Manufactured Savings: How Ember Turns Assumptions into Energy Policy

Charles Rotter

Ember’s latest report, confidently asserting that “clean power fortifies Britain against gas price shocks,” arrives wrapped in the language of analysis but functions as something closer to strategic persuasion. The numbers are crisp, the tone authoritative, and the conclusion conveniently aligned with current political messaging. What sits underneath is a sequence of assumptions and omissions that consistently point in one direction.

Consider the central claim:

“Great Britain has saved around £7 million a day… as domestic solar PV and wind capacity has removed the need for importing gas.” (Solar Power Portal)

That sentence carries the weight of an observed fact. It reads as though someone checked the accounts and discovered a daily saving. But the report itself makes clear—if one reads beyond the headline—that this figure is derived from a hypothetical:

“Had British gas usage not declined, and remained at the same levels as in 2021… Britain would spend an additional £7 million per day.” (Solar Power Portal)

In other words, the “saving” exists only relative to a constructed scenario. This is not a measured outcome. It is a model output built on a specific assumption about what would have happened otherwise. Change that assumption, and the number changes with it.

That distinction is not a minor technicality. It is the entire foundation of the claim.

What follows is a familiar pattern. A favorable counterfactual is selected, a result is generated, and the output is presented with the rhetorical force of empirical evidence. The report does not explore a range of plausible alternatives. It does not ask how sensitive the result is to different assumptions about demand, imports, or system behavior. It selects the pathway that produces the desired conclusion and then assigns it a precise monetary value.

This is how you get a headline like “£7 million a day.” Not from observation, but from construction.

The framing continues in the scope of the analysis. The report highlights that:

“Wind and solar has met 40% of Britain’s electricity demand… almost double that of gas.” (Solar Power Portal)

That is accurate within the narrow boundary of electricity generation during a specific period. It is also carefully chosen. Electricity is the segment where renewables appear strongest. It is not the majority of total energy consumption, and it is not where households face their largest energy costs.

Even Ember’s own material elsewhere acknowledges the broader picture:

“Heating and transport… form the majority of household energy expenditure, and both depend on fuel imports.” (ember-energy.org)

That context is absent from the headline claim. By isolating electricity, the report presents a partial success as if it were system-wide resilience. The reader is left with the impression that Britain’s energy system has been “fortified,” when in reality only a subset has been examined.

Timing does additional work. The report is anchored to a geopolitical shock that drove gas prices sharply higher:

“The cost of generating electricity with gas… almost doubled… within a month.” (Solar Power Portal)

Under those conditions, any reduction in gas usage will appear beneficial. This is hardly surprising. What is surprising is the lack of symmetry. There is no comparable analysis of periods when wind output is low, when solar generation drops, or when the system must fall back on dispatchable sources.

Those periods are not hypothetical. They are routine features of the system. Yet they do not appear in the cost narrative.

Instead, the report presents a one-sided snapshot: renewables performing well during a gas price spike. From that, it extrapolates a broader conclusion about resilience. The uncomfortable parts—the need for backup generation, the costs of balancing, the persistence of gas in price formation—are either minimized or excluded.

This selective accounting extends to costs. The report implicitly assumes that avoiding gas purchases translates directly into savings. It does not seriously engage with the costs required to build and maintain the system that enables those avoided purchases.

Grid expansion, storage, balancing services, and capacity payments are not rounding errors. They are structural components of a system with high intermittent generation. Their absence from the headline calculation is not because they are irrelevant. It is because including them would complicate the narrative.

Ember’s broader body of work makes its policy direction explicit. Statements such as:

“Clean power… is the only way to shield against sudden gas and power price hikes” (ember-energy.org)

and

“Reducing gas reliance will be a major win for UK energy security” (Tech Digest)

are not neutral observations. They are prescriptions. The modeling flows toward them.

This alignment becomes even clearer when placed alongside political messaging. UK Energy Secretary Ed Miliband recently stated:

The difference clean power makes to our energy security 👇 https://t.co/6IpIkyOeJZ

— Ed Miliband (@Ed_Miliband) April 10, 2026

The symmetry between the report and the political line is difficult to miss. The report supplies the numbers; the politician supplies the slogan. Each reinforces the other.

At this point, the question is no longer whether the analysis contains assumptions—it obviously does—but whether those assumptions are neutrally selected or directionally chosen to support a predetermined conclusion.

The pattern suggests the latter.

A genuinely exploratory analysis would present multiple scenarios. It would show how outcomes vary under different conditions. It would quantify not only benefits during favorable periods but also costs during unfavorable ones. It would treat uncertainty as central rather than peripheral.

That is not what is on display here.

Instead, the report follows a consistent structure: define the desired policy outcome, construct a model that produces it, and present the result with the confidence of measurement. The uncertainties remain in the background, while the conclusion moves to the foreground.

Even within Ember’s own material, there are hints of the limits. The UK remains heavily dependent on imports across large parts of its energy system. Gas continues to play a central role in balancing and price-setting. Intermittency remains an inherent constraint. These realities do not disappear because a model highlights a favorable month.

They are simply not the focus.

The result is a piece of work that is best understood not as detached analysis but as advocacy expressed through quantitative language. It is persuasive because it appears precise. It is compelling because it simplifies. And it is influential because it arrives at a moment when policymakers are actively seeking justification for a particular direction.

Calling this “bullshit” may be emotionally satisfying, but it undersells the sophistication of what is actually happening. This is not careless analysis. It is careful, selective analysis designed to produce a specific conclusion while maintaining the appearance of objectivity.

That is a more serious issue.

Because once speculative outputs are presented as concrete savings, they begin to shape policy decisions, investment flows, and public expectations. And when those decisions are made on the basis of partial accounting and optimistic assumptions, the costs—unlike the modeled savings—have a way of becoming very real.