IN Brief:
- National Grid and GridCARE are working together in New York to identify underused grid capacity for large-load customers.
- The platform uses AI modelling, grid simulations, and real-time system intelligence to find operational headroom.
- The companies say the approach could reduce energisation timelines from several years to as little as six to 12 months in suitable cases.
National Grid is working with GridCARE in New York to identify latent capacity on the existing network and shorten the time needed to connect large-load customers. The collaboration is focused on a part of the U.S. market where power access has become a material factor in decisions around data centres, advanced manufacturing, and other electricity-intensive developments.
GridCARE’s platform combines AI models, grid simulations, and real-time system intelligence to test a very large number of operating scenarios and identify the periods and conditions when the system approaches constraint. The model then applies operational strategies, including batteries and distributed flexibility, to create usable connection headroom without waiting for a full conventional reinforcement cycle.
The companies have said the method could reduce time-to-energisation from several years to as little as six to 12 months in appropriate situations. That does not remove the need for new infrastructure, but it does change the sequence, allowing additional load to connect earlier where hidden or intermittent capacity already exists on the system.
The partnership is set out in a joint announcement that places asset utilisation, affordability, and connection speed at the centre of the project. For utilities facing rapid demand growth, the more immediate question is whether these tools can move from targeted case studies into repeatable interconnection practice.
