Design and control of grid-responsive communities

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The proposed research program aims at supporting the transformation of building design by developing integrated methodologies to optimize the design and operation of grid-responsive, energy efficient communities with on-site renewable energy generation. Grid responsiveness is the ability of Integrated Community Energy Systems (ICES) and of the buildings within a community to adapt their power demand to reduce peak loads or maximize the use of renewable energy, thereby playing an active role in a smart electric grid. This grant application focuses on two main objectives: 1) modeling of advanced Integrated Community Energy Systems; and 2) design and operation strategies for grid-responsive communities.***1) Modeling***Grid-responsive communities include complex, hybrid ICES based on novel HVAC components, which poses significant challenges to existing simulation tools. Different models are required: online (real-time) predictive control requires computationally efficient models well suited to online parameter identification, while detailed design models should be based on physical principles and/or measured performance data. Two sub-projects will address the challenge of combining these model requirements. Laboratory facilities and data from real systems will be used to inform and validate the models which will be implemented in the appropriate tools for design, development of control strategies, and online control. ***2) Design and operation strategies***The conventional approach of optimizing energy system design using basic control rules and then optimizing control strategies for a given design cannot leverage synergies between different objectives such as energy efficiency, resilience, and grid-responsiveness. An integrated methodology will be developed to optimize the design and operation of buildings and integrated energy systems, using the most appropriate modeling resolution. The project will deliver model-based predictive control strategies capable of taking into account real-time data and forecasts for the weather, occupant behavior and energy prices. Our work has shown that this cannot be achieved through incremental improvements to existing methods, and a novel approach will be developed and integrated within the design optimization process. ***Anticipated impact***The research projects will be performed in close collaboration with industry, building on previous successful collaborative projects. They will also strive to bridge the disciplinary divide between architects and engineers by involving the trained HQP in multidisciplinary collaborations with university and industry. This will benefit Canada by advancing and transferring the knowledge required to enable the next generation of high performance integrated community energy systems and by training HQP capable of contributing their expertise in a multidisciplinary context.