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© Fraunhofer IWES, Paris, 26.06.2013,
Real-Time Simulation of Distribution GridsPaul Kaufmann
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013,
Real-Time Simulation of Distribution Grids with high Penetration of Renewables and Distributed Generation
Dr. J.-C. Toebermann, D. Geibel, M. Hau, R. Brandl, P. Kaufmann, C. Ma, Prof. Dr. M. Braun, Dr. T. Degner
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 3
The Fraunhofer-Gesellschaft in Germany
Fraunhofer-Gesellschaft, the largestorganization for applied research inEurope
undertakes applied research of direct utility to private and public enterprise and of wide benefit to society.• 80 research units, including
60 Fraunhofer Institutes• 20, 000 staff• € 1.8 billion annual research budget
Research centers and representative offices in Europe, USA, Asia and in the Middle East.
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 4
Fraunhofer IWES:Institute for Wind Energy and Energy System Technology
Research spectrum: Wind energy from material development to grid connection Energy system technology for all renewables
Foundation: 2009 Staff: approx. 500Annual budget: approx. 30 million eurosDirectors: Prof. Dr. Andreas Reuter, Prof. Dr. Clemens Hoffmann
Formerly: Fraunhofer-Center für Windenergie und Meerestechnik CWMT in Bremerhaven Institut für Solare Energieversorgungstechnik ISET in Kassel
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 5
Fraunhofer IWES: Business Fields
Environmental analysis for wind and ocean energy
Control and integration of decentralized converters
Energy and grid management
Energy supply structures and systems analysis
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 6
Renewable and Distributed Generation in Germany
Share of Renewable Energies in Power Supply Today: 23% 2020: 35% 2030: 50% 2050: 80%
Renewable Energies in Distribution Grids 45 GW capacity in LV and MV grids Reverse power flows -
example LV grid “Sonderbuch”Max. load: 130 KWp Max. feed-in: 1,200 KWp
Estimation of 42.5 billion Euros fordistribution grid reinforcement up to 2030
Sources: J. Appen, M. Braun, T. Stetz, K. Diwold, D. Geibel, “Time in the Sun”, IEEE Power & Energy Mag., vol.11, pp.55-64, March 2013
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 7
Project 1: Holistic Smart Distribution Grid Simulation
minimize charging costs improve integration of renewables reduce network extension costs
challenge: What are the behavioral and electric interdependencies and the dynamics within a distribution network?
intelligent generators and loads exhibit complex behaviors depend on local and global events and
decisions follow different and sometimes
contradicting goals example: charging of electric vehicles
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 8
Project 1: Holistic Smart Distribution Grid SimulationExample: Integration of Electric Vehicles
our vision: a system for HIL simulation and testing of system operation control strategies power HIL simulation of electric vehicles
Dr. J.-Chr. Toebermann
Funded by BMU, 0325402
© Fraunhofer IWES, Paris, 26.06.2013, 9
Project 2: Test Bench for System Stability based on Distributed Generation
Factors of influence of network stability
Balance between production and consumption
Coming inverter-dominated areas
Balance more complex
Compensation of system stability necessary
Overview of stability issues
Ron Brandl, Dominik Geibel
© Fraunhofer IWES, Paris, 26.06.2013, 10
Overview of stability issues 2
Classic network stability
Prospective power plant change
New system stability necessary
Rotor angle stability
Frequency stability
Voltage stability
Compensation of conventional power plants stabilities regulation effect
require new stability functionalities of DER
Project 2: Test Bench for System Stability based on Distributed Generation
Ron Brandl, Dominik Geibel
Source: Definition and Classification of Power System Stability, IEEE/CIGRE Joint Task Force on Stability Terms and Definitions, IEEE Transactions on Power Systems, Prabha Kundur et. al.
© Fraunhofer IWES, Paris, 26.06.2013, 11
State-of-the-art Network Simulator
Advanced PHiL Test Bench
Interaction between simulator and Device under Testing (DUT)
No feedback from device Feedback by current measurement as input for U/f calculation at network connection point
Voltage and frequency curves
- Fixed before test run- Independent from DUT
Depends on interaction between simulated network and DUT
Characteristics of network connection point
- Emulated by physical resistance- Network impedance is fixed
- Simulated - Adopted due to network behaviour
Power system capability
- Less complexity- No interaction between different functionalities
- Entire transmission/distribution networks- Influence of complex functionalities
Comparison between state-of-the-art and PHIL-Test-Benches
Project 2: Test Bench for System Stability based on Distributed Generation
Ron Brandl, Dominik Geibel
© Fraunhofer IWES, Paris, 26.06.2013, 12
Simulation Model for Stability Analyses Transmission/Distribution networks
Prospective change of inverter dominated areas
3phase EMT model for PHIL simulation
>2500 nodes in transmission level and >100.000 nodes in distribution level
Project 2: Test Bench for System Stability based on Distributed Generation
Ron Brandl, Dominik Geibel
© Fraunhofer IWES, Paris, 26.06.2013, 13
Transmission/Distribution networks
Prospective change of inverter dominated areas
3phase EMT model for PHIL simulation
>2500 nodes in transmission level and >100.000 nodes in distribution level
Development of distribution network equivalent
Simulation Model for Stability Analyses 2
Project 2: Test Bench for System Stability based on Distributed Generation
Ron Brandl, Dominik Geibel
© Fraunhofer IWES, Paris, 26.06.2013, 14
Multi –Purpose Test Bench for Stability Research
Real-Time Simulation Transmission/Distribution level EMT signal output of defined
network buses Network fault
Generation unit Up to 300kVA Up to three units Rotation and static
DER Self-controllable Stability support
AcknowledgmentsWe acknowledge the support of our work by the German Ministry of Environment, Nature and Nuclear Safety and the Projekträger Jülich in the frame of the project “DEA-Stabil” (FKZ 0325585A).Only the authors are responsible for the content of the publication.
Project 2: Test Bench for System Stability based on Distributed Generation
Ron Brandl, Dominik Geibel
© Fraunhofer IWES, Paris, 26.06.2013, 15
Project 3: Test Benches for Controllers of Wind Turbines / Wind Parks
HIL-Simulation and control for grid integration of Wind Energy
1. Wind park controller
Participation in grid voltage support (reactive power at PCC)
Active power control at PCC
2. Control on wind turbine level
Actuator of wind park controller (active / reactive power)
Fault-Ride-Through
Synthetic inertia, i.e. replicating the natural inertia in the grid
General aim: grid-friendly behavior = stable control system, avoid oscillations
Melanie Hau, Park Control and Real-Time Simulators
© Fraunhofer IWES, Paris, 26.06.2013, 16
Development of Wind Park Controllers:
1. Software-in-the-loop (Basis: detailed model of the wind park / grid)
model insecurities (parameters, communication dead-times)
Software-only (hardware-related issues ignored, e.g. signal exchange)
2. Commissioning and testing in real wind parks
Testing for few, non-critical operating points
Environmental conditions (wind, grid) not reproducible
High costs
Additional hardware-in-the-loop testing prior to commissioning
Hardware controller and communication system connected to a real-time simulator of the wind park and superior grid
Systematic testing: reproducible, safe & cost-effective hardware testing
Project 3: Test Benches for Controllers of Wind Turbines / Wind Parks
Melanie Hau, Park Control and Real-Time Simulators
© Fraunhofer IWES, Paris, 26.06.2013, 17
Basis: model library in Matlab/ Simulink Flexible with respect to real-time environment platform Embedded into automatic test processing environment
Project 3: Test Benches for Controllers of Wind Turbines / Wind Parks
Funded by
Melanie Hau, Park Control and Real-Time Simulators
© Fraunhofer IWES, Paris, 26.06.2013, 18
Summary
Growth of wind and solar energy as well as rising E-Mobility usage will increasingly challenge grid assets, operation, and control
Real-time Hardware-in-the-loop simulation is essential for understanding the interdependencies and stability of "smart" inverters and system operation strategies and providing stability to the electric grid
The challenge of integrating "smart" grid components is urgent in Germany demanding for quick technical and regulatory solutions
Thank you very much for your attention
Contact: Paul Kaufmann / Dr. J.-Chr. Toebermannpaul.kaufmann@iwes.fraunhofer.deFraunhofer IWESKoenigstor 5934119 Kassel / Germany
Dr. J.-Chr. Toebermann
© Fraunhofer IWES, Paris, 26.06.2013, 19
Research Objectives and Real-Time Simulation
Primary objective of our research is to find solutions which are based on distributed power plants interfaced with an inverter lead to reduced / acceptable operational and investment cost ensure the current high quality standard in power supply
Application examples based on real-time simulation Simulation of distribution grid system operation Simulation of system stability based on distributed generation Simulation of grid connection of wind turbines and wind parks
Dr. J.-Chr. Toebermann