基于结果的代码和标准，来确定不同建筑组件的实际和指定性能之间的差距。 这项研究将导致数据和建议，以基于实际绩效而非预期的绩效开发更强大的建筑设计模型来支持政策制定者。 设计社区中的其他利益相关者（能源建模者，工程师和建筑师）将通过访问组件级的性能数据来利益，以基于其模型。 业主和居住者将受益于更舒适和健康的室内环境，该环境可靠地执行由代码和标准设定的水平。