In 2020–2023, Forum Virium Helsinki and VTT (Technical Research Centre of Finland) tested tools developed by VTT for building energy efficiency and maintenance as a part of the EU-funded Beyond project. With these tools of the future, we can achieve more effective energy renovation projects and anticipate maintenance operations with the help of machine learning.
The international Beyond project had access to tools developed by VTT which help building owners save in energy costs and do their part for achieving carbon neutrality, quickly and easily.
With the VTT-developed Renovation tool, a property owner can easily examine the most suitable energy renovation projects for their building. The owner can get started easily by providing some information about the building, such as the year of construction, building type, number of floors, total area, number of occupants, number of dwellings, general heating method, and the heating method for domestic water. Based on this data, the tool is able to calculate other values that affect an energy renovation project, such as the U values of the walls, which indicate heat insulation capacity, or the type of windows in the building. The user can also edit the values when necessary to achieve even more accurate assessments.
The user also has to provide the building location at the city level, so that the tool can take local weather conditions into consideration. After this, the user can simulate potential energy renovation projects and their impact, which may include repay time, CO2 emissions and energy savings. With the information gained, the user can take measures such as moving to a geothermal heating system or installing solar panels.
Putting building data to use
These days, a modern building produces immense amounts of data, but this data is rarely used in building maintenance. Electricity companies measure the total energy consumption of a building very precisely, and it is fairly easy for the building owner to access this data through electricity bills or the energy monitoring services provided by the companies, for example.
In addition to energy consumption, the values being measured include water consumption and indoor temperature. With the help of this information, the building’s use can be optimised and energy savings can be achieved by lowering the temperature, for example. However, this is but a drop in the ocean of data that a modern building can produce.
A modern office building may have over 5,000 measurement points in its building automation systems. This means over 5,000 different values being measured in a single building. These measurements may include the temperature of the ventilation system air supply, the room temperature, and the energy consumption of the lighting and cooling systems. The values measured can be used to assess things such as user comfort, but also to anticipate upcoming maintenance operations.
VTT has even developed a tool dedicated to anticipating maintenance, which can be used to prepare for ventilation system maintenance, for example, earlier than any brewing problems can be sensed by humans. The tool makes use of machine learning and artificial intelligence when processing the measurement data for the building. In practice, the tool accesses measurement history and looks for deviations.
Optimising electricity bills with AI
The production of renewable energy increases the fluctuation in energy prices, which also requires flexibility from a building’s electricity consumption. Related to this, VTT has developed a prototype of an AI-based application that minimises the electricity bill of a building that is heated electrically using market-price electricity, while also maintaining a good temperature for the occupants. VTT also developed another software prototype related to market-price electricity, which learns to minimise the electricity bill of a building with the help of AI. This is done by optimising the battery charging and discharging cycles in a building that uses electricity produced by local solar panels and has the opportunity to sell its surplus electricity, in addition to conventional electricity consumption.
The tools mentioned above have been tested as a part of the Beyond project. The tools are still in development, but the results have been promising so far. The tools are not publicly available for the moment.
Read more about the Beyond project: beyond-h2020.eu
Photo: Andy Ngo, Helsinki Partners