GU301: Navigating AI Data Center Interconnection: From System Impact to Mitigation Solutions

The rapid growth of AI data center loads can introduce grid reliability and power quality risks to both grid-connected and islanded power systems. These loads are characterized by fast, large-magnitude, and repetitive power swings that can cause power quality issues, challenge ride-through requirements, excite oscillatory interactions with nearby generation plants, and destabilize microgrids serving co-located or off-grid data center campuses. This tutorial examines these risks from multiple stakeholder perspectives, spanning power system studies, technology solutions, utility/TSO requirements, and data center development needs. This tutorial is structured as a problem-to-solution session, guiding participants from the underlying behavior of AI loads and the risks they present, through interconnection study requirements and case studies that quantify their impacts, to practical mitigation options such as BESS, STATCOM, and Enhanced STATCOM, as well as other emerging technologies, including Enhanced UPS, thyristor-controlled load banks, and rack-level storage. The session concludes with a practical framework for identifying AI load-driven grid risks and selecting appropriate mitigation strategies.

Takeaways

• Summary of practical framework for identifying the risks from AI load and selecting appropriate mitigation strategies
• Mitigating Impact of AI Data Center Load (Examples of how BESS and E-STATCOM can be used whether individually or coordinated)

Session Sponsored by Hitachi