Optimization of the design and operation strategies of sustainable buildings

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The long-term objective of the applicant’s research program is the optimization of the design and operation strategies of sustainable buildings, which maximize the use of renewable energy sources and minimize the life cycle impacts on the natural environment, while offering high quality indoor environment. This is a highly original and innovative research program leading to the development of knowledge and technologies for the design and operation of buildings of the future, with high potential of application by the HVAC industry. The short-term objectives of research activities over the next five years focus on: (1) the ongoing commissioning for the operation of existing heating, ventilation and air conditioning (HVAC) systems in commercial and institutional buildings, and (2) the optimization of the design and operation of solar combisystem (SCS), as a particular case of HVAC systems. The proposed research approach for task 1 comprises the analysis and use of Building Auto,ation System (BAS) trend data from existing HVAC systems for the development of new mathematical models and analysis methods, and the development of an ongoing commissioning prototype tool that integrates the proposed new developments. The benchmark models, forecasting models and virtual sensor models will be developed and tested with measurements from some existing buildings, however, the goal is the development of generic models that could be applied on a large scale to other buildings. For each building, the new training data set will be used for the identification of model parameters. Task 2 covers the improvement of SCS optimization methods, and the coupling of new optimization methods with a detailed energy analysis program for assessing the systems’ performance, and finally the selection of optimum SCS configuration at different locations in Canada. Under the first objective the following tasks will be undertaken: (1.a) the development of benchmarks of the performance of HVAC systems, (1.b) the forecasting of electric demand for the demand response control strategy, (1.c) the development of a library of virtual sensors for the HVAC system, and (1.d) the development of the Automated Assistant for Ongoing Commissioning and Calibration. Under the second objective the following tasks will be undertaken: (2.a) the optimization of the configuration of SCS, and (2.b) the development of improved optimization methods.