Digital heating control in existing buildings: cut costs fast

Optimizing an existing heating system rarely requires a full renovation. You can start with the operating parameters, the control settings and the hydraulic balancing of a building that is still occupied, and typical market figures point to savings of 10 to 20 percent, depending on the condition of the system and with no blanket guarantee for every property.

For housing companies, this is above all a question of scale. Multi-family buildings make up only 18 percent of buildings, yet account for around 55 percent of all residential units, and most of that housing stock still runs on fossil fuels: 56.1 percent on gas, 17.3 percent on heating oil. At the same time, the German Building Energy Act (GEG) requires a systematic check and optimization of older water-based systems in larger buildings. Anyone operating many systems therefore needs measures that can be rolled out during ongoing operation and repeated across the portfolio. A single showcase project in one boiler room simply does not move the needle here.

Before you set budgets and priorities, it pays to look at the range between a quick efficiency gain and a genuine investment need:

Which heating optimization works quickly in existing buildings?

The fastest effect comes from the levers with the lowest intervention depth: operating parameters and digital transparency can be tackled in an occupied building without renovating the risers and without swapping out the boiler. Keep these four levels cleanly separated, because they differ sharply in effort, effect and verifiability. Visibility alone, however, lowers no consumption. Savings only become measurable once the data leads to active control or a physical correction.

Levers with low intervention depth

Operating parameters are the cheapest place to start. A wrongly set heating curve or an oversized pump wastes energy in continuous operation without anyone noticing. These are exactly the interventions that BAFA subsidizes as heating optimization, including hydraulic balancing with heating curve adjustment, pump replacement, adjustment of flow temperature and pump output, plus control instrumentation. Digital transparency is the second low-invasive level: a digitally read boiler room reveals overheating and faults that stay invisible on paper.

Automation and more capital-intensive interventions

Automated control goes one step further and turns monitoring into active operation. Systems such as KUGU EOS (Energie-Optimierungssystem) run every 15 minutes and calculate an optimized operating plan for the next 24 hours, based on a digital building model, actual usage behavior and the weather forecast. Hydraulic balancing remains the more capital-intensive but often decisive foundation, because it puts room-by-room heat load, radiators and flow temperature in order. How quickly the digital connection works shows in practice: in Leipzig, the sensors in two older buildings were installed within a single day. Control technology and hydraulics belong together, because a smart operating strategy only works if the water in the network is properly distributed in the first place.

Which data do housing companies lack in heating monitoring?

The decisive hurdle rarely lies in the technology in the boiler room, but in missing and inconsistent operating data. Without room-by-room heat load, documented setpoints and a weather-adjusted baseline, you can neither prove an optimization potential nor demonstrate a saving. With its documentation requirement, the GEG effectively hands you a checklist of what is often simply not available in the existing stock.

For reliable heating monitoring, a portfolio needs six categories of data above all, captured continuously and brought together:

According to KEDi, digital monitoring can meet legal requirements and continuously uncover optimization potential. In the market, though, it is still the exception. As of 30 June 2025, the KEDi provider survey shows a coverage of just 4.4 percent of apartments in German multi-family buildings. The real brakes are organizational: inconsistent data sources, missing interfaces and rollout processes across many properties. How well digitized heating systems can be connected during ongoing operation therefore matters more for success than the choice of any individual sensor. KUGU VIS (Visuelles-Informationssystem) bundles this level, visualizing meter readings, temperatures and consumption values in real time and drawing on more than 20 criteria for system diagnostics. This transparency layer of the KUGU Energieplattform is separate from billing via the KUGU Messdienstplattform.

What do balancing and automation cost in existing buildings?

Reliable prices exist above all for hydraulic balancing, while digital optimization is barely standardized in public data. For an average single-family home, co2online cites 650 to 1,250 euros including new thermostatic valves. In a multi-family building, the costs run roughly three to four times higher on average. These figures come from single-family examples and only work for portfolios as a lower bound.

A more realistic picture for larger properties comes from a study of a multi-family building with 40 units and 2,850 square meters: the hydraulic balancing cost 13,900 to 16,900 euros there, with heat savings of 28.5 to 34.2 MWh per year and payback periods of around 6.4 to 10 years. The consumption reality in the stock is sober, though: in documented co2online examples, consumption in a 6-unit building fell by only about 5.9 percent, and in a 12-unit building by roughly 4.4 percent.

For the digital level, reliable public prices per unit essentially do not exist, so a flat rate here would be dishonest. Provider and field figures serve as orientation: for EOS, KUGU cites an average of more than 20 percent savings and a contractually guaranteed minimum of 12 percent in heating energy, tied to stable usage conditions and no serious hydraulic defects. In Berlin-Rudow, 27 percent was reported; in Leipzig, 39 and 33 percent; and in a Berlin portfolio pilot across ten buildings, around 260,000 kWh and more than 18,000 euros in energy costs. Such numbers are practical examples, not an independent market average, and the platform behind them shows the range rather than a fixed return. Decision-makers should therefore compare measures by intervention depth, data maturity, proof of savings and repeatability across the portfolio.

When does operational optimization come before renovation?

Operational optimization precedes renovation when the system is functional but run in an unclear or over-supplied way and the data foundation is missing. The pressure to act is real: 60 percent of the residential building stock dates from construction periods up to 1979, and the building sector continues to miss its climate targets by a wide margin. The sensible move is to first reduce over-supply and gather real operating data before making investment decisions about heat generators, radiators or the building envelope.

Worth knowing: Hydraulic balancing under the GEG requires checking the radiators for the lowest possible flow temperature. This very reduction is what makes a building ready for a later heat pump, which is why optimization and renovation interlock.

The limits are just as clear to name: aged heat generators, hydraulics that cannot be adjusted, missing low-temperature capability and structural deficits. Comfort sets a boundary too. Each degree less in room temperature saves around 6 percent energy, yet unused rooms should not cool below 16 degrees, or mold becomes a risk. Optimization is thus a step toward insight and efficiency for better investments, not a rejection of renovation.

From existing data to the next investment

The value of heating optimization emerges where short-term consumption reduction, a solid data foundation and investment preparation come together. When you first create transparency, then control operations automatically, and only then invest deliberately, you make expensive decisions about heat generators and the building envelope on the basis of real operating data instead of assumptions.

The expectation horizon stays realistic here: market figures of 10 to 20 percent and field cases above 30 percent show the range, yet every result depends on system condition, stable usage and clean hydraulics. The KUGU Energieplattform ties these three elements together: KUGU VIS delivers the transparency, KUGU EOS handles the automated optimization, all without replacing existing heating systems.

The concrete next step is a portfolio-ready capture of system, meter, temperature and consumption data. On that basis, measures can be prioritized by intervention depth and proof of savings, then rolled out repeatably across many properties.

Frequently asked questions (FAQ)

Which GEG obligations apply to heating optimization in a multi-family building?

For water-based systems in buildings with at least six residential or commercial units, the GEG sets out several obligations. Older systems installed before 1 October 2009 must be checked and optimized by 30 September 2027. When a new water-based system is installed, a mandatory hydraulic balancing is added. Inspection, optimization and balancing are separate requirements.

Can large housing companies count on BAFA funding for heating optimization?

Only to a limited extent. The basic funding rate for heating optimization is 15 percent, with an additional 5 percent through the iSFP bonus, from a minimum eligible volume of 300 euros gross. The decisive point for portfolios: funding for system efficiency applies to residential buildings only for existing properties with no more than five units. Larger multi-family buildings should therefore not factor BAFA subsidies into the business case as a matter of course.

How long does hydraulic balancing take in existing buildings?

For a single-family home, co2online cites about 1.5 hours of data capture, roughly 4 hours of calculation and around 5 minutes of adjustment work per radiator, provided no components need replacing; two appointments are typical. This cannot be scaled up linearly to larger buildings. The number of radiators, any necessary component replacement and the property size determine the actual duration.

Which data does digital heating monitoring need for existing systems?

What is needed above all are consumption values, meter readings, temperature data, system behavior, setpoints and fault diagnostics. KUGU VIS, for example, captures these categories in real time and complements them with more than 20 criteria for system diagnostics. Only from this foundation does a weather-adjusted baseline emerge, which is what makes proof of savings and the prioritization of measures across the portfolio possible in the first place.

Can digital heating optimization start without replacing the boiler?

Yes. In practical cases, the existing system was connected digitally without any structural work, in Berlin-Rudow within a few hours and with around three days of measurement data for calibration. Reliable results, however, require stable usage conditions and no serious hydraulic defects. Unstable usage and disordered hydraulics noticeably limit the achievable savings.

When is heating optimization in existing buildings no longer enough?

Operational optimization reaches its limit when the heat generator is aged, the hydraulics can no longer be adjusted or the radiators do not allow a low flow temperature. Structural deficits and comfort conflicts set a boundary too. At that point, optimization still lowers consumption, but it does not replace changing the generator, adapting the radiators or measures on the building envelope.