Sustainability and Environmental Performance

Smarter Buildings, Cleaner Grid: The Case for Automated Demand Management

noda.ai

Published 2024

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📄 Paper
It’s well recognized that our built environment accounts for roughly 40% of global greenhouse gas emissions. Although this often-cited figure may seem overused, it continues to underscore a key point: operating our existing building stock more intelligently holds immense potential for combating climate change. Within the broader realm of building operations, automated demand management (ADM) is poised to be a game changer for improving energy performance, reducing operational costs, lowering emissions, and enhancing grid stability. But what exactly is ADM, and who stands to gain? At its core, ADM focuses on adjusting buildings’ energy use patterns in direct response to real-time conditions—such as grid load, weather, and the availability of renewable energy. By layering external factors on top of internal operations, commercial real estate teams can extend beyond traditional efficiency approaches and achieve deeper savings, while meaningfully cutting emissions and alleviating grid stress.

Abstract

It’s well recognized that our built environment accounts for roughly 40% of global greenhouse gas emissions. Although this often-cited figure may seem overused, it continues to underscore a key point: operating our existing building stock more intelligently holds immense potential for combating climate change. Within the broader realm of building operations, automated demand management (ADM) is poised to be a game changer for improving energy performance, reducing operational costs, lowering emissions, and enhancing grid stability. But what exactly is ADM, and who stands to gain? At its core, ADM focuses on adjusting buildings’ energy use patterns in direct response to real-time conditions—such as grid load, weather, and the availability of renewable energy. By layering external factors on top of internal operations, commercial real estate teams can extend beyond traditional efficiency approaches and achieve deeper savings, while meaningfully cutting emissions and alleviating grid stress.

Topics

AI for Energy Performance OptimizationCase StudySmart Building Systems and IoT IntegrationSustainable Buildingssmart grids

Cite this paper

@misc{9a0f1354,
  title = {Smarter Buildings, Cleaner Grid: The Case for Automated Demand Management},
  author = {noda.ai},
  year = {2024},
  howpublished = {\url{https://noda.ai/insights/smarter-buildings-cleaner-grid-adm}},
  url = {https://noda.ai/insights/smarter-buildings-cleaner-grid-adm},
  urldate = {2026-08-04},
  note = {Sustainability and Environmental Performance}
}