Do you think that to be a driving force to battle climate change and other global challenges, the modelling community should focus more on existing buildings rather than the design of new ones? How can we target the vast majority of buildings built with the standard practice rather than fancy glazed skyscrapers with high green ratings built for <1% of the population?
-A Hypocritical Modeller
Dear Hypocritical Modeller,
As many readers might agree, buildings are a critical component of a sustainable, low-carbon future. In 2019, 28% of all primary energy consumption (and subsequent carbon emissions) in the United States came from our buildings (International Energy Agency). And while there are emerging policies that emphasize the importance of energy efficiency in newly constructed buildings (California Public Utilities Commission), up to two-thirds of the building area that exists today will exist in 2050 – buildings whose efficiencies are constrained by aging equipment, poor infrastructure, and inadequate operations and maintenance. It is well established that existing buildings can achieve energy savings of up to 50-75% through deep energy retrofits (IPCC). And so, if we want to achieve the ambitious carbon reductions targets set by policymakers around the world under the threat of climate change, it is critical we leverage the power of energy modelling tools to understand how retrofits can improve the energy efficiency of our existing building stock.
However, a key question remains: out of the thousands of buildings that make up a single city, how can we determine which ones are best for retrofitting? I believe this challenge is best met through a two-pronged, interdisciplinary approach – the combination of data science and energy modelling. Over the last couple decades, an enormous amount of sensing technologies has been deployed to help understand the performance of the built environment. Annual energy data is used to “benchmark” buildings to identify inefficient buildings (e.g., NY Local Law 84), empowering policymakers with better information on which buildings would benefit most from retrofits. More recently though, smart meter energy data allows building energy performance to be measured at smaller time intervals, like daily performance, helping differentiate buildings that would benefit from specific types of retrofits. From there, we can more effectively rely on energy models created for specific buildings to determine an optimal retrofit program to improve overall energy efficiency.
Finally, in order for the vast majority of buildings to see energy efficiency improvements, we need to ensure the removal of barriers and the implementation of effective policies and incentive structures. Many of these barriers such as split incentives, industry fragmentation, and inadequate access to financing still remain today and limit the potential for the uptake of retrofit opportunities. However, through measures such as effective building codes (e.g., California Title 24) and appliance standards, financing instruments (e.g., PACE financing, energy service performance contracting), and technological improvements – these approaches can assist in making our existing building stock more energy efficient and thus help the battle in mitigating climate change.
Alex Nutkiewicz, M.S.
PhD Candidate, Stanford Urban Informatics Lab
alexer@stanford.edu
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