The energy-efficient transformation of existing buildings is an investment in the future. It plays a central role in achieving climate protection goals and also increases property values. Nevertheless, the renovation rate is at a historically low level.
Can artificial intelligence help to eliminate the uncertainty factor in terms of profitability? Daniel Gerdelmann, Head of ESG & Sustainability at apoprojekt, talks about data-driven planning as the key to sound renovation decisions.
Market shifts and energy performance
An apartment building in Hamburg's sought-after Rotherbaum district, built in 1993, 12 units, balconies, garden access, underground parking, a sure-fire success, one might think. Were it not for the ‘E’ in the energy performance certificate. According to a study by Sprengnetter, 40 per cent of apartment buildings in the city on the Elbe fall into energy efficiency class E or worse and are therefore considered ‘brown’ properties; nationwide, the figure is 43 per cent.
This example illustrates a fundamental shift in the market: the old mantra of ‘location, location, location’ is still relevant, but energy efficiency is becoming increasingly important and is emerging as a real counterpoint. Those who fail to invest in the future viability of their properties risk losing value or even facing vacancy. Conversely, according to a profitability analysis by Prognos AG on behalf of WWF Germany, residential properties with very good efficiency ratings achieve up to 30 per cent higher sales proceeds than buildings with the worst consumption figures.
On behalf of an institutional investor, apoprojekt is carrying out the energy-efficient renovation of a 15,000 m² residential complex at St.-Cajetan-Straße 26–38 in the Ramersdorf-Perlach district of Munich. © Markus Traub
False restraint: climate targets are receding into the distance
Energy-efficient renovations not only increase the value of real estate. Above all, they are a key lever for climate protection. There is an urgent need for action here: according to the Climate Protection Act, Germany wants to be greenhouse gas neutral by 2045. However, current projections show that this goal cannot be achieved with the existing instruments.
Germany is also at risk of missing the targets set by the EU Effort Sharing Regulation for the period 2021 to 2030. This is mainly due to the building sector, which is one of the two main contributors alongside transport. Building operations alone account for around 35 per cent of final energy consumption and 30 per cent of CO₂ emissions.
Overall, the emissions gap has increased by 78 million tonnes of CO₂ equivalents compared to the previous year, to 110 million tonnes. Although the amendment to the Climate Protection Act in July 2024 has taken some pressure off the boiler by moving away from sector targets, it does not release the industry from its responsibility. Rather, it is time to finally kick-start the renovation process.
In 2024, only 0.69% of the building stock was modernised to improve energy efficiency. However, in order to achieve greenhouse gas neutrality by 2045, this figure would have to rise to 1.9% by 2030.
Office properties are also gaining value through decarbonisation. At Karl-Martell-Straße 60 in Nuremberg, apoprojekt is bringing 26,000 square metres of space up to the latest energy standards. © apoprojekt
AI beats gut feeling
So, what does all this have to do with artificial intelligence? There are many reasons for the low willingness to renovate: high construction and financing costs, regulatory uncertainties, an opaque jungle of subsidies and, last but not least, rent regulations in the form of lowered caps and rent controls.
The common denominator? A lack of predictability and calculability. This is precisely where AI comes into its own. To gain an even better understanding of the existing building stock, apoprojekt is collaborating with the Austrian deep tech start-up OPTIMUSE. Its platform for AI-based building planning enables objective, data-driven decisions to be made within a very short time.
Prescriptive analyses provide specific recommendations for action
Energy-efficient renovation can easily cost over £1,000 per square metre of gross floor area (GFA). This makes it all the more important to get the maximum energy efficiency gain from every pound invested.
OPTIMUSE first digitises the available static building data, cleans it up and fills in any data gaps. On this basis, the software then creates a digital twin that can be used to perform comprehensive analyses and building physics simulations.
For example, how does the heating load behave after façade insulation? The simulation calculates exactly how much heat is needed to ensure a comfortable room temperature even on the coldest days. This makes expensive oversizing – in this case of the new heating system – a thing of the past.
OPTIMUSE can also run through different scenarios: What energy savings does window model X achieve and at what cost? What is the cost-benefit ratio for model Y? The result is reliable recommendations for action that show which energy-efficient renovation measures really pay off.
“The costs of energy-efficient renovation are too high to rely on estimates or empirical values. That is why we rely on software support from OPTIMUSE: an AI-supported platform that uses detailed building data and individual targets to determine the most cost-efficient renovation strategy with technical measures, investment and energy-saving potential, and various scenarios for achieving the targets. This enables intelligent, data-based decisions and accelerates the transition from conception to execution. Away from theory, towards practice. Only when we use software that helps us implement measures can we make a difference.”
Daniel Gerdelmann, Head of ESG & Sustainability at apoprojekt