Data-driven optimization of light commercial buildings' operation

拟议中的项目将在康科迪亚大学的研究人员和总部位于蒙特利尔的专注于建筑自动化的斯特拉托自动化公司之间建立合作关系。它旨在通过整合先进的控制策略，开发一个整体的工作流程来优化轻型商业建筑的运行。更具体地说，它将专注于1)为自动故障检测和诊断（AFDD）创建新的算法，利用数据挖掘来识别故障操作；2)开发易于部署的基于模型的预测控制算法（MPC），以优化能源使用和峰值需求，基于前一天的天气预测。最终目标将是扩展行业合作伙伴的Strato轻型商业（SLC）系统的能力，以优化轻型商业建筑的运行。鉴于2019冠状病毒病后前所未有的远程工作转变，这将为整个加拿大经济带来切实的好处。这种戏剧性的转变很可能会持续下去，这就是为什么优化轻型商业建筑的运营受到极大关注的原因。通过访问北美数百个商业建筑，合作伙伴组织将利用这项研究的结果来补充他们现有的使用SLC的智能建筑控制解决方案和算法库。最终，这些解决方案将加强他们在高效和数据驱动的楼宇自动化领域的全球领导者地位。研究成果也可以很容易地以最小的资本成本部署在加拿大超过50万的商业建筑中，这些建筑的总能耗超过850 PJ。此外，这种合作关系将为高素质人才（HQP）提供一个获得相关行业经验的独特机会，使他们能够充分了解建筑系统和控制技术。他们将处理来自真实建筑的数据，并与他们的系统和组件进行交互，同时获得将建筑工程与数据科学相结合的跨学科研究技能；这两者都是加拿大建筑业迫切需要的。

The proposed project will establish a partnership between researchers at Concordia University and Strato Automation, a Montreal-based company focusing on building automation. It aims to develop a holistic workflow for optimizing the operation of light commercial buildings by integrating advanced control strategies. More specifically, it will focus on 1) creating new algorithms for automated fault detection and diagnostics (AFDD) that leverage data-mining to identify faulty operations, and 2) developing easily deployable model-based predictive control algorithms (MPC) to optimize energy use and peak demand, based on day-ahead weather predictions. The ultimate goal will be expanding the capabilities of the industry partner's Strato Light Commercial (SLC) system to optimize the operation of light commercial buildings. This will provide tangible benefits to the Canadian economy at large, given the unprecedented shift to remote working in the aftermath of COVID-19. This dramatic shift is likely here to stay, which is why optimizing the operation light commercial buildings is gaining significant interest. With access to hundreds of commercial buildings across North America, the partner organization will leverage the outcomes of this research to complement their existing libraries of solutions and algorithms for smart building controls using SLC. Ultimately, these solutions will strengthen their position as a global leader in Efficient and Data-Driven Building Automation. Research outcomes can also be easily deployed at minimal capital cost in many of Canada's over half a million commercial buildings, which collectively consume over 850 PJ of energy. Furthermore, this partnership will provide Highly Qualified Personnel (HQP) with a unique opportunity to gain relevant industry experience that will allow them to fully understand building systems and controls technologies. They will work with data from real buildings and interact with their systems and components, while gaining interdisciplinary research skills combining building engineering with data science; both of which are strongly and urgently needed in the Canadian building industry.