Success-Story of our Partner OPAL-RT
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SESA How can our energy system become smart but still secure?
The so-called "energy revolution" and simultaneous digitization of the energy sector have increased the complexity of the energy supply. In future, the energy system will be made up of many small producers, storage facilities, and numerous heterogeneous ICT components for networking and intelligent control and automation.
One challenge of these smart grids is the accelerated rollout of information and communication technology, which dynamically develop and adapt the energy system – but in this application context they have never been tested for their interaction and interdependencies. In addition to this, external cyber-criminal attacks represent a significant risk and are a key issue.
The Smart Energy Simulation and Automation (SESA) Lab allows large-scale, real-time co-simulation of impacts on energy supply systems under realistic conditions to facilitate integration of new components into the system; to identify critical situations; and to develop any adaptations that might be required. The SESA-Lab infrastructure comprises of following main features:
- Real-time and offline simulators and co-simulation frameworks - particularly mosaic - for modelling of cyber physical energy system.
- Smart energy automation including physical and/or virtualized operational technologies.
- Industrial and open source SCADA systems for Power and ICT systems monitoring and management.
- Big data analytics and security platform including anomaly detection and ISMS.
A special feature of the SESA Lab installation is the topology free allocation and combination of inputs and outputs. To ease the simulation planning and execution process, SESA includes a virtualization server (VM cluster) that can provide virtual machines for software-based simulations (with the possibility of coupling with hardware-based real-time simulation and automation system in the Lab), development environments, or licensing servers for possible runtime environments. Such a virtualized and topology free allocation allows SESA to provide remote access to external users.
Large scale Real-time and offline Smart Grid simulations
- Holistic system approach (design of experiment based statistical experiments)
- Coupling heterogeneous simulations
- Transparent SCADA viewpoint and control of the conjointly (heterogeneous) simulated system
- Testing integrated control application
Prototyping for Smart Grid control concepts
- Black / White / Grey Box testing
- Centralized and decentralized control approaches (e.g., Multi-Agent Systems)
- Standard compliant communication and control from devices up to SCADA systems
Framework to assess cyber-security/communication integrity and response mechanism
Development and testing of added value services based on Smart Meter Gateway Infrastructure
Simulation tools and frameworks
- Mosaik is a flexible Smart Grid co-simulation framework that allows to reuse and combine existing simulation models and simulators to create large-scale Smart Grid scenarios. These scenarios can then serve as a test bed for various types of control strategies (e.g., multi-agent-based control) or other algorithmic solutions for future power systems.
- The OPAL-RT digital real-time simulator (eMEGAsim and ePHASORsim) software allows the execution of highly detailed, dynamic power grid and network component models on dedicated FPGA-based signal processors. ePHASORsim is capable of modelling up to 30,000 nodes. The OPAL simulator provides analog I/O and following communication protocols for hardware and software interfacing: Analog inputs and outputs, 60870-5-104, IEC 61850 GOOSE and Sample Value, Modbus RTU/TCP, C37.118 for PMU.
- EXata Scalable Network and Attero Spirent are two commercial real-time communication network simulators and emulators to model and study the network behaviour with high fidelity, accuracy, and precision.
- Offline simulation tools are provided individually or as part of mosaic-based co-simulation platform such as PowerFactory, OMNET++, pandapower and MATLAB via virtualization server.
Automation components
- Field devices: Phoenix Remote Terminal Units, National Instruments NI CompactRIO, Beckhoff PLCs, KoCoS Grid Automation System
- Spitzenberger APS 1000 amplifier for Controller Hardware in the Loop (CHIL) testing
- Virtual or software-based OT (vRTU, vIED,vPMU) for large scale simulation
- Industrial SCADA system from PSI and KISTERS
- Open source ICT monitoring and intrusion detection system (based on Snort and Check-MK) and industrial network monitoring and detection tool (Rhebo industrial protector)
- Smart Meter Gateways and Controlboxes of different vendors, licensed GW administration, Meter Data Management and CLS management
Data analytic platform
- An open source data stream management system, Odysseus (https://odysseus.informatik.uni-oldenburg.de/)
- A nosql database, Cassandra (http://cassandra.apache.org/). The data can be stored in short-term as well as long-term for further analysis.
Smart Grid Control Centre at SESA
SESA-Lab includes a smart grid control room workplace to test new functionalities of future energy grid and adequate provisioning of information to humans as well as to train operators for the new situation. In this control centre, three industrial SCADA DMS are installed (PSI Control, KISTERS ControlStar, BTC PRINS) and an open source SCADA interface based on OpenKonsquenz requirements.
The industrial and open-source SCADA system are integrated to real-time and offline (co-) simulation platform at SESA-lab (also through mosaic) which provides the capability of interfacing the SCADA to “virtual grid” and therefor possibility of testing SCADA for different operational scenarios.
The research directions around the SCADA infrastructure replica are, not limited to:
- Testing performance of operators in different work environment (visualisation schemes or different operational scenarios e.g. blackouts)
- Integration of new source of information (e.g. ICT health, low voltage grid data) in conventional SCADA system
- Developing advanced grid operation functions e.g. adaptive state estimation, control interaction management
- Automated data management and engineering
