For industrial facilities, optimizing energy use can be a complex puzzle of managing production demands and distributed energy resources. The latest artificial intelligence (AI) technologies for energy management can transform this puzzle into a competitive advantage.
As the energy transition advances, could AI be the solution to industries’ top challenges?
ABB’s recent survey of European electrification decision makers highlighted the difficulties of energy management such as combining power from multiple sources and demand forecasting and management.
AI-powered energy management solutions solve for a maze of interconnected variables inside and outside the walls of an industrial site. Today’s analytical tools forecast everything from production energy demands and energy pricing, to weather and renewable energy generation.
“Companies that use AI analytical tools will have the best outcomes on resilience, operational costs and decarbonization,” Wise said.
ABB Electrification is partnering with startups to accelerate delivery of AI-powered energy management solutions for managing both energy demand and supply.
Managing demand: improving efficiency and cost savings
The pathway to energy savings starts with understanding when and how energy is being used. AI-driven solutions help industrial facilities gain this understanding to reduce usage and effectively manage peak demand.
For example, ABB Electrification partners with Ndustrial, a startup whose unique AI-driven energy management solution brings industrial customers precise visibility to the energy intensity of their production.
“Ndustrial integrates with systems across an industrial site to turn energy costs into tangible insights,” Wise said. “Customers gain precise visibility to the amount of electricity used for each unit coming off a production line. “
By integrating data on weather, market rates, equipment performance, industrial process outputs and more, companies can analyze, optimize and predict their energy usage and production costs. This enables real-time decisions and automated controls specific to the industry, facility or production line being optimized.
Genan, the world’s largest mechanical tire recycling company, saved hundreds of thousands of dollars by using Ndustrial’s automated response to energy pricing. Genan was able to quickly stop production when energy pricing exceeded a set threshold.
Turning energy supplies into an advantage
When it comes to powering operations, industrial sites face many decisions: how to use energy generated by renewables, when to charge or discharge battery storage, and when to buy or sell electricity to the grid. With the right strategy, companies can save energy costs and possibly generate revenue.
AI-powered solutions apply forecasting models for weather, energy market pricing, and production needs to devise real-time strategies for managing energy supplies. One example is ABB Electrification’s investment in GridBeyond’s AI-powered platform.
“By teaming up with GridBeyond, we offer solutions that combine our hardware and maintenance services with their energy distribution software platform and energy trading capability,” Wise said. “It’s very symbiotic and supports customers in reducing energy costs, or even making money by trading energy back to the grid.”
The advantages of AI-based energy management are expected to grow as adoption continues and forecasting models benefit from even more data.
