DOE Report on Electric Reliability

The Department of Energy (DOE) recently released their report: “Evaluating the Reliability and Security of the United States Electric Grid.”

This report and associated analysis were prepared for DOE to evaluate both the current state of electrical adequacy as well as future adequacy from the combination of announced retirements and large load growth from expansion of industry, data centers and AI.

This report serves as DOE’s response to a Presidential Executive Order by delivering the required uniform methodology to identify at-risk region(s) and guide reliability interventions. The report was developed with assistance from the Pacific Northwest National Laboratory (PNNL) and National Renewable Energy Laboratory (NREL) using data from the North American Electric Reliability Corporation (NERC).

The highlights relating to PJM below is excerpted from the 73 page report. They developed three separate cases for 2030. The “Plant Closures” case assumes all announced retirements occur plus generation additions which include NERC’s Tier 1 resources category- completed and under-construction power generation projects, as well as those with firm-signed and approved interconnection service or power purchase agreements. The “No Plant Closures” case assumes no retirements plus the same additions. A “Required Build” case further compares the impacts of retirements on perfect capacity additions needed to return 2030 to the current system level of reliability.

The model assumes electricity moves between subregions, when conditions start to tighten. Each region has a certain amount of capacity available, and the methodology determines if there is enough to meet the demand. When regions reach a “Tight Margin Level” of 10% of capacity, i.e., if a region’s available capacity is less than 110% of load, it will start transferring from other regions if capacity is available.

Several utilities and financial and industry analysts identify data centers, particularly those supporting AI workloads, as a key driver of electricity demand growth. Multiple organizations have developed a wide range of projections for U.S. data center electricity use through 2030 and beyond, each using distinct methodologies based on their institutional expertise.

These projections were used to explore reasonable boundaries for what different parts of the economy envision for the future state of AI and data center load growth. For the purposes of this study, rather than focusing on any specific analysis.

Key Findings:

Plant Closures Case:

• Systemwide Failures: PJM failed reliability thresholds.
• Loss of Load Hours (LOLH): Was projected to be 430 hours/year in PJM.
• Load Shortfall Severity: Max shortfall reached as high as 43% of hourly load in PJM
• Normalized Unserved Energy: Normalized for PJM was 0.1473% (PJM), far exceeding thresholds of 0.002%.
• Extreme Events: Most regions experienced ≥3 hours of unserved load in at least one year. PJM had 1,052 hours in its worst year.
• Spatial Takeaways: Subregions in PJM met thresholds—indicating possible benefits from transmission.

No Plant Closures Case:

• Improved System Performance, but PJM still experienced shortfalls.

Regional Failures:

• PJM (was the worst failure zone) 214 hours/year average, 0.066% normalized unserved energy, 644 hours in worst year, max 36% of load lost.

Key Takeaways

The Status Quo is Unsustainable. The status quo of more generation retirements and intermittent replacement generation is neither consistent with winning the AI race and ensuring affordable energy for all Americans, nor with continued grid reliability (ensuring “resource adequacy”). Absent intervention, it is impossible for the nation’s bulk power system to meet the AI growth requirements while maintaining a reliable power grid and keeping energy costs low for our citizens.

Grid Growth Must Match Pace of AI Innovation. The magnitude and speed of projected load growth cannot be met with existing approaches to load addition and grid management. The situation necessitates a radical change to unleash the transformative potential of innovation.

Retirements Plus Load Growth Increase Risk of Power Outages by 100x in 2030. The retirement of firm power capacity is exacerbating the resource adequacy problem. 104 GW of firm capacity are set for retirement by 2030. This capacity is not being replaced on a one-to-one basis and losing this generation could lead to significant outages when weather conditions do not accommodate wind and solar generation. In the “plant closures” scenario of this analysis, annual loss of load hours (LOLH) increased by a factor of a hundred.

Planned Supply Falls Short, Reliability is at Risk. The 104 GW of retirements are projected to be replaced by 209 GW of new generation by 2030; however, only 22 GW would come from firm baseload generation sources all the rest is intermittent and weather dependent and climate change is impacting solar and wind generation. Even assuming no retirements, the model found increased risk of outages in 2030 by a factor of 34.