News August 16, 2021

Egain presents Sustainable City Award to Berlinovo Apartment GmbH

Egain presents Sustainable City Award to Berlinovo Apartment GmbH

Figure 1: Constanze Dühring and Ute Rüße (right in the photo) accept the Egain Sustainable City Award from Eva-Maria Metz and Janot Dohrmann(Egain Germany)
Note: The applicable Corona regulations were observed when the photo was taken.

The Egain Sustainable City Award is presented to property owners who have achieved good savings with high energy and emissions reduction as a result of Egain’s services. This includes ensuring the management of the “low hanging fruit” in the heating system without human intervention using AI. In addition to this, active and systematic energy management by the technical stakeholders and management commitment are crucial. If all those responsible for the building, both internal and external, pull in the same direction, it is much easier to develop existing buildings towards achieving set environmental and energy targets.

Learn more about the Egain Sustainable City Award

All these factors come together Egains project together with Berlinovo Apartment GmbH, who are the latest recipients of the Egain Sustainable City Award. Within just one year, over one million kilograms of CO2 were saved. For Berlinovo, the path to efficient and environmentally friendly buildings has a long-term focus. In addition to the automated optimization by Egain AI, Berlinovo, supported by Egain energy experts, regularly works with the energy data to ensure high system availability and continuous improvement of the energy quality.

The supervising Egain energy expert, Janot Dohrmann, confirms: “Berlinovo is working in an exemplary manner to increase the efficiency of its properties without losing sight of the concerns and comfort needs of the tenants. This project shows how ecological and social factors can be reconciled. And last but not least, it pays off financially.”

As a prize for the award, Egain had 50 trees planted on behalf of Berlinovo by the Swedish NGO Vi Skogen.

General functioning of AI-based heating optimization.Building technology systems provide a large amount of important data on energy consumption and system status. A computer can process a significantly larger amount of data in a short time than a human being. Algorithms use measured temperatures from the flow and return of the heating circuits as well as temperature and humidity from the rooms and other operating and consumption data to create an accurate energy profile of the respective building. Depending on the renovation status of the property and site characteristics, such as orientation or exposure to wind, a building’s heat storage capacity will vary. Coupled with a weather forecast, the algorithm continuously calculates the actual amount of energy needed to keep the individual rooms or zones within the desired temperature band.

The first step was digitization.
For this purpose, a specification sheet was prepared in advance, which on the one hand provides an overview of the current heating technology and measurement infrastructure in the properties to be considered and on the other hand defines the customer’s expectations with regard to future data evaluations and optimization results. In this case Berlinovo faced the challenge of different types of systems and missing data from their properties. The properties are heated partly with gas and partly with district heating via one-pipe and two-pipe systems. Tenant complaints could not be verified before the project began, resulting in high administrative expenses due to on-site visits. The objective of the project was therefore not only to realize savings through the algorithm, but also to establish an energy management system that could be handled by the building management. A particular focus was on the continuous and structured presentation of the hydraulics and control technology, as well as on the comparative energy analysis of the different properties and effective alarm management.

With these data and objectives, the necessary sensor equipment was determined. The algorithm only requires the measurement of one heating circuit and a few reference rooms. For further objectives and the creation of transparency, however, it is often useful to collect additional data. In the case of Berlinovo, 685 room sensors were installed in 30 buildings to measure temperature and relative humidity. Because the room sensors are wireless and easily installed inside an apartment, the customer was able to install them themselves, with telephone support from Egain. The sensors on the heating circuits as well as the outdoor temperature sensors/data gateways (Edge Hub) and modules for remote meter reading were installed by a local installer.

Energy management “up and running” after only six weeks.
Within a short time, all buildings were online. With the data now available, the customer portal was set up in accordance with the specifications. For example, special attention

Figure 2: Heating central sensors
Figure 2: Heating central sensors

was paid to the structure and navigation setup of the system according to the type of heating in order to quickly compare the consumption values within the respective group. Furthermore, in addition to the evaluation of consumption and CO2 emissions with the corresponding trends, an alarm was also set up for room temperatures that drop too low.

Berlinovo’s energy management is supported by Egain with an annual energy analysis.

Low-hanging fruits with the help of artificial intelligence.
Continuous savings potentials are generated by the algorithm as shown in the first section. Thus, a large part of the portfolio can be left to self-learning optimization. For the properties that showed large energy potentials in the continuing energy management, further optimization measures were developed and monitored after implementation. Climate neutrality of buildings cannot be achieved by one technology – an effective and transparent management of optimization measures is therefore the central task of energy management.

Figure 3: Egain Edge Hub
Figure 3: Egain Edge Hub

Results and outlook
Since the start of the project, the heating energy requirement has been reduced by an average of 19.8 kWh/m² across all properties compared with the reference year 2018. At the same time, over 1 million kg less CO2 has been emitted to date. These figures are based on measured and weather-cleaned consumption values.

But the optimization path does not end here. The path to a climate-neutral building involves a series of measures that must be planned and monitored. The new Egain Energy Target module is designed for this purpose: Based on the consumption data already recorded, the path to climate neutrality is simulated via further measures inside Egain Edge. The user can run through various measures already stored with data. In this way, it can be determined specifically which measure can be used to achieve the necessary CO2 reduction in a cost-efficient manner.

Would you like to know how you can operate your systems more efficiently without any loss of comfort for your tenants? Talk to us!


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