As one of the ten largest university locations in Germany, Aachen is an important science location with the RWTH Aachen University. In addition to special research facilities, the RWTH also has numerous buildings for traditional teaching for students
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As one of the ten largest university locations in Germany, Aachen is an important science location with theRWTH Aachen University. In addition to special research facilities, the RWTH also has numerous buildings for traditional teaching for students. The very different contexts in which the buildings are used, together with the widely varying years of construction, pose a particular challenge for building management, but at the same time offer enormous potential for reducing CO2 emissions from property operations. As the first building at RWTH, aedifion is connecting the PPS lecture hall building to the platform and optimizing the operation of the building in cooperation with RWTH‘s building management.
The PPS is a modern lecture hall center that was built in 2012 on the Königshügel in Aachen. With this building,RWTH Aachen University provides its students with a modern teaching and learning center with lecture, seminar and computer rooms. With its connection to the RWTH‘s local heating and cooling system, the building has always been supplied with a particular focus on climate friendliness. In order to also consciously use resources sustainably in operation, a possibility was required that identifies and prioritizes potentials for more sustainable operation based on data and consumption. With the aedifion cloud platform, the building management of the RWTH relies on a digital tool for sustainable operational optimization that delivers results quickly and efficiently.
8 470 € annual operating cost savings (1,96 €/m²/a)
107 MWh Annual energy savings(24,7 kWh/m²/a)
14 t CO2 annual avoided emission (3,3 kg /m²/a)
Providing data availability quickly and easily is a particular trump card of the aedifion cloud platform.Because of the pre-configured edge device, an uncomplicated and simple plug-and-play installation is possible for the operating team. Within minutes, all relevant data is available on the cloud platform. In the case of the PPS, rapid transparency is therefore a promise fulfilled. Special security is provided by aedifion‘s redundant security mechanisms.To meet the special requirements of network access at the university, access to the automation system of the PPS is additionally encapsulated via a Virtual Local Area Network (VLAN).
The PPS is the first building at RWTH Aachen University to be equipped with the cloud platform. In order to quickly and completely relieve the operator team, aedifion was commissioned with its full-service solution .elevate. In this context, aedifion engineers took over the building‘s data anamnesis, created digital twins of all building technology systems and curated the results of the automatic data analysis. Together with the operating team, the implementation of measures in the specific building context was prioritized within a very short time. building context were prioritized within a very short time. The first measure implemented is the optimization of the temperature control sequence on one of theAHUs, which has already realized energy savings of 11.05 % and a reduction in CO2 emissions of 8.5 % compared to the previous year, thus avoiding 14.4 tons of CO2 emissions annually from now on. The project was closely supported by aedifion‘s engineers as part of .elevate, which simultaneously trained the operating team. The aedifion platform is now available as a digital helper for operational optimization and provides transparency for maintenance work.
As one of the largest university locations in Germany, we at RWTH naturally have correspondingly high energy turnover in our more than 300 buildings. In the PPS lecture hall building, we have started a project with aedifion to digitize energy management and quickly provide more transparency in our buildings. Both the operator and energy management benefit from the data and insights gained. I see the fast implementation through the plug-and-play connection to the cloud platform and the rapid automatic identification of optimization potential as trend-setting.
Mario Hillebrand | Energiemanager
