MonSec – Energy system monitoring and secure database systems

Monitoring Secure

Duration: 04/2019 - 03/2023
Contracting Authority/ Sponsors: Bundesministerium für Wirtschaft und Energie (BMWi)
Project Partners: Hochschule Biberach, Institut für Gebäude- und Energiesysteme, Technische Hochschule Rosenheim, enerquinn GmbH, Weingarten, Mondas GmbH, Freiburg
Project Focus:      
© Fraunhofer ISE

The technical monitoring of energy systems and buildings is a key technology in the implementation of energy efficiency targets and quality assurance in the heat and power sector. In the project Monitoring Secure - Energy System Monitoring and Secure Database Systems, in short "MonSec", monitoring processes are investigated and new software tools are developed to promote the dissemination of this key technology. 

Modern energy concepts link different, highly efficient components to form complex systems. As the complexity of the system technology increases, so does the vulnerability to errors during commissioning and operation of the systems. Ultimately, the effectively achieved system efficiency often falls short of expectations.  

Monitoring systems that can detect such errors are an important source of information for operators. For this purpose, many measured variables must be acquired and recorded. Although modern building control systems are also capable of storing such data, in practice the available measurement data quality is often insufficient, or the available data treasure remains unused due to lack of time and costs.  

In the context of scientific monitoring, data of sufficient quality can be collected and extensively analyzed, but a high degree of standardization and automation is necessary to limit the costs. The MonSec project therefore investigates distributed, decentralized measurement technology based on Internet of Things (IoT) technologies. In this context, the development and adaptation of encryption and anonymization methods will ensure end-to-end data security from the source to the central data storage. To increase the degree of automation of monitoring and evaluation of measurement data, new AI-supported methods for labeling sensors, equipment and systems with metadata and structural data are being investigated. Automatic fault analysis enables additional added value in this context.

Finally, the developed methods will be prototypically tested in ongoing monitoring projects of the participating partners. 

Through the participation of the universities, the transfer of knowledge into practice is also to be achieved: Here, further training courses are being developed for the various professional branches such as planners, architects and facility management.

More Information on this Topic:

Research Topic

Building Operations Management

Business Area

Energy Efficient Buildings