OFFIS Institute for Information Technology – Energy Lab
TA44 – OFFIS-eLab
Location
Escherweg 2
26121 Oldenburg, Germany

Description
The OFFIS Energy Lab provides large-scale, multi-domain experiments on smart energy systems under realistic conditions to foster innovative solutions and integrate new components. Key features include real-time communication, Mosaik co-simulation, big data, agent-based management, SCADA, smart meter gateway and interoperability testing.
OFFIS Energy lab offers hardware and software infrastructure, supporting offline and real-time simulations, such as hardware-in-the-loop testing with communication simulation and emulation. Our industrial controllers operate with protocols such as IEC 60870-5-104 and IEC 61850 for substation automation systems. To investigate multi-modal energy systems, the Mosaik co-simulation platform enables the integration of different simulation models and components, facilitating communication orchestration between simulators.
Additionally, the OFFIS Energy Lab assists users throughout their access period, ensuring effective experiment planning and execution. A unique feature of the OFFIS Energy Lab is its topology-free allocation, which provides remote access to external users for software-based simulations, with the option to couple industrial devices in the laboratory.
Testing Capabilities
- Hardware-in-the-Loop testing
- Communication simulation and emulation
- Communication interface
- Interoperability testing
- Virtualisation technology
- Co-simulation platform
Technical Equipment
- OPAL-RT real-time simulator
- Beckhoff controller
- Smart meter gateway
- RevPi
- Attero network impairment and emulation testing
- OMNeT++
- Mosaik co-simulation
Additional information
Technology Readiness Level: 4-6
Special considerations: Lab Agreement for external, lab access contract, liability insurance
Technology clusters: Information and Communication Technologies
Website: https://www.offis.de/en/applications/living-labs/sesa.html
Availability: All year
Provision of tools to prepare data sets in a FAIR way: Yes