Ask a model a stupid question …

TLDR; you can use a mature model with lots of detail and vetted data to produce garbage output by feeding it a dumb scenario and willfully misinterpreting the answers.

I’m a little late to the party, but DOE’s 2025 ‘Resource Adequacy Report’ for the electric power system just came across my desk. Key findings in the executive summary point the finger at for future reliability problems at renewables:

  • 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.

On the report’s topic page, this is restated as:

Retirements plus projected load growth increases the risk of power outages by 100 times. At present, 104 GW of firm generation is slated to retire by 2030.  Without corresponding replacement, the risk of annual outages could increase from single digits today to more than 800 hours per year. Such a surge would leave millions of households and businesses vulnerable during stressful grid conditions. New supply planned is insufficient. Of the 154 GW of capacity in advanced stages of development, only 19 GW can regularly operate around the clock. Even in scenarios with no additional retirements, that imbalance leaves a significant shortfall in dependable power. 

Notice right away that the numbers don’t match – is the replacement pipeline 154GW or 209GW? That’s really the least of the problems though.

First, any statement about the effect of renewables on reliability is pure speculation, unsupported by the actual analysis, because they didn’t run any scenarios that test retirements and replacements with renewables separately. They ran 3 scenarios (on top of a current-conditions base case):

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, 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.

Again, there’s no experimental design that factors closures and replacements into separate renewable and fossil/nuclear buckets, so attribution to a particular cause is simply magical thinking.

Worse, the “closures” scenario doesn’t make some important corrections for differences in sources, so you don’t know what’s an apple and what’s an orange:

  • There’s no correction from nameplate capacity to derated capacity, adjusting for wind and solar availability, so you can’t tell whether aggregate capacity in the closure scenario is sufficient or short.
  • There’s no translation of capacity to cost, or of operating mix to marginal cost.
  • There’s no recognition that the planning leadtimes for sources differ a lot (and specifically, that they’re shorter for wind and solar). This may mean that the pipeline of renewables to be installed before 2030 is understated.
  • There’s no reporting of volatility sources. Historically, coordinated outages of fossil fuels are possible, as in the big Texas freeze..

Implicitly, the closure scenario assumes that managers in each ISO are stupid and don’t have access to capacity planning tools. It also assumes no price feedback. Yet in the real world, if capacity is short and loss of load is high, power market prices would go through the roof, creating a financial incentive that would prevent the scenario’s postulated retirements.