Smart Converter Lab

The lab hosts a wide variety of edge microprocessors, including +10 dSPACEs, +10 Raspberry PIs, and several proprietary processors from several industrial vendors. All microprocessors have interfaces via IoT gateways to the DTU cloud platform and cloud platforms of external collaborators.

+15 active front end (AFE), drive converters and electrical motors from various vendors and with several power ratings (from 2 kVA to 50 kVA)

Analog three-phase 4-quadrant power amplifiers (smaller with 25 kVA and larger with 150 kVA power rating) with outstanding overload characteristics allowing versatile platform for PHIL tests, lab supply, component testing combined with grid studies. Amplifiers can be modeled as grids, where different grid situations can be emulated under controlled conditions such as voltage and phase non-symmetry, frequency change and phase jumps.

An industrial grid-tied battery (30 kVA power rating, 80 kWh energy rating), with reconfigurable cell-to-cell monitoring controllability and embedded AFE.

+10 programmable dc electronic sources/loads.

Lab is also connected to a configurable low voltage (400V) grid managed by PowerLabDK with 22 lab cells, one of which is EV lab where we can access Smart EV chargers and a local fleet of EVs. Via the same cell system, lab also has access to one of Europe’s most powerful hardware in the loop platform integrated with high-performance computing facilities provided by DTU’s Computing Center.

Lab Setups

The lab is organized as a number of general purpose mobile setups, where a wide variety of systems can be emulated in a controlled environment and also cooperatively controlled, either via a local communication network or a DTU cloud platform. Furthermore, lab has bidirectional data access to several demonstration sites in the real-world, from controllable water pumps and EV charging stations, to fleets of electrical vehicles.

Exemplary applications that have been emulated and tested within the lab itself are:

• Condition monitoring of electric machines and drives
• Smart electronically regulated loads (e.g. fans, pumps, compressors)
• Energy islands (i.e. AC and DC microgrids)
• Grid connected converters for renewables and energy storage systems
• PV and wind power plants, HVDC systems
• Electrical vehicles (e.g. cars, ships, aircrafts)
• Cyber-security of converter systems
• Machine learning and other advanced algorithms for control and diagnostics of broad converter-based power systems

Tomislav Dragičević, DTU Professor

https://orbit.dtu.dk/en/persons/tomislav-dragicevic