Data-driven optimization of light commercial buildings' operation

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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.