Yizhi Yang, Yingli Lou, Chris Payne, and Yunyang He have developed a model to “comprehensively assess the long-term carbon intensity reduction potential of aggregated commercial buildings on a county-by-county basis in the continental U.S.” Yizhi Yang is a current PhD student in the SBS Lab, and Yingli Lou and Yunyang He are lab graduates. Their paper summarizing the model and its application to U.S. K-12 buildings has been published in the Energy and Buildings Journal and is available for free until March 11, 2023.
Their case study weighed the effects of climate, energy sources, and building retrofits on K-12 buildings in 14 different climate zones from 2022 to 2050. By considering these effects simultaneously, they were able to predict what retrofits would be most effective and when; for example, they predicted that in 2022 reducing lighting power density in Oregon schools would most effectively increase energy savings, but in 2050 improving roof insulation will be a more effective energy saver because Oregon will have transitioned to clean energy sources for the majority of their electricity. They also concluded that there was a wide range of energy-saving potential across schools and that, depending on the primary energy source, energy savings potentials are not guaranteed to decrease (the example of this phenomenon being Mississippi’s predicted 2044 nuclear plant shutdown, which might be replaced with coal and natural gas plants.)
This case study demonstrates the capabilities of the author’s model, which can help policymakers, engineers, and community members estimate the impacts of different retrofits on buildings in their communities. Future work includes considering future weather predictions in the model, potential policies such as a carbon tax, and increasing the accuracy of buildings estimated in the model with building codes and climate zone geometrical information for climate reduction.
You can read the paper here: https://lnkd.in/efqdSVTr
