Why this comparison matters in Bavaria

For many households in Bavaria, the heating decision is no longer a vague debate about future technology. It is a practical planning question with real annual bills attached to it. Detached homes around Munich, Augsburg, Regensburg, and rural alpine areas often have very different heat demand profiles, yet they all face the same underlying trade-off: a gas boiler turns purchased fuel into heat with a seasonal efficiency below 100%, while a heat pump uses electricity to move heat and can deliver several units of useful heat for each unit of electricity consumed. That difference is why a heat pump can reduce both emissions and running costs even when electricity is more expensive per kilowatt-hour than gas.

This page is designed to make that trade-off concrete. Instead of asking whether heat pumps are good in general, the calculator asks a narrower and more useful question: given your floor area, your building's annual heat demand, the performance of a likely heat pump, the seasonal efficiency of a gas boiler, and the prices and emission factors you expect to face, how large is the difference in year one and over a longer planning horizon? That framing is much closer to the way households, installers, and finance providers actually compare retrofit options.

What the calculator actually computes

The model starts with useful annual heat demand. In plain language, that is the amount of heat your home needs delivered into the building over a year. The calculator estimates it from conditioned floor area, multiplied by specific heat demand, multiplied by a degree-day adjustment. The first input reflects how much heated space you have. The second reflects the quality of the building envelope and systems. The third lets you nudge the estimate upward or downward for climate severity or a home that behaves differently from the Munich-style baseline used in many examples.

Here, Q is useful heat demand in kilowatt-hours per year, A is conditioned floor area in square metres, q is specific heat demand in kilowatt-hours per square metre per year, and D is the degree-day adjustment expressed as a percentage. A house with 160 m² of conditioned space and a specific demand of 80 kWh/m²·year at 100% weather adjustment therefore lands at 12,800 kWh of useful annual heat demand.

Once useful heat demand is known, the calculator converts that demand into purchased energy for each technology. For the heat pump, purchased electricity equals useful heat divided by seasonal performance factor, or SCOP. For the gas boiler, purchased gas equals useful heat divided by seasonal efficiency. A higher SCOP means the heat pump needs less electricity to deliver the same heat. A higher boiler efficiency means less gas is burned for the same outcome, but the boiler still cannot multiply energy the way a heat pump can.

Emissions are then calculated from those purchased-energy figures. The heat pump uses an adjusted grid emission factor that is reduced by the share of renewable electricity you say is covered by green tariffs or on-site generation. The gas boiler uses the gas emission factor directly. Costs are simpler: purchased electricity times electricity tariff, and purchased gas times gas tariff. For the multi-year view, the model keeps gas emissions constant per kilowatt-hour, lets the electricity grid gradually decarbonise, and escalates electricity and gas prices using the annual rates you provide.

In abstract form, the calculator still follows the general pattern of many engineering and planning tools. First the inputs are gathered, then transformed, then combined into outputs. The existing model blocks below are kept intentionally because they describe that general structure clearly:

On this page, those weights are things like efficiency, SCOP, emission factors, and price escalation. The crucial point is not the algebra alone, but what the variables mean in a heating context. If you choose realistic inputs, the output becomes a sensible scenario estimate. If you mix annual and monthly values, gross floor area and conditioned area, or grid-average electricity and a specific green tariff, the arithmetic still runs but the interpretation becomes shaky.

How to choose each input well

The most important input is usually specific heat demand because it acts like a multiplier across the rest of the model. A poorly insulated post-war detached house may sit much higher than an upgraded envelope with low-flow radiators or underfloor heating. If you have an energy performance certificate, measured annual consumption adjusted for weather, or a proper heating-room calculation from a designer, use that instead of guessing. If your own number includes domestic hot water and you want the calculator to represent total delivered heat, that is acceptable as long as you stay internally consistent across both technologies.

The degree-day adjustment deserves a short explanation because it can be misread. It is not a percentage efficiency and it is not a tariff modifier. It is simply a climate or severity adjustment layered on top of specific heat demand. A value of 100% means you are using the baseline estimate as entered. Values above 100% represent harsher conditions, more wind exposure, or a home whose real operation tends to use more heat than the nominal demand figure suggests. Values below 100% represent milder conditions or a more restrained heating pattern.

SCOP, the seasonal coefficient of performance for the heat pump, is the second input that strongly changes the outcome. Readers sometimes interpret it as a peak laboratory COP, but the calculator expects a seasonal figure. That means it should already reflect winter operation, defrost cycles, flow temperature, and how the system performs across the year rather than at one perfect test point. In a retrofit context, a small change in SCOP matters because emissions and operating cost are both divided by it. A heat pump with a SCOP of 3.8 is not just slightly better than one at 3.0; it can materially reduce purchased electricity for the same useful heat.

Boiler seasonal efficiency should also be read as a real seasonal figure rather than an optimistic brochure number. A condensing boiler can achieve high seasonal performance, but only if it is sized and operated in a way that allows condensing conditions for much of the year. Return temperature, cycling behaviour, and maintenance all matter. The calculator therefore treats efficiency as a practical yearly ratio between useful heat delivered and gas energy purchased. Using 92% is often reasonable for an existing modern condensing system, but older or poorly tuned installations can perform worse.

Tariffs and emission factors are where local assumptions enter. The electricity tariff should be your expected delivered price per kilowatt-hour, not just an energy-only line item from a comparison site. The gas tariff should likewise include the real bill impact you expect to pay, including carbon price effects if they are already reflected in your tariff assumption. The green electricity share is not the same thing as grid decarbonisation: green share changes the fraction of your own heat-pump electricity treated as low-carbon today, while grid decarbonisation changes the future carbon intensity of the remaining grid electricity over time.

A worked Bavarian example using the default values

The defaults in the form are not recommendations, but they do make a useful worked example. With 160 m² of conditioned space, 80 kWh/m²·year of specific heat demand, and a degree-day adjustment of 100%, useful annual heat demand is 12,800 kWh. Using a SCOP of 3.4, the heat pump needs about 3,765 kWh of electricity in year one. Using a gas boiler efficiency of 92%, the boiler needs about 13,913 kWh of gas in year one. Already you can see the core physics of the comparison: the heat pump buys much less final energy because it moves heat instead of producing it by combustion alone.

Now apply the emissions assumptions. With a grid emission factor of 0.32 kg CO₂ per kWh and a renewable electricity share of 40%, the adjusted electricity factor becomes 0.192 kg CO₂ per kWh. Multiplying that by 3,765 kWh gives roughly 723 kg CO₂ in year one for the heat pump. The gas boiler, using 13,913 kWh of gas at 0.201 kg CO₂ per kWh, lands at roughly 2,797 kg CO₂. In this default scenario, the year-one reduction is therefore about 2,074 kg CO₂, or roughly 74% lower emissions from the heat pump route.

The same inputs produce a cost comparison. At €0.32 per kWh, the heat pump's year-one electricity cost is about €1,204.80. At €0.12 per kWh, the gas boiler's year-one fuel cost is about €1,669.56. The calculator labels the year-one cost line as heat pump minus gas, so a negative figure means the heat pump is cheaper to operate in year one. For the lifetime line, the summary reports savings from the heat pump perspective over the full analysis horizon, so a positive number there means the heat pump comes out ahead over time. This distinction matters because many readers scan the signs too quickly and assume both rows use the same direction.

The long-term view adds two more effects. First, electricity emissions can fall each year if the grid decarbonises. Second, electricity and gas prices can rise at different annual rates. That means a heat pump can gain a larger emissions advantage over time even if the home's heat demand stays constant. Whether it also gains a larger cost advantage depends on your escalation assumptions. In other words, the calculator does not assume that today's cost gap and today's carbon gap will remain frozen for 15 years. It lets you test how the trajectory changes.

How to read the result section without overthinking it

The result list is intended to answer the first questions a homeowner usually has after entering data. Useful heat demand tells you whether the building-level assumption looks sensible. Heat-pump electricity use and boiler gas use tell you how much purchased energy each system would need. The year-one emissions line tells you the immediate carbon difference using today's assumptions. The lifetime emissions line tells you how much cumulative carbon could be avoided across the full analysis horizon. If your useful heat demand looks wildly too high or too low, stop there and correct the building inputs before paying attention to the downstream totals.

The comparison table underneath is more straightforward than it may first appear. The annual energy row compares electricity bought for the heat pump with gas bought for the boiler. The year-one operating cost row compares what each technology costs at today's tariffs. The year-one emissions row compares today's carbon outcome. The lifetime rows combine all analysis years into one cumulative total. This is particularly useful when you want to compare a near-term bill difference against a medium-term emissions pathway instead of treating the decision as only a one-year snapshot.

If you are testing several scenarios, the best approach is usually to change one major variable at a time. Start with your best estimate. Then run a conservative case with lower SCOP, higher electricity price, and perhaps a smaller green share. Then run an optimistic case with better system performance or lower electricity price. When the sign of the result is stable across all three, you can be more confident that the direction of the comparison is robust. When the sign flips, you have learned something useful too: the decision is sensitive, and the sensitive variable deserves better evidence before you commit capital.

Assumptions, limits, and good judgement

No simple web calculator can capture every relevant detail of a heating retrofit. This one does not model capital cost, subsidies, financing, maintenance, domestic hot water as a separate load, defrost strategy, flow-temperature redesign, thermal storage, occupant behaviour by room, or hybrid controls with weather-compensated changeover. It is a scenario tool for energy, emissions, and operating cost, not a substitute for a room-by-room design or a compliance certificate. That does not make it unhelpful. It simply means the output is best used to frame decisions, shortlist options, and ask better follow-up questions.

• Use annual inputs consistently: do not mix monthly consumption, seasonal COP, and annual heat demand unless you have converted them properly.
• Stay realistic about SCOP: retrofit performance depends heavily on emitter temperature and installation quality.
• Remember that tariff structure matters: fixed charges, dual-rate contracts, and taxes can change real bills even when energy-only prices look attractive.
• Treat the green share carefully: a certified green tariff changes accounting assumptions, while rooftop PV changes self-consumption patterns and may not cover winter demand evenly.

A sensible final check is to ask whether the result aligns with the physical story behind the numbers. If the heat pump has a strong SCOP and the effective electricity carbon intensity is much lower than gas emissions per delivered unit of heat, then substantially lower emissions are exactly what you should expect. If your heat pump scenario still looks worse, inspect the inputs rather than assuming heat pumps are categorically unsuitable. Conversely, if your house requires very high flow temperatures and you enter a low seasonal performance factor, the calculator may show a weaker result. That is not a bug; it is a reminder that building fabric and system design are part of the decision, not background details.

Used that way, the calculator becomes more than a one-click answer. It becomes a compact planning worksheet for the Bavarian heating transition. You can check a baseline, explore how strongly the result depends on weather severity or SCOP, and understand why grid decarbonisation can widen the emissions gap over time. That combination of transparency and speed is what makes a comparison tool valuable: not because it replaces detailed design, but because it helps you arrive at that next conversation with clearer numbers and better questions.