Utilities discuss IPE plans and AI impacts on California's distribution grid

The California Public Utilities Commission convened the 2025 Distribution Forecasting Working Group on June 2, 2025, to discuss critical updates and projections regarding the state's energy distribution landscape. The meeting focused on embedded and unknown loads, emphasizing the need for updated forecasting to reflect anticipated changes in energy demand.

The session began with a review of the current forecasting processes, highlighting that the existing models have not been updated to account for potential new loads expected this year, similar to those observed in the previous year. Participants expressed interest in revising these models to better capture the evolving energy landscape.

Barney, a representative from the Integrated Planning and Evaluation (IPE) team, presented plans that are set to be filed and served within the week. Stakeholders were encouraged to provide feedback, which will be incorporated into the revised IPE plans due for redistribution by August 15.

The meeting then transitioned to a discussion led by Yi Lee from San Diego Gas & Electric (SDG&E) regarding the joint Integrated Resource Planning (IRP) forecast scenario proposal for 2025-2026. Yi outlined the local reliability scenario, which is designed to address specific distribution planning needs. Notably, the proposal included a shift from the AFS4 scenario to AFS3, which reflects a more conservative approach to forecasting future loads, particularly in light of the anticipated impact of electric resistance water heaters.

Questions from attendees focused on the rationale behind selecting AFS3 over AFS4, with explanations highlighting the potential for underestimating future demands if higher efficiency appliances are assumed to dominate the market. The discussion underscored the importance of accurately representing customer needs in the context of electrification trends.

As the meeting progressed, participants raised concerns about the implications of artificial intelligence (AI) on power demand and distribution forecasting. While some utilities indicated that the majority of AI-related loads would likely impact transmission rather than distribution systems, the potential knock-on effects on distribution were acknowledged as a relevant concern.

The meeting concluded with an open forum for additional questions and discussions, allowing stakeholders to address cross-cutting topics or revisit earlier subjects. Overall, the session provided a comprehensive overview of the current state of distribution forecasting in California, emphasizing the need for ongoing collaboration and adaptation in response to emerging energy demands.