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Initial Models of Existing Canadian Buildings for Building Energy Code Analysis

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Proceedings of the 5th International Conference on Building Energy and Environment (COBEE 2022)

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Abstract

Policies, programs, and building code updates are being developed to reduce greenhouse gas emissions from existing buildings. To assess their impact, building energy models representing existing Canadian commercial and institutional buildings have been developed and implemented in the Building Technology Assessment Platform (BTAP). The simulated annual energy intensity for existing schools and offices are compared to Ontario public building data for 2011–2017 for several Ontario cities to evaluate how well the models predict actual building energy use. The annual energy use intensity (EUI) of existing schools modeled without ventilation systems (0.51–0.65 GJ/m2/year) compares well against mean Ontario school EUI data (0.67–0.79 GJ/m2/year). The modeled annual EUI of existing offices (0.48–0.79 GJ/m2/year) is lower than the mean of administrative buildings (offices) reported in the Ontario data (1.0–1.3 GJ/m2/year). These existing building models can be used to evaluate the approximate relative impact of policies, codes and efficiency measures on existing building performance.

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Acknowledgements

This project was supported by Natural Resources Canada’s Office of Energy Research and Development under the Greening Infrastructure Fund. The authors wish to acknowledge the contributions of the U.S. National Renewable Energy Laboratory, the Pacific Northwest National Laboratory, and others groups and U.S. national labs to the OpenStudio-Standards project.

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Correspondence to Chris Kirney .

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kirney, C., Gilani, S., Haddad, K., Lopez, P., Lubun, M. (2023). Initial Models of Existing Canadian Buildings for Building Energy Code Analysis. In: Wang, L.L., et al. Proceedings of the 5th International Conference on Building Energy and Environment. COBEE 2022. Environmental Science and Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-9822-5_88

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  • DOI: https://doi.org/10.1007/978-981-19-9822-5_88

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9821-8

  • Online ISBN: 978-981-19-9822-5

  • eBook Packages: EngineeringEngineering (R0)

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