Degree-hour: calculating heating needs to read a DPE better in 2026

Understanding degree-hours and their direct link to the DPE

Degree-day, degree-hour: simple definitions and useful differences on site

The heating degree day (HDD) adds up, over a day, the gap between a base temperature (often 18 °C) and the average outdoor temperature when it's colder. The degree-hour does the same thing, but hourly. It's a finer reference point. On site, it helps explain why two "cold" weeks don't look alike, and to discuss comfort, settings and power.

Why HDD and degree-hours influence the heating consumption estimated in a DPE

The DPE doesn't use your bills. It relies on a conventional climate tied to the location (zone, altitude). The colder the reference year, the higher the HDD or degree-hours climb. With identical insulation and system, the calculated heating need rises. For more on this, see unified degree-days (HDD).

What the DPE actually "sees": local climate, thermal mass, surface area, usage (and what it doesn't replace)

The DPE "sees" the surface area, the envelope, thermal bridges, ventilation, equipment efficiency, and standard occupancy (temperature, schedules). It also factors in the building's thermal mass. However, it doesn't replace an on-site measurement, actual usage, or the microclimates that can differ from one street to the next.

Method for calculating degree-hours to estimate your heating needs

Data to gather: base temperature, heating period, HDD/degree-hours for your zone

Start by fixing the base temperature used for HDD, often 18 °C in France. Adjust it if your actual setpoint differs, or if your DPE highlights a home that's very sensitive to temperature swings. Then define your heating period, based on observed start-up dates. Finally, gather the HDD for your commune or the nearest weather station. To get degree-hours, simply convert: DH = HDD x 24.

The step-by-step formula: from degree-hours to heating needs (kWh) based on the envelope

1) Assess the heat loss coefficient G in W/K. Add up the losses through surfaces, i.e. U x A, plus an estimate of ventilation losses. 2) Calculate your degree-hours DH over the period. 3) Theoretical heating need in kWh. Q = G x DH / 1000. 4) For energy consumed, divide by the system's seasonal efficiency (boiler, heat pump): see also seasonal efficiency of generators.

Common mistakes to avoid: unrealistic setpoints, thermal bridges, ventilation, solar gains

• Assuming a setpoint of 21 to 22 °C everywhere. Reality is often more nuanced from room to room.
• Forgetting thermal bridges. They inflate G, especially in partial retrofits.
• Underestimating ventilation and infiltration. Mechanical ventilation, air inlets, airtightness defects change everything.
• Ignoring solar and internal gains. They reduce needs, especially with large windows.

Using the DPE to prioritise heating and insulation works

Reading the DPE indicators that matter for your costing: label, consumption, emissions, heat losses

On a DPE, four pieces of information save time when quoting. The energy label and the climate label give the target. Consumption in kWhEP/m²/year and emissions in kgCO2/m²/year are used to compare before and after works. And the breakdown of heat losses (roof, walls, floor, windows, ventilation) shows where the energy is escaping.

Linking degree-hours and heat losses: quickly spotting the items that "drive" heating

The degree-hour, close to degree-days, indicates the "length" of the heating season for your zone. Cross-reference it with the DPE's heat losses. If the surfaces (walls, loft) dominate, insulation quickly lowers the needs. If ventilation and infiltration weigh heavily, target airtightness and suitable ventilation. You spot what's driving heating at a glance.

Choosing the right scenario: insulation, controls, generator replacement (heat pump, boiler, etc.)

1. Address the envelope first on the main items.
2. Add controls (programmable thermostat, thermostatic valves, balancing).
3. Then size the generator (air-to-water heat pump, condensing boiler, biomass) for proper sizing after insulation.

On-site case: turning a calculation into a coherent quote (without losing a whole day)

House example: estimating the heating need before/after works from the degree-hour figure

For a 110 m² house, you gather the degree-hours for your commune (base 18 °C). You estimate the overall heat loss coefficient UA (in W/K) from the surfaces and ventilation. Annual need (kWh) = UA × DH / 1,000. Order-of-magnitude example with 50,000 K.h. Before works UA = 220, i.e. 11,000 kWh. After insulation and window/door work UA = 120, i.e. 6,000 kWh. This drop helps you size a generator or a heat pump without overselling.

How to justify your assumptions in the quote: transparency on temperatures, usage and limits

In the quote, list 3 or 4 key assumptions. Indoor temperature used (often 19 °C), occupancy periods, ventilation, reference weather, and the energy price used. Add the limits. This calculation is simplified, and doesn't replace either a thermal study or a regulatory DPE.

Presenting a readable gain to the client: savings, comfort, and consistency with the DPE

Show a before/after in kWh, in euros, and in comfort. Fewer cold surfaces, a more stable temperature, and a system that runs less. Link it to the expected DPE, staying cautious. The client sees a clear gain, and you keep a consistent message about the possible variations depending on weather and usage.

Saving time with Argile: degree-hour, DPE and renovation scenarios in practice

Fast energy diagnosis: compare scenarios in under 5 minutes from the home's data

You enter the address, the surface area, the heating system and, if you have it, the existing DPE. Argile cross-references this information with building and climate data to estimate the needs, including a degree-hour reference point for summer comfort. In under 5 min, you compare 2 or 3 scenarios (insulation, ventilation, heat pump) and their impacts.

Feasibility analysis: detecting technical constraints (Open Data) that impact heating and performance

Before the visit, Argile surfaces the key constraints via Open Data. Protected area, local rules, hazards (flooding, clay shrink-swell), altitude and gas or electricity network. You avoid unrealistic quotes and choose the right heating solution faster.

Pre-costing and quote: integrating aid (MaPrimeRénov'/CEE) and structuring a comprehensive retrofit offer

Argile prepares a pre-costing and a quote with aid built in. MaPrimeRénov' and CEE are taken into account to structure a comprehensive retrofit offer, with a readable remaining cost and coherent packages. Enough to move fast, without selling blind.