US Regional Transmission Organization (RTO) Southwest Power Pool (SPP) has approved an accelerated pathway for large load users, including data centers, to connect to the grid.

SPP’s High Impact Large Load will establish a 90-day study-and-approval process for interconnecting large loads that will be paired with new generation - either on-site or nearby - or for interconnecting large loads with current or planned generation.

In addition, load interconnections will be accelerated through integrated design, study, registration, and operations.

The RTO claims that the new process will provide developers with key benefits, including faster market entry and enhanced price signals, which will allow these loads and supporting generation to have more confidence in expected costs and timelines.

According to the SPP, the new policy was developed following months of collaboration among stakeholders, with a primary focus on addressing the challenges of connecting customers with large power demands, particularly those driven by AI data centers, while balancing reliability and affordability for other customers.

”I’m very pleased we’ve adopted a policy that addresses an urgent need and opportunity in the SPP region,” said board member Stuart Solomon. “I appreciate SPP’s quick work to develop an innovative proposal and our members’ and Regional State Committee’s active participation in refining it. This is a great example of our stakeholder process at its best, and I’m confident we now have an excellent approach to meeting the needs of our members and large-load customers looking to locate in the SPP region.”

The SPP is one of seven US RTOs. It manages the electric grid and wholesale power market for the central US, serving all of Kansas and Oklahoma, and sections of Montana, Arkansas, Iowa, North Dakota, Texas, Nebraska, South Dakota, Missouri, Wyoming, Minnesota, Louisiana, and New Mexico.

Earlier this year, the RTO partnered with Hitachi to develop an Nvidia-powered artificial intelligence solution that reduces the duration of interconnection impact studies. The integrated AI-based solution is expected to reduce the length of time it takes for the studies from 18 to 27 months to less than 12 months.