Machine Learning Technology to Help Manage Energy Operations of C&I Buildings

by | Nov 6, 2019

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Verdigris Technologies, developers of Artificial Intelligence (AI) solutions, has partnered with Global Electrification company, ABB, bringing Verdigris’s machine-learning applications to ABB’s global line of connected low-voltage switching fabric products to predict unplanned surges in power consumption for commercial and industrial buildings. The electrical equipment, power, robotics and automation company is launching a new digital energy app-store and Verdigris’s AI technology is their first app.

Through both internal and field studies with ABB, Verdigris demonstrated near-range energy forecasts with greater than 90% accuracy, useful in demand management applications, and outperformed common open-source forecasting alternatives.

According to the US Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, connected sensor networks and advanced monitoring and analytics combined with adaptive and autonomous controls have a technical potential to save a wasted 3.31 quads of energy or $43 billion annually. Using EPA’s US average electricity source emissions data published in 2018, these figures represent an opportunity to curb 270 million metric tons of GHG annually by 2030 in just US commercial building stock alone.

According to Verdigris, DOE Studies show with accurate sensing and predictive analytics we can reduce building energy consumption by up to 30%. With AI we have the building blocks to go further in developing adaptive and autonomous buildings, and eventually optimize networked fleets of generators, energy storage systems, EV infrastructure and smart buildings.

Further collaboration between ABB and Verdigris to advance AI capability on electrical infrastructure are planned.

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