TalTech’s energy manager Janar Küla, professor Eduard Petlenkov and one of the founders of R8 Technologies, Siim Täkker, discuss how the innovative product was created and how it helps solve global problems.
High energy consumption
The real estate sector accounts for nearly 40 percent of global CO2 emissions. Estonian buildings consume an average of 53% of Estonia’s energy costs, which is nearly 15% higher than the European average. In order to reduce our CO2 footprint, we need to find solutions both domestically and globally to reduce energy consumption.
However, according to Siim Täkker, this is made difficult by the fact that property owners and facility managers are not eager for rapid changes because their implementation is generally a lengthy and costly process. “It’s a very conservative but impactful sector – buildings are planned and constructed for years, and managed and maintained over decades. The real estate sector operates at a completely different pace compared to the IT sector,” he explains.
Therefore, it is necessary to create solutions that property managers can conveniently and quickly adopt with a short payback period.
“Modern digitized buildings contain a big load of data related to indoor climate, technical systems, energy consumption, maintenance, and management, whose full potential has not been fully utilized,” says Täkker. “Our company’s goal is to harness this data using artificial intelligence in an automated form and provide value to customers.”
R8 Jenny helps to operate buildings more efficiently
As a novel solution, R8 Technologies and TalTech collaborated to create R8 Jenny – a digital operator that helps to solve global issues such as excessive CO2 levels and an energy crisis, as well as addressing company-level challenges like reducing (energy) costs and thereby increasing revenue.
Managing and efficiently controlling energy consumption systems has been a significant challenge that R8 Jenny has successfully addressed. “Now people can focus on smarter tasks instead of constantly monitoring and making minor adjustments to the system – artificial intelligence can handle that,” says Petlenkov.
R8 Jenny can predict and plan the building’s energy consumption for the next day. This information also reaches energy suppliers, so they don’t have to order additional energy that ultimately goes unused. “The cleanest energy is still the one that isn’t produced,” says TalTech professor Petlenkov, and with R8 Jenny, it becomes possible to reduce energy production and thus decrease the CO2 footprint.
TalTech’s energy manager, Janar Küla, has a background in electrical engineering and energy trading, and he first encountered R8 when working for an energy service company: “In this field, such an innovative product was already making waves a few years ago. However, at that time, the solution wasn’t as widely spread. When I became TalTech’s energy manager, the opportunity arose to acquire this product. We did the groundwork, held thorough negotiations, signed contracts, and now the service has been in use for over a year in three TalTech buildings,” Küla explains.
During this time, significant resources have been saved. From March of last year until February of this year, thanks to the new technology, they achieved savings of 4.9% on electricity, equivalent to 65 MWh, and 23% on heating, equivalent to 435 MWh. After deducting the service fees, the net gain was over 40,000 euros.
Today, large international corporations in both Estonia and Europe are already using the R8 Jenny solution. For example, this year, the software’s usage was expanded to all buildings in the Ülemiste City campus in Estonia, and across Europe, the solution is used in buildings totaling over 2.2 million square meters from Portugal to Finland.
Siim Täkker emphasizes that R8 is already at the forefront globally, but the plan is to continue advancing and developing artificial intelligence according to the desires of clients and current/future challenges in the world. TalTech researchers plan to develop algorithms in the future that can improve building energy labels without the need for extensive renovations or significant expenses. “This is one of the first steps that pays off immediately without spending money,” says Petlenkov. “Currently, we are analyzing data to determine how much artificial intelligence can regulate building energy costs.”
Petlenkov draws a comparison with the development of cars: “I remember when I bought my first car 20 years ago, it was normal for it to consume ten liters of fuel per hundred kilometers. Now it’s significantly less. The same goes for buildings – they can consume significantly less energy than we can imagine.”
Currently, research is heading in that direction, but they are still at a stage where the savings are small, and people need to contribute to the technology. Therefore, the research work must continue, hoping that in the near future, a solution can be created to further reduce the carbon footprint even more effectively.