The Green Energy Double-Whammy: Subsidies Upfront and Forever, Combined with 100 Times As Many Blackouts
A good friend and loyal reader sent me a Utility Dive article with quite the headline: “Load growth, plant retirements could drive 100x increase in blackouts by 2030: DOE."
That certainly got my attention, but the article summation in brief reminded me of Harry Truman’s desire for one-handed economists who wouldn’t keep resorting to “on the other hand” answers:
Blackouts could increase by 100 times in 2030, relative to today’s averages, if the United States continues to shutter power plants and fails to add additional firm capacity amid rising demand, the U.S. Department of Energy said in a Monday report.
The report includes a uniform methodology to identify regions at risk of power outages and guide federal reliability “interventions,” DOE said. The report was required by President Donald Trump’s April executive order which directed the agency to respond to an “energy emergency” he declared in January.
But clean energy advocates say the report appears to exaggerate the risks, and undercount the contributions of wind, solar and battery storage resources. “If the analysis is overly pessimistic about advanced energy technologies and the future of the grid, consumers will end up paying too much for resources we no longer need,” Caitlin Marquis, managing director at Advanced Energy United, said in an email.
As usual, I decided to check out the DOE report for myself. It’s titled “Evaluating the Reliability and Security of the United States Electric Grid,” and is packed full of data and electricity acronyms (28 in all) and odd terms used by no one outside the grid. Nonetheless, we get the big picture from these excerpts (emphasis added):
Our Nation possesses abundant energy resources and capabilities such as oil and gas, coal, and nuclear. The current administration has made great strides—such as deregulation, permitting reform, and other measures—to enable addition of more energy infrastructure crucial to the utilization of these resources. However, even with these foundational strengths, the accelerated retirement of existing generation capacity and the insufficient pace of firm, dispatchable generation additions (partly due to a recent focus on intermittent rather than dispatchable sources of energy) undermine this energy outlook.
Absent decisive intervention, the Nation’s power grid will be unable to meet projected demand for manufacturing, re-industrialization, and data centers driving artificial intelligence (AI) innovation. A failure to power the data centers needed to win the AI arms race or to build the grid infrastructure that ensures our energy independence could result in adversary nations shaping digital norms and controlling digital infrastructure, thereby jeopardizing U.S. economic and national security.
Despite current advancements in the U.S. energy mix, this analysis underscores the urgent necessity of robust and rapid reforms. Such reforms are crucial to powering enough data centers while safeguarding grid reliability and a low cost of living for all Americans.
Key Takeaways
Status Quo is Unsustainable. The status quo of more generation retirements and less dependable 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. Even assuming no retirements, the model found increased risk of outages in 2030 by a factor of 34.
Old Tools Won’t Solve New Problems. Antiquated approaches to evaluating resource adequacy do not sufficiently account for the realities of planning and operating modern power grids. At a minimum, modern methods of evaluating resource adequacy need to incorporate frequency, magnitude, and duration of power outages; move beyond exclusively analyzing peak load time periods; and develop integrated models to enable proper analysis of increasing reliance on neighboring grids…
This analysis developed three separate cases for 2030. The “Plant Closures” case assumes all announced retirements occur plus mature generation additions based on NERC’s Tier 1 resources category,11 which encompasses 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 mature 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.
DOE ran simulations using 12 different years of historical weather. Every hour was based on actual data for wind, solar, load, and thermal availability to stress test the grid under a range of realistic weather conditions. The benefit of this approach is that it allows for transparent review of how actual conditions manifest themselves in capacity shortfalls. For all scenarios, LOLH and NUSE are calculated and used to compare how they change based on generation growth, retirements, and potential weather conditions…
[T]he model shows a significant decline in all reliability metrics between the current system scenario and the 2030 Plant Closures scenario. Most notably, there is a hundredfold increase in annual LOLH from 8.1 hours per year in the current case to 817 hours per year in the 2030 Plant Closures. In the worst weather year assessed, the total lost load hours increase from 50 hours to 1,316 hours.
There no specific recommendations in the report, but they are implicit in the conclusions as to how much new reliable generation is needed in various regions:
MISO: In the Plant Closures case, 32 GW of capacity was retired, such that net retirements in the Plant Closures case were -11 GW, or 196 GW of overall installed capacity on the system.
PJM: In the Plant Closures case, reliability metrics worsened significantly, with annual LOLH surging to over 430 hours per year and NUSE reaching 0.1473%—over 70 times the accepted threshold. During the worst weather year, 1,052 hours of load were shed. To restore reliability, the study found that PJM would require 10,500 MW of additional perfect capacity by 2030.
SERC: The analysis identified that planned retirements, combined with rising winter load from electrification, would stress the system. To restore reliability in SERC-East, the study found that 500 MW of additional perfect capacity would be needed by 2030.
CAISO: Average LOLH reached 7 hours per year, and the worst-case year showed load shed events affecting up to 31% of demand. The NUSE exceeded reliability thresholds, signaling the system’s vulnerability to high load and low renewable output periods.
ERCOT: In the current system model, ERCOT exceeded reliability thresholds, with 3.8 annual Loss of Load Hours and a NUSE of 0.0032%, indicating stress even before future retirements and load growth. In the No Plant Closures case, conditions worsened as average LOLH rose to 20 hours per year and the worst-case year reached 101 hours, driven by data center growth and limited dispatchable additions. The Plant Closures case intensified these risks, with average annual LOLH rising to 45 hours per year and unserved load reaching 0.066%. Peak shortfalls reached 27% of demand, with outages concentrated in winter when generation is most vulnerable. To meet reliability targets, ERCOT would require 10,500 MW of additional perfect capacity by 2030.
Pretty sobering, huh? This report clearly lays out the risks created from pushing subsidized intermittent energy onto the grid: not only do we have to pay for it upfront and ongoing, but we have to suffer the consequences of our self-inflicted energy disaster. We must immediately change direction before this double-whammy destroys us.
#DOE #Grid #Electricity #Subsidies #Reliability #Blackouts #Risks
If it’s not dispatchable it’s not capacity.
The belief in the models bones down to do you believe the grid operators competency and understand their bias. We have more risk to assess with the grid operators skill that is not addressed in the capacity models. It’s nice that the feds did the study but it’s the cart before the horse. Until the grid operators and their operations are in order the models have little validity. All of the efforts to prop up wind, solar, and batteries are not well disguised, and this modeling should not be used to put these into the grid as they are relatively quick to build but still with the fatal flaw of intermittency.
And now the basic question - do you still believe the government?