Large energy users must ’embrace AI and machine learning’

The boss of an energy technology company has urged business leaders to harness AI and machine learning applications in their energy consumption.

“High energy users must embrace AI and machine learning technology to advance towards a more resilient, flexible and decarbonized grid,” said Michael Phelan, chief executive at GridBeyond, A UK provider of demand side response and energy services for large industrial and commercial firms.

“The energy revolution has been fomenting for a decade, and we are now in the primary phase of action,” he said. “Technological platforms, powered by AI and machine learning, support this revolution by driving the energy systems towards a cleaner, safer, more flexible and more resilient electricity grid.”

Speaking at the FT Digital Energy Summit in London, Phelan explained: “The increase in electricity demand from heat, electric vehicles, electrification of business operations and domestic lifestyles, combined with growing intermittent renewable energy sources, has meant that advanced technology is a necessity both in front of the meter and behind the meter.”

He said that large industrial and commercial energy consumers “play a key role in the revolution of the system and the market, by taking control of their electricity usage, increasing energy efficiency, and participating in National Grid programmes to balance electricity supply and demand”.

“Highly advanced technological platforms enable large energy users to fully control their energy assets and embedded generation, improve production processes and predict and prevent system failures, whilst optimising savings and revenue opportunities”.

READ MORE: Why grid resilience is moving behind the meter

AI, machine learning and grid resilience are all hot topics at European Utility Week in Vienna in November. Click here for details and to register.



No posts to display