1. A useful label answers a narrower question than a household bill
A heat pump can earn a strong seasonal rating and still produce a disappointing electricity bill in a particular home. A household can also report lower spending without having demonstrated an improvement in the equipment's efficiency. Those observations are not contradictory. The rating, the building's demand for heat and the amount charged by the utility belong to different parts of the account.
The current ENERGY STAR heat-pump specification provides a timely reason to examine those boundaries carefully. Version 6.2 is available in a February 2026 revision. That is a version of a product-label specification, not a report of a newly tested household's winter savings. ENERGY STAR's revised heat-pump specification
To interpret a performance claim, follow three separate questions. What did a defined test procedure establish about the equipment? How does the heat required by a particular building compare with what the equipment can deliver under relevant conditions? What electricity and other energy crossed the household's billing boundary during the period being discussed? Each question needs information that the others do not supply.
This article concentrates on those links. It does not revisit the basic explanation of why heat moved into a building can exceed the electricity used by a heat pump. Nor does it recommend a brand, equipment size, thermostat setting or electrical modification. Installation, maintenance and safe measurement require qualified professionals. The examples here are original paper exercises using invented buildings, performance points, weather hours and tariffs, not measured results from a product or advice for a real home.
The goal is a more useful form of skepticism. Instead of treating a label as either a guarantee or meaningless advertising, ask what comparison it makes possible and what additional evidence a stronger claim requires. A standardized result can be valuable precisely because it holds some conditions fixed. A household bill can be valuable precisely because it records a real transaction. Neither becomes more informative when it is mislabeled as the other.
2. Read the test version before comparing the number
DOE's January 7, 2025 final rule amended the Appendix M1 test procedure using AHRI 210/240-2024 and established Appendix M2 using AHRI 1600-2024. M1 measures the familiar SEER2 and HSPF2 metrics; M2 introduces SCORE and SHORE. The rule ties the required transition to the newer metrics to compliance with standards based on them. The existence of a new test appendix is therefore not, by itself, evidence that every advertised rating has already changed metrics. DOE's January 2025 test-procedure rule
There is a further date distinction. A September 9, 2025 final rule delayed specified controls-verification enforcement provisions. The current text of 10 CFR 429.134(k), checked for this article, separately identifies July 7, 2025 for paragraphs one through three and July 7, 2026 for paragraph four. That is not a blanket postponement of every test or rating. These documents should not be collapsed into a single undifferentiated “new rules” date. September 2025 final rule, current enforcement provision
For a fictional comparison, imagine an advertisement for system Alder displaying “9.0 heating efficiency,” while a second advertisement for system Birch displays “8.5 HSPF2.” The larger number does not yet establish a better result. Alder's label has omitted the metric and test basis. It could refer to a different rating convention or a different quantity. The first task is not calculating a percentage advantage; it is identifying what the numbers mean.
Even once the metrics match, the date and equipment configuration can matter. An old brochure might describe a combination no longer under consideration. A revised document might correct a rating or use a different test basis. The reader needs an identifiable record, not merely a familiar product-family name.
This is a practical document problem rather than an invitation to practice regulatory law. Preserve the title and edition of the rating method, the document date, the equipment combination and any stated exceptions. If a comparison spans different metrics, explain why the conversion or comparison is justified rather than assuming a universal multiplier. A change in how performance is represented is not automatically a change in the machine's physical behavior.
The same caution applies to proposals. A proposed change can be important for future planning without being an effective requirement. Conversely, a final rule may contain different implementation dates for different provisions. Reading the stage and scope of the document prevents a technically accurate date from being attached to the wrong obligation.
3. A seasonal ratio is an account, not an operating point
AHRI 210/240-2024 defines HSPF2 using seasonal space-heating demand in Btu divided by seasonal electrical energy in watt-hours. It identifies Region IV as the basis used for the relevant federal compliance rating. The number is not a dimensionless operating-point COP, and its reference season is not a record of the weather at a specific buyer's address. AHRI's 2024 rating standard
A fictional record makes the distinction concrete. Suppose a calculation assigns a system 24 million Btu of seasonal heating and three million watt-hours of electricity. The resulting ratio is eight Btu per watt-hour. Those stipulated totals are sufficient to reproduce the division. They do not identify the heat output at a particular cold temperature, the amount of electricity on a particular January day or the cost of that electricity.
Now suppose another record also gives a ratio of eight but uses twice the heating total and twice the electricity. The ratio is unchanged, while the energy quantity has doubled. A rating cannot tell a reader the total bill without an additional account of how much service is required. This is one reason that “more efficient” and “uses less electricity in this house” are related questions rather than identical sentences.
The equipment identity is part of the comparison too. A reader can apply a simple evidence check: does the record describe the exact combination being discussed, or only a component shared with that combination? Recognizing a familiar outdoor-unit brand does not resolve an unexplained difference between the certificate and the proposal. The following example illustrates that logical gap.
For Alder, imagine a certificate names outdoor component A and indoor component X, but a quotation names outdoor A with indoor Y. The certificate does not prove that the quotation has the same rating simply because A appears in both documents. That conclusion would require a record for the relevant combination or an otherwise valid basis for the representation. No claim is being made that X or Y is better; the identity mismatch comes before the performance comparison.
A careful reader can therefore construct a compact comparison row: metric, units, method edition, system identity and represented result. Only after those fields align should the numerical ranking begin. This is not bureaucratic decoration. It is what keeps a real standardized comparison from being replaced by a comparison between unrelated labels.
4. Cold-weather capacity and cold-weather efficiency answer different questions
The current ENERGY STAR cold-climate criteria include a COP of at least 1.75 at five degrees Fahrenheit and heating capacity at that temperature of at least 70 percent of the specified 47-degree capacity. They also include controls verification. These are equipment-performance criteria at defined conditions, not a statement that every qualifying unit can meet every building's cold-weather load without supplemental heat. ENERGY STAR's cold-climate requirements
Consider two invented performance records. Alder delivers ten kilowatts of heat at the warmer reference point and seven at the colder point. Birch delivers six and 4.2 respectively. Both retain 70 percent of their warmer-point capacity. But if an imaginary building requires six kilowatts at the colder condition, their absolute capacity positions differ: Alder's stipulated capacity exceeds that load by one, while Birch falls short by 1.8.
Retention is therefore not adequacy. A percentage answers how one point compares with another point for the same equipment. Adequacy asks whether the relevant output meets the building's required service. Those questions can be confused when a headline advertises a large retention percentage without giving the absolute output or the load it is supposed to serve.
Efficiency adds a third comparison. If Alder supplies seven kilowatts of heat while using 2.8 kilowatts of electricity under the example's defined condition, its operating ratio is 2.5. That does not establish how often the building needs all seven kilowatts. Nor does a higher efficiency ratio automatically compensate for a capacity shortfall: a system can supply heat efficiently and still supply too little for the stipulated requirement.
The NEEP sizing guide, revised April 8, 2020 and hosted by DOE, distinguishes building-load calculations from equipment selection at relevant design conditions. It also identifies building-envelope and distribution characteristics as inputs to the load assessment. The guide's revision date is not the later date embedded in its hosting path, and it is not used here as a new 2026 equipment test. NEEP's load-and-selection guide
For a second fictional building, change only the assumed cold-condition load from six to four kilowatts. Birch's 4.2 now exceeds the stipulated load. The equipment record has not improved; the building question changed. Conversely, a renovation that changes a building's heat requirement changes the comparison even if the equipment remains the same.
These arithmetic examples are not sizing instructions. They omit numerous conditions that a professional assessment must address. Their narrower purpose is to show why a seasonal rating, a capacity-retention percentage, an absolute capacity and a building-load estimate cannot substitute for one another. A fair report keeps all four labels visible.
5. Seasonal averaging is not averaging the attractive ratios
The following weather-bin exercise is original and deliberately simplified. It is not a reproduction of the federal HSPF2 calculation, a local climate forecast or a certified rating. It uses kilowatt-hours for both heat and electricity so that the resulting seasonal ratios are dimensionless. There are only two fictional temperature bands, no distribution losses, no standby use and no auxiliary heat unless explicitly added later.
In the mild band, an imaginary building needs four kilowatts of heat for 1,000 hours. The assumed equipment ratio is four, so it uses one kilowatt of electricity during those hours. Heat delivered is 4,000 kilowatt-hours and electricity is 1,000. In the cold band, the building needs eight kilowatts for 500 hours. At an assumed ratio of two, electricity use is four kilowatts, giving another 4,000 kilowatt-hours of heat and 2,000 of electricity.
The whole season delivers 8,000 kilowatt-hours of heat using 3,000 of electricity. Its ratio is approximately 2.67. Averaging the two operating ratios, four and two, would give three instead. Weighting those ratios by the number of hours would give about 3.33. Neither shortcut reproduces the stipulated energy account, because the hours carry different heat loads and different electrical demands.
The correct aggregation for this example is uncomplicated: add heat across the bins, add electricity across the same bins, then divide the totals. The point is not that all seasonal methods use these exact two bins or assumptions. It is that an aggregate ratio should be derived from the quantities it claims to summarize. A mathematical average of ratios can answer a different question.
Now move 250 hours from the mild band to the cold band while keeping total hours at 1,500. Mild-band heat becomes 3,000 kilowatt-hours and electricity 750. Cold-band heat becomes 6,000 and electricity 3,000. The revised total is 9,000 heat units and 3,750 electrical units, giving a ratio of 2.4. The fictional equipment's two operating-point ratios are unchanged, yet the seasonal result is lower and electricity use is higher.
This is what a weather mix can do in a transparent toy model. It does not prove the size of a real winter's effect, because the model has only two bands and stipulated loads. It shows why a single laboratory point cannot predict a season and why a season from one climate cannot simply be transferred to another.
There is a further subtlety. Total heating hours did not change in the second scenario. A comparison based only on hours of operation would therefore miss the difference. The colder hours required more heat and more electricity per hour. A useful seasonal report needs enough detail to distinguish duration from the conditions and service associated with that duration.
A reader does not need to reproduce a full certification algorithm to ask the right question: what conditions receive weight in this result, and does the claimed household conclusion rely on a different mix? The rating and the household forecast can both be useful, provided their weather assumptions are not silently exchanged.
6. A small share of heat can be a larger share of electricity
Auxiliary heating introduces another denominator problem. For this paper exercise only, suppose a fictional building receives 10,000 kilowatt-hours of heat. The heat pump supplies 9,000 at an assumed ratio of three, using 3,000 kilowatt-hours of electricity. An idealized electric-resistance source supplies the remaining 1,000 using 1,000 electrical kilowatt-hours. No additional losses or other electrical uses are included.
The whole system supplies 10,000 heat units using 4,000 electrical units, for a ratio of 2.5. Auxiliary heat supplied ten percent of the heat but consumed 25 percent of the electricity in this account. Those percentages are both correct because their denominators differ. A statement that auxiliary heating is “only ten percent” is incomplete unless it names the quantity being counted.
Increase the auxiliary heat share to 20 percent while holding total delivered heat at 10,000. The heat pump now supplies 8,000 using about 2,666.67 electrical kilowatt-hours; the idealized auxiliary source supplies 2,000 using 2,000. Total electricity is approximately 4,666.67, and the overall ratio is about 2.14. The auxiliary share of electricity becomes about 42.86 percent. The example shows a nonlinear relationship between a heat-share statement and the combined efficiency ratio.
Nothing in this arithmetic recommends disabling supplemental heat. The example's building still requires the stipulated total heat, and a real system's safe operation and comfort requirements cannot be determined from a simplified article. The appropriate question is what role supplemental heat plays in the documented design and how its contribution is represented in the performance claim.
A different auxiliary source would require a different account. If it uses another fuel, a spreadsheet containing only electricity no longer represents all purchased heating energy. If it serves a different space or interval, its output cannot simply be added to the heat-pump total without aligning the boundaries. A report should not hide a second fuel simply because the headline promises electrification, nor pretend that a second fuel makes the heat pump's measured contribution disappear.
For a fictional comparison between two winters, record heat-pump electricity, auxiliary electricity and any other heating fuel separately before forming the total. If only the total household bill is available, the auxiliary share may be unknown. Calling the unknown share zero would turn a lack of information into an unsupported performance claim.
This distinction is especially useful when interpreting a cold-weather anecdote. The building may remain comfortable because the complete heating arrangement supplies the required service. That observation alone does not reveal which source supplied which portion, or how efficiently each portion was supplied. Comfort, capacity and purchased energy are related observations, not interchangeable measurements.
7. The interval must include the operating modes the claim covers
NIST Technical Note 2101, published in July 2020, compared two heat-pump systems in a laboratory house using alternating weeks and simulated household loads. It reported differing defrost behavior and examined the effect of a firmware change. This was a bounded comparison of particular systems and conditions, not a ranking of today's products. Its relevance is that controls and operating modes belong in the performance record, rather than being incidental details beside a nameplate rating. NIST's side-by-side heat-pump study
A separate invented hour shows why the interval matters. During its first fifty minutes, a fictional system supplies three kilowatts of net heat while consuming one kilowatt of electricity. During a stipulated ten-minute transition, net heat delivered is zero and electrical use is 1.2 kilowatts. These are chosen accounting values, not a universal description of defrost or a measurement of any real machine.
The first interval delivers 2.5 kilowatt-hours of heat and uses about 0.8333 kilowatt-hours of electricity. The second adds no net heat and uses 0.2 electrical kilowatt-hours. Across the full hour, the ratio is 2.5 divided by approximately 1.0333, or about 2.42. Reporting only the first fifty minutes would give three. That narrower result is not arithmetically wrong; it answers a narrower question than full-hour performance.
The report must therefore say whether a quoted result represents selected steady operation or all modes inside a specified interval. A perfectly accurate trace from the selected interval cannot establish what happened during the excluded ten minutes. Conversely, a short transition should not be presented as though it describes the entire winter. Both selective optimism and selective pessimism can begin with genuine data.
Now imagine the transition interval is missing from a data export rather than intentionally excluded. The remaining observations still support their own subtotal, but they do not establish the full-hour total. Filling the missing interval with the favorable steady-state value would invent a result. A transparent analysis can instead identify the gap, report the observed subset and explain what additional evidence is needed for the broader calculation.
The same logic applies when comparing control versions. If an update occurs between observation periods, the record should identify that change. A difference between those periods might also reflect weather or load, so a before-and-after subtraction does not isolate the software's effect automatically. A claim about the update needs a comparison that addresses those other changes.
For the public reader, this is a request for a mode history, not instructions for altering controls. The useful evidence concerns which operating conditions were included, how transitions were handled, and whether the denominator covers the same time as the delivered heat. It does not require anyone to change a setting, disable a function or access energized equipment.
8. Heat at the equipment is not necessarily heat delivered where it is needed
Return to the invented building, but draw two different reporting boundaries. At the equipment's defined delivery boundary, suppose the record shows twelve kilowatt-hours of heat and four kilowatt-hours of electricity, with the relevant indoor-fan electricity already included. The ratio at that boundary is three. Now stipulate that only 10.8 kilowatt-hours reach the rooms included in the service claim during the same interval. The room-delivery ratio is 2.7.
The calculation does not establish why the difference exists in any real building. It simply assigns two different endpoints to two different quantities. If the claimed service is heat reaching those rooms, a measurement at an earlier boundary needs an account of the intervening difference. If the claim concerns equipment output, the earlier boundary may be appropriate, but it should not be relabeled as whole-house delivery.
Even the word loss needs care. Suppose some of the remaining heat enters another space that is inside the building's intended heated boundary. Calling all of it lost to outdoors would be a different, unsupported assumption. If it reaches an unneeded space or arrives outside the evaluated interval, the service comparison changes again. A record should identify the destination and time meaning rather than treating every unmeasured difference as the same physical effect.
This distinction is related to the load question, but it is not identical. A building may need a certain amount of heat overall while particular rooms receive too little. A whole-building total cannot establish the temperature in every room. Likewise, a comfortable main room does not prove that every part of the house received the same service as before. A comparison of energy use should state what was being heated and to what documented conditions.
For a fictional retrofit report, imagine electricity falls by 15 percent while the recorded heated floor area also falls by 20 percent because two rooms are no longer included. The energy reduction is real under the stipulated measurements, but it cannot all be credited to a more efficient machine without addressing the changed service. Conversely, an increase in energy use may accompany an increase in the area maintained at the intended conditions. The meaning of the change depends on the service comparison.
There is no need to prescribe how a household should use its rooms. The reporting task is simply to avoid comparing unlike services while claiming an equipment-only improvement. A technically sound result can be narrow: the system supplied a defined amount of heat across a defined boundary over a defined interval. Extending that result to comfort, distribution or the entire building requires evidence for those extensions.
9. Reconcile the electricity before explaining the money
Consider an original fictional billing card for one month. The household meter records 2,400 kilowatt-hours. In this exercise, separately stipulated records assign 1,400 to the outdoor heat-pump unit, 100 to the indoor fan, 300 to auxiliary electric heat and 600 to unrelated household uses. The categories do not overlap. Their sum matches the household meter, and the heating-related subtotal is 1,800 kilowatt-hours.
At an invented flat price of twenty cents per kilowatt-hour, the energy charge is $480. Add a fixed $25 monthly charge and the bill is $505, with no taxes or other adjustments in this simplified example. The heating-related energy charge is $360. Calling the full $505 a heat-pump operating cost would assign unrelated electricity and the entire fixed charge to the heating equipment without explaining that choice.
A different question could justify including some or all fixed charges. If a project creates or eliminates a separate utility account, those charges may matter to the comparison. If the account remains regardless of the heating choice, treating its full fixed charge as an avoidable heating cost would be misleading. The article does not decide a household's tariff treatment; it shows why the accounting rule must be stated.
EIA explains that electricity prices vary with location and other supply conditions, and that some utilities offer time-of-day pricing. A national average or a simple flat-rate example is therefore not a substitute for the relevant tariff and usage record. EIA's electricity-price explanation
In a second invented tariff, 1,200 heating kilowatt-hours occur at fifteen cents and 600 occur at thirty cents. The heating energy charge is $180 plus $180, or $360. The average is twenty cents, but it emerges from the allocation of use between prices. Moving 300 kilowatt-hours from the cheaper period to the more expensive one, while holding total electricity at 1,800, raises the charge to $405. No equipment-efficiency change is needed to produce the difference.
The reverse problem appears in year-to-year bills. Suppose one period uses 2,000 kilowatt-hours at fifteen cents plus a fixed $20 charge, costing $320. Another uses 1,800 at twenty cents plus the same fixed charge, costing $380. Electricity consumption fell ten percent while the bill rose 18.75 percent. A claim that the higher bill proves worse equipment performance would contradict the stipulated consumption record.
None of these numbers is a forecast or a quoted tariff. They are a reconciliation exercise: separate quantities, prices and fixed terms before attributing a money change to the machine. Without that separation, both favorable and unfavorable bill anecdotes can tell a story that their underlying records do not establish.
10. Weather normalization can help, but it cannot manufacture a control group
EIA describes heating degree days as a weather index based on how far daily average temperature falls below a reference temperature, commonly 65 degrees Fahrenheit in its reporting. The index is useful for comparing weather-related heating demand. It is not a direct measurement of heat delivered to a particular house or of a heat pump's efficiency. EIA's degree-day explanation
Use a deliberately simple invented model: household electricity equals a 500-kilowatt-hour nonheating baseline plus two kilowatt-hours per heating degree day. A period with 500 degree days therefore uses 1,500 kilowatt-hours. A period with 750 degree days uses 2,000. The model's heating relationship has not changed.
Divide total household electricity by degree days, however, and the first period gives three while the second gives approximately 2.67. The ratio appears to improve as weather gets colder even though the assumed heating relationship is identical. The fixed nonheating baseline is being spread across more degree days. Under this model, subtracting the known 500 baseline before dividing gives two in both periods.
That correction works because the baseline and linear relationship are stipulated. In a real evaluation, neither may be known exactly. Nonheating consumption can change, and a heat pump's electricity requirement need not be a fixed linear multiple of degree days across all conditions. The two-bin example earlier already showed how a changing mix of conditions can alter the relationship between delivered heat and electricity.
A sensible analysis therefore distinguishes a weather adjustment from a measured counterfactual. An adjusted estimate can be useful, but it inherits its model assumptions. If occupancy, heated area or operating schedule also changed, weather alone does not explain the whole difference. A comparison with several plausible baselines can reveal sensitivity without pretending that one selected adjustment has discovered the only true savings number.
For an original sensitivity check, keep the first period's 1,500 kilowatt-hours and 500 degree days. If the assumed nonheating baseline is 400 rather than 500, the heating-related ratio becomes 2.2. If the baseline is 600, it becomes 1.8. Those values are not a confidence interval unless a justified statistical model supplies that interpretation. They show how an uncertain accounting input changes the conclusion.
EIA's October 2026 Winter Fuels Outlook itself includes warmer and colder weather cases, expressed as ten-percent changes in heating degree days from its base case. It also cautions that household characteristics and operating conditions affect expenditures. Those scenarios are forecasts, not observed bills for the coming winter and not predictions for a specific address. EIA's October 2026 winter outlook
The useful lesson is to preserve the distinction between observation and adjustment. The meter reading is an observation. The chosen baseline, weather relationship and counterfactual period are parts of an analysis. A reader should be able to identify which is which before accepting a claim of improvement or disappointment.
11. A record can pass the arithmetic check and still miss the question
Imagine a fictional independent analyst receives three files about a winter retrofit: a rating certificate, monthly utility bills and a monitoring summary. The certificate identifies system Alder with component X. The installation invoice identifies component Y. The bills cover the whole property. The monitoring summary covers only the outdoor unit and excludes several days with missing data. Each file may be genuine, yet the files do not automatically form a complete comparison.
The first task is identity reconciliation. If the equipment combination in the certificate differs from the installed combination, the analyst should resolve the mismatch rather than transfer the rating by brand association. The second is boundary reconciliation: whole-property consumption and outdoor-unit consumption are different quantities. The third is period reconciliation: a monitored subtotal over twenty-six days cannot be compared directly with a thirty-one-day bill.
Suppose the monitored twenty-six days total 1,040 kilowatt-hours. Multiplying the daily average of forty by thirty-one gives 1,240. That is an extrapolation, not a measured monthly total. If the missing five days were unusually cold, the simple extrapolation could be unrepresentative. If they were unusually mild, it could err in the other direction. The arithmetic is correct, but the calendar is part of the evidence.
If a recovered log later assigns 300 kilowatt-hours to those five missing days, the completed month totals 1,340, not the extrapolated 1,240. The completed total should replace the estimate in the revised comparison, with the hundred-kilowatt-hour difference explained. It does not alter the original 1,040 observation or establish that the equipment changed efficiency during the gap.
A useful report could retain both the observed subtotal and the estimated full-period figure, with an explanation of the missing days. It should not blend them into a single column labeled measured. If there is no defensible basis for the extrapolation, a narrower result may be the most accurate one: the observed equipment electricity over the available interval, without a claimed complete-month comparison.
Next consider the thermal side. A monitoring summary containing only electricity cannot, by itself, provide a measured seasonal ratio of delivered heat to electricity. The missing numerator might be estimated with an appropriate model, but then the result is model-based rather than wholly measured. Calling an estimate a measurement does not become acceptable because the estimate looks plausible or agrees with a rating.
This distinction does not diminish the value of billing data. Bills can establish purchased energy and expenditure over their stated periods. They can help test whether a larger household claim is consistent with observed use. But a bill does not report all the quantities needed to diagnose a particular component's performance, just as a component test does not report everything needed to reconstruct the bill.
For the hypothetical analyst, the stopping rule is evidence-based: report the strongest comparison supported by aligned identities, boundaries and periods. Leave the remaining difference unresolved or obtain the missing record. There is no need to turn incomplete information into either a product endorsement or a declaration of failure.
12. What a fair winter-performance claim would actually say
Return to three imagined headlines. The first says that a system has a specified HSPF2 rating under an identified procedure. The second says that a particular building received a stated quantity of heat while the complete heating system consumed a stated amount of electricity during a defined winter. The third says that the household's total heating expenditure fell relative to a justified comparison period. Each headline can be meaningful. Each requires a different evidence package.
The first needs the rating record and exact equipment scope. The second needs a coherent service boundary, period and energy account, including the treatment of supplemental sources and missing observations. The third additionally needs prices, fixed charges, other fuels and a defensible comparison of weather and service. None of the stronger claims follows automatically from the weaker one.
A useful public account would also distinguish capacity from consumption. A system's ability to supply heat at a cold condition matters even if that condition occurs rarely. Seasonal energy matters across the whole evaluated mix of conditions. A household can care about both comfort on a difficult day and expenditure across the winter without expecting one number to answer both questions.
This is why standardized tests and field evidence are complements rather than rivals. A common test basis makes a bounded comparison possible. A carefully described field record shows what happened in a particular setting. Disagreement between a naive forecast and a bill is a reason to inspect the translation between those settings, not immediate proof that testing is useless or that a household's experience is wrong.
The fictional examples in this article identify several translations worth checking: reference season to actual weather mix, retained capacity to absolute building load, heat share to electricity share, equipment output to room-delivered service, electricity quantity to tariff charge, and observed period to estimated counterfactual. A mistake at any one of those steps can change the story while leaving the original rating perfectly intact.
A seasonal rating is therefore valuable without being a winter-bill guarantee. Its value lies in the question it answers under stated conditions. The more ambitious claim—that a particular household will receive a particular service for a particular amount of money—needs the additional account. Keeping that account visible is how a heating-performance story becomes useful rather than merely reassuring or alarming.