Energy Optimization Service for Buildings: Savings & Performance

An energy optimization service for buildings takes over the ongoing, automated control of the heating system, including monitoring, plant diagnostics and reporting while the system stays in operation. Providers such as KUGU guarantee at least 12 percent heating energy savings and reach more than 20 percent on average, manufacturer-independent and without renovation or a heating system replacement. For housing companies, that translates into measurable cost and CO₂ savings without any investment in new plant technology.

For housing companies and building operators, this topic matters right now because energy costs and regulatory pressure keep rising, while structural renovations take years and tie up large amounts of capital. An energy optimization service works differently: it starts at the operational level and often shows results within a few weeks, independent of renovation cycles or funding deadlines.

The question here is usually not whether savings can be achieved technically, but how they translate into a viable contract model for your portfolio. Four factors determine how quickly a pilot project pays off:

What does an energy optimization service for buildings actually do?

An energy optimization service controls the heating system automatically and based on actual demand, monitors operation in real time and delivers regular reporting, all without anyone needing to intervene on site. The foundation is a digital building twin that is continuously synchronized with sensor and consumption data and makes optimization potential visible.

Digital building twin: a virtual, continuously synchronized replica of a real building that serves as the basis for automated, predictive control. Issues such as fouling in the heat exchanger or faulty sensors can be identified early, before they lead to failures or higher consumption.

Building on this, KUGU EOS continuously adjusts energy supply to the building model, usage patterns and weather forecasts. In parallel, KUGU VIS makes all operational data visible in real time and automatically detects faults or inefficiencies, without a technician ever needing to travel to the site. The need for this is significant: according to the dena Building Report, 79 percent of Germany's nearly 20 million residential buildings are still heated with oil or gas, and more than 5 million heating systems are older than 30 years. At this scale, optimization is realistically only achievable through automated, software-based solutions.

In practice, this removes several manual tasks from conventional operations:

The technology runs independently of the heating system manufacturer and can be retrofitted into existing buildings. To see how a digital twin is actually built and calculated in an existing property, our article Digital Heating Optimization: Efficiency Through the Digital Twin walks through the example of a Berlin apartment building with commercial units dating back to the 1980s.

How much heating energy, cost and CO₂ can realistically be saved?

Providers such as KUGU guarantee at least 12 percent heating energy savings compared with conventional operation, and the actual figures achieved average more than 20 percent across energy, cost and CO₂. This calculation is based on a stable building usage pattern without major hydraulic defects, comparing each year to the previous one on a climate-adjusted basis.

How solid this order of magnitude is in practice becomes clear in a pilot phase that Gewobag ran with KUGU between October 2024 and March 2025 across ten equipped buildings. Over that single heating season, roughly 260,000 kWh of energy, more than 50 tons of CO₂ and over 18,000 euros in energy costs were saved. The 12 percent guarantee was met in all ten buildings and, in some cases, significantly exceeded.

Real-world proof from Gewobag: "We were able to reach KUGU's 12 percent savings guarantee in every building, and in some cases exceed it significantly," says Dominik Unger of Gewobag ED on the pilot phase during the 2024/2025 heating season.

A second case, documented by dena, goes even further: a residential and commercial building in Berlin-Rudow with 12 residential units dating from the 1980s cut its energy consumption during the 2023/2024 heating season by 27 percent through a digital twin and smart heating control, with no structural renovation at all. In absolute terms, that amounts to roughly 87,480 kWh and about 20 tons of CO₂ equivalent. The dena documentation of the showcase also records an improvement of two full energy efficiency classes.

One point matters for context here: both figures are individual case results from concrete pilot projects, not a certified market-wide average. They do show, however, the realistic order of magnitude when the building, its usage and its plant technology are reasonably stable. The article Heating Optimization in Existing Buildings: Levers, Costs, Savings Potential covers further levers in more depth, including hydraulic balancing and operating parameters.

How are energy optimization services billed, and how do you recognize a viable offer?

Three billing models have become established in practice: a fixed fee per residential unit and year, a tiered rate per portfolio based on the number of connected systems, and a success-based fee tied to the savings actually achieved and guaranteed. There is currently no independent, market-wide pricing statistic for these software-based optimization services; publicly available pricing exists mainly for classic energy-saving contracting.

This classic performance contracting model differs structurally in important ways: it typically ties a building owner to an energy service provider for 8 to 15 years, with the provider covering upfront investment in renovation and plant technology and refinancing it through guaranteed savings of 20 to 30 percent. Berlin's Energiesparpartnerschaften, a contracting program running since 1996 for more than 1,400 predominantly public buildings, achieve an average guaranteed saving of 26 percent and around 12.5 million euros in annual energy savings, as shown by the BBU report on contracting in the housing industry. A software-based energy optimization service needs neither this upfront investment nor a long contract term, because it works with the existing system rather than requiring renovation.

You can recognize an economically viable offer by whether the fee is tied to a transparently calculated, actual savings figure rather than a flat monitoring fee. This also matters legally: a legal opinion commissioned by dena finds that digital heating optimization, provided as an ongoing service with recurring payments, can be passed on through operating costs when there is a direct functional connection to the central heating system and the principle of cost-effectiveness is maintained.

Legal context: the relevant legal basis is Section 7(2) of the German Heating Costs Ordinance (Heizkostenverordnung) and Section 2 No. 4 of the Operating Costs Ordinance (Betriebskostenverordnung). According to the dena legal opinion from July 2025, monitoring alone, without an actual optimization measure, is not sufficient to qualify for cost pass-through.

Which selection criteria point to an economically viable provider?

Four criteria determine whether an energy optimization service works across a real portfolio: manufacturer independence, retrofit compatibility with existing buildings, integration into existing infrastructure, and scalability.

The article Heating System Diagnostics: Which Faults Cost Building Portfolios Money shows just how precisely good plant diagnostics can uncover weak points during ongoing operation, from persistently excessive flow temperatures to incorrectly set heating curves.

Good to know: under Germany's Energy Efficiency Act, companies with an average annual energy consumption currently above 7.5 gigawatt hours must operate a certified energy management system under ISO 50001 or EMAS. An automated energy optimization service already delivers the reliable consumption and operational data needed for that.

How does a pilot project run, from sensors to ongoing optimization?

The typical starting point is a pilot covering 5 to 10 buildings across one complete heating season, before a decision is made on a full portfolio rollout. The technical process follows three steps.

After a successful pilot phase, the real test is how well the model scales: following its ten pilot buildings, Gewobag is now planning a rollout to 250 systems, concrete proof that the approach transfers to a much larger portfolio. As a next step, it makes sense to briefly review the existing plant technology and data situation in the selected buildings before the pilot starts, and to define the expected savings as the contractual baseline in advance.

Energy optimization service or pure metering service: what's the difference?

A pure metering service records and bills consumption; an energy optimization service actively reduces it. This distinction also shows up structurally at KUGU: the KUGU Energy Platform with EOS and VIS controls and monitors the heating system itself, which is what creates the actual savings. The KUGU Metering Service Platform with AbSys, by contrast, enables digital, independent billing of heating and water costs.

In practice, that means: if you only need legally sound and transparent billing data, a metering service covers that need well. If you want to actually reduce consumption, meaning energy, cost and CO₂, you need the active control that an energy optimization solution like EOS and VIS provides. Both layers can run in parallel; they do not replace each other.

The pilot phase decides how quickly a rollout pays off

The real bottleneck with energy optimization services is rarely the technology. Digital twins, automated schedules and manufacturer-independent retrofitting have already been demonstrated repeatedly in documented projects. The bottleneck lies in deciding which compensation model fits your own portfolio size and whether the savings are calculated in a transparent, traceable way.

That is exactly why taking the detour through a small pilot is not a delay, it is a safeguard: five to ten buildings over one heating season deliver reliable, building-specific figures before you commit to 50, 100 or more systems. This exact pattern, moving from a small pilot to a broad rollout, has already proven itself as a workable path in practice.

If you are considering commissioning an energy optimization service, check three concrete things: the contractual savings guarantee and how it is calculated, retrofit compatibility with your specific building stock, and a realistic billing model for your portfolio size. A pilot project run over one heating season provides the data foundation needed to make that decision with confidence.

Frequently asked questions about energy optimization services for buildings

How soon do savings appear after starting an energy optimization service?

Within a few weeks: calibrating the digital twin takes about three days, after which automated daily schedules take over. In the Gewobag pilot, the full savings of roughly 260,000 kWh were already visible and documented after a single heating season between October and March.

Does the optimization also work with very old or mixed heating systems across a portfolio?

Yes, digital efficiency measures such as control boxes and sensors can be retrofitted regardless of the heating system's manufacturer or age. Connection happens via existing interfaces or external sensors, so even older systems can be integrated without replacing hardware.

How is it verified that the guaranteed savings were actually achieved?

Savings are calculated annually against the previous year and adjusted for climate, meaning weather fluctuations are factored out so the comparison stays fair. The basis is a stable building usage pattern without major hydraulic defects. According to provider data, this calculation method also underpins the 12 percent guarantee.

Can tenants share the cost of an energy optimization service through operating costs?

Yes, according to a legal opinion commissioned by dena, digital heating optimization qualifies as an ongoing service that can be passed through operating costs when there is a direct functional connection to the central heating system and the principle of cost-effectiveness is maintained. Monitoring alone, without an actual optimization measure, is not sufficient for this according to the opinion.

How many buildings should a pilot project for digital energy optimization include?

Five to ten buildings over one complete heating season are considered a sensible pilot size in practice, before a decision is made on rolling out across the full portfolio. Gewobag used exactly this scale before planning its rollout to 250 systems.