In a recent episode of Tech Nest: The Proptech Podcast, host Nate Smoyer sat down with Cortex’s Owen Glubiak to discuss the role of technology in decarbonizing commercial real estate. Their conversation covered topics ranging from current carbon regulations, to sustainable transportation, to machine learning applications. Listen now!
Don’t have time? Here are a few key takeaways:
1. Machine learning plays a key role in building performance optimization
One of the primary highlights of Owen Glubiak & Nate Smoyer’s discussion was the critical role of machine learning in enhancing the energy efficiency of buildings. Glubiak emphasized the difficulty of optimizing building performance, pointing to factors like tenant occupancy and weather patterns which significantly influence energy consumption. “AI is a great way to connect the dots… to bring these systems together,” he explained. To maximize energy efficiency and minimize carbon output given these changing factors, building engineers “need an AI tool to help narrow [the flow of information] down so that you can really focus on the things that matter” to improve results.
2. Properties will require building electrification and grid advancements to truly achieve net zero
Decarbonization in commercial real estate hinges on building electrification and grid advancements, as Glubiak pointed out. He noted, “Buildings will need to electrify if we’re going to hit decarbonization goals,” highlighting the inefficiencies of alternatives like fuel switching. The role of the power grid is also crucial, requiring access to renewable sources and improved storage capabilities. “The grid itself is definitely part of this equation,” Glubiak added, underscoring the need for a holistic approach to decarbonization.
3. CRE professionals must find a balance between prioritizing energy management and tenant comfort
A critical aspect of energy management, as discussed by Glubiak, is the “balance between your tenant comfort and your energy performance.” He acknowledged the conflict of interests – where prioritizing comfort often leads to excessive energy use – and suggested that a data-driven approach to this challenge can help balance these two priorities. Engaging building systems at the right time each day limits excessive energy expenditure, and serves occupants by reducing their energy bills while still satisfying agreed tenancy temperature thresholds. Owen argued that asset managers – as financial and environmental stewards entrusted “to optimize the performance of the building” by investors and occupants alike – “need to make sure they are in balance based on data” to avoid both tenant complaints and emissions fines.
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