Decision Support Tool for Optimizing the Energy Efficient of Buildings

加拿大的建筑行业一直在为智能建筑开发自动化技术。在单个建筑层面，楼宇自动化系统（BAS）是智能建筑的关键技术。这些系统监视和控制建筑系统，产生大量数据。虽然这些数据嵌入了关于建筑动力学的导入和关键信息，但很少有分析以获得对建筑系统的彻底理解。目前的决策支持系统大多基于先验知识，通常由一大堆方程和经验关系来表示，没有足够的关于实际系统的知识，这些知识可以通过分析运行数据和自我学习过程在线获得。本研究旨在探讨如何最好地理解BAS运行数据中嵌入的信息**，以及如何利用这种理解来优化建筑的运行。**在项目中，我们将整合一个模型，可以从数据采集**系统中彻底分析BAS的运营数据，为楼宇管理人员提供优化楼宇运营的工具。我们的工作将有以下新颖的贡献：(1)决策支持系统将能够关联不同的动态和静态变量，为优化提供建议。(2)决策支持系统，也将能够量化滞后或延迟的建筑参数之间的因果关系。(3)允许楼宇管理人员模拟预测的绩效措施作为干预的结果。简而言之，这个研究项目可以增加合作公司在建筑行业的竞争优势，从而在保护环境的同时为加拿大的经济做出贡献。此外，这个项目也将是一个非常有用的平台，为学生（HQP）提供实际的就业经验。

The construction industry in Canada has been developing automated technologies for smart buildings.At the**individual building level, Building Automation Systems (BAS) is a key technology for smart buildings. These**systems monitor and control building systems, generating a huge amount of data. Whilst this data embeds**imported and critical information about the building dynamics, little has been analyzed to obtain thorough**understanding on the building systems.Current decision support systems are mostly based on prior-knowledge,**which is normally represented by a huge set of equations and empirical relationships, without sufficient**knowledge about the actual systems that can be obtained online through analyzing the operational data and a**self-learning process. This proposed research is aimed to investigate how to best understand the information**embedded in BAS operational data and how to use this understanding to optimize the operation of the building.**In the project, we will integrate a model that can thoroughly analyze BAS operational data from data capturing**systems to provide building managers with a tool for optimizing building operations. Our work will have the**following novel contributions: (1) the decision support system will be capable of correlating the different**dynamic and static variables to provide suggestion for optimization.(2) the decision support system, also will**be able to quantify the lagged or delayed cause-effect relationships among the building parameters. (3) allows**for building manager to simulate predicted performance measures as the result of interventions.In a nut**shell,This research project can increase the competitive edge of the collaborating company in the construction**industry thereby contributing to Canada's economy while protecting environment.In addition, this project will**also be a very useful platform to provide students(HQP) with hands on marketable career oriented experience.