Grid Services and Reliable Energy Operations of Commercial and Industrial Buildings, Which Rank Among the Top Carbon Emitters, Can Be Managed by up to 10-20% Through Energy Forecasting and Intelligent Alerts Applications
Verdigris Technologies, developers of award-winning Artificial Intelligence (AI) solutions, has partnered with Global Electrification leader, 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 Fortune 500 electrical equipment, power, robotics and automation company is launching a new digital energy app-store and Verdigris’s AI technology is their first app.
Excited to see @VerdigrisTech partnering with @ABBelec to reinvent energy management for planetary sustainability.
The joint release of new Energy Forecasting and Intelligent Alerts now available on the ABB Ability™ Digital Marketplace was announced today.
Mark Chung, Verdigris CEO said: “We chose to partner with ABB because they are the leading supplier of electrification products to our core customer segments. This collaboration represents an avenue to accelerate our objectives of meeting growing customer demand for energy resilience and delivering a global-scale coordinated response to the threat of climate change through responsive energy intelligence.”
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.
Andrea Temporiti, Digital Leader for ABB’s Electrification business, said: “Our use of AI to help customers make better energy management decisions demonstrates ABB’s commitment to innovation in our products and quality in our services. With the new Energy Forecasting and Smart Alerts apps, AI drills down into the facility’s power data to pinpoint actionable opportunities for productivity improvements and energy cost savings.”
According to the U.S. 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 $43B 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.
Jonathan Chu, Verdigris CTO said: “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.”