In February, Reactive Technologies participated in the NERC Emerging Large Loads Technical Conference, held on February 24–25, 2026 in Arlington, Virginia. The conference brought together grid operators, utilities, regulators, and technology providers to examine how the rapid growth of large electricity loads, particularly AI-driven data centers, is reshaping reliability considerations for the bulk power system.
The event focused on one central question: how can the grid reliably integrate rapidly growing computational loads while maintaining stability and operational visibility?
During the conference, Dr. Diego Rodriguez, Technical Solutions Lead at Reactive Technologies, joined a panel discussion alongside industry experts including Mark Lauby of NERC, as well as representatives from PJM, Constellation, NATF and Equinix.
The panel explored the reliability implications of large-load integration and the operational challenges this creates for grid operators.
A key discussion during the panel was the growing need for closer collaborations between stakeholders including data center operators, utilities and regulators. Historically this level of co-ordination has often been limited. However, as large computational loads introduce faster and more complex demand patterns, the industry is entering a new phase where stronger collaboration and better visibility across stakeholders will be essential to support reliable grid operation.
Diego Rodriguez, Technical Solutions Lead said,
“Large computational loads are introducing faster and more complex behaviors to the power system. High-resolution system visibility is becoming essential for maintaining reliability. This is particularly important because high-frequency oscillations can signal the early stages of instability, and detecting small oscillations early can help prevent wider system disturbances.“
As system challenges continue to evolve, we look forward to ongoing collaboration across the power sector to better understand emerging risks and support reliable grid operations.
