VILLASframework

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Name

VILLASframework

Screenshots

Focus Topic

Toolset for distributed real-time simulation and HIL testbed interconnection

Primary Purpose

Modular co-simulation framework

Description

Real-time simulators are already used extensively for academic research as well as industrial applications in electrical power networks. The primary application of real-time simulators is in the area of hardware-in-the-loop (HiL) simulation. In this context, HIL simulation integrates simulated components with a physical DUT in a feedback loop. In this way, the interactions of real components in a virtual overall system can be investigated with the aid of simulated subsystems. In addition to cost savings during development, HiL simulation enables the validation of components even for contingencies that cannot be realized without simulation.

An extension of the HiL approach is Geographically Distributed Real Time Simulation (GD-RTS), in which the simulation infrastructure, consisting of component test benches as well as simulation hardware, is not installed at one location, but is used coupled across geographical distances. Since in HiL simulations the communication latencies between simulation hardware and test benches have a direct influence on the mappable dynamic range of the simulation, long distances between coupled test benches are a particular challenge. However, the potential of such a Geographically Distributed Real Time Simulation (GD-RTS) is large. While in classical HiL simulation investigations with several test benches or different simulation hardware are difficult to implement due to high acquisition costs and special requirements, the geographically distributed simulation allows to use existing simulation infrastructure coupled at different locations. The integration of different test bench components enables the interaction between interdisciplinary teams of experts whose collaboration on joint component tests was not possible before. For manufacturers and/or certifiers, geographically distributed simulation enables remote access to simulation infrastructure without having to move components or personnel between locations. Another advantage is the assurance of confidentiality of, for example, model data, which in such a simulation only leaves the communication infrastructure of a network participant via defined interface.

The framework consists of several independent components, which can be combined according to requirements and needed functions:

-Central is VILLASnode as interface for the coupling between the involved components. It enables real-time data exchange via various protocols and data formats.

-In addition, VILLASweb provides a web-based user interface with which scenarios, user groups, laboratory infrastructure and measurement results can be managed. The execution of experiments can be monitored and controlled by means of a freely programmable virtual control room. For this purpose, real-time data can be transferred directly to the web-based control room via the VILLASnode interface.

-The configuration, inventory and control of the involved laboratory infrastructure is realized via the VILLAScontroller, which exchanges the current status as well as control commands and configurations between the virtual control room and the laboratory infrastructure.

Mathematical Description

No response

Website

https://www.fein-aachen.org/en/projects/villas-framework/

Documentation

https://villas.fein-aachen.org/doc.

Source

https://villas.fein-aachen.org/doc/installation.html

Year

2014

Institution

Institute for Automation of Complex Power Systems.

Funding Source

RESERVE: European Unions Horizon 2020 research and innovation programme under grant agreement No 727481. VILLAS: Funding provided by JARA-ENERGY. Jülich-Aachen Research Alliance (JARA) is an initiative of RWTH Aachen University and Forschungszentrum Jülich.Urban Energy Lab 4.0: Funding is provided by the European Regional Development Fund (EFRE).

Publications

12

Publication List

1. A. Monti et al., “A Global Real-Time Superlab: Enabling High Penetration of Power Electronics in the Electric Grid,” in IEEE Power Electronics Magazine, vol. 5, no. 3, pp. 35-44, Sept. 2018.
2. M. Stevic, S. Vogel and A. Monti, “From Monolithic to Geographically Distributed Simulation of HVdc Systems,” 2018 IEEE 19th Workshop on Control and Modeling for Power Electronics (COMPEL), Padova, Italy, 2018, pp. 1-5.
3. M. Mirz, S. Vogel, B. Schäfer, A. Monti, “Distributed Real-Time Co-Simulation as a Service,” 2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES), Waikato, NZ, Jan. 2018.
4. S. Vogel, M. Mirz, L. Razik and A. Monti, “An Open Solution for Next-generation Real-time Power System Simulation,” 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), Beijing, 2017, pp. 1-6.
5. M. Stevic et al., “A Multi-Site European Framework for Real-Time Co-Simulation of Power Systems,” IET Generation, Transmission & Distribution, Jun. 2017.
6. M. Stevic, M. Panwar, M. Mohanpurkar, R. Hovsapian and A. Monti, “Empirical study of simulation fidelity in geographically distributed real-time simulations,” 2017 North American Power Symposium (NAPS), Morgantown, WV, 2017, pp. 1-6.
7. C. F. Covrig et al., A European Platform for Distributed Real Time Modelling & Simulation of Emerging Electricity Systems. European Union: JRC Science Hub, 2016.
8. E. Bompard et al., “A multi-site real-time co-simulation platform for the testing of control strategies of distributed storage and V2G in distribution networks,” in 18th European Conference on Power Electronics and Applications (EPE’16 ECCE Europe), 2016, pp. 1–9.
9. M. Stevic et al., “Virtual integration of laboratories over long distance for real-time co-simulation of power systems,” in IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, 2016, pp. 6717–6721.
10. M. Stevic, S. Vogel, A. Monti, and S. D’Arco, “Feasibility of geographically distributed real-time simulation of HVDC system interconnected with AC networks,” in PowerTech, 2015 IEEE Eindhoven, 2015, pp. 1–5.
11. M. Stevic, A. Monti and A. Benigni, “Development of a simulator-to-simulator interface for geographically distributed simulation of power systems in real time,” IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, Yokohama, 2015, pp. 005020-005025.
12. M. Stevic and S. Vogel, “Geographically Distributed Simulation: a backbone platform for studying integration of offshore wind energy,” MARINET Infrastructure Access Rep., Dec. 2014.

Use Cases

VILLAS can therefore be used as a manufacturer-independent tool for coupling various components and has already been in use for several years at approx. 29 universities and research institutions (https://villas.fein-aachen.org/docs/users). The efficiency of VILLASframework was already proven in several national, as well as international research projects.

Infrastructure Sector

• Atmospheric dispersion
• Agriculture
• Biomass
• Buildings
• Communications
• Cooling
• Ecosystems
• Electric
• District heating
• Forestry
• Health
• Hydrogen
• Individual heating
• Land use
• Liquid fuels
• Natural Gas
• Transportation
• Water

Represented Behavior

• Earth Systems
• Employment
• Built Infrastructure
• Financial
• Macro-economy
• Micro-economy
• Policy
• Social

Modeling Paradigm

• Analytics
• Data
• Discrete Simulation
• Dynamic Simulation
• Equilibrium
• Engineering/Design
• Optimization
• Visualization

Capabilities

Toolset for local and geographically distributed real-time co-simulation

Programming Language

• C – ISO/IEC 9899
• C++ (C plus plus) – ISO/IEC 14882
• C# (C sharp) – ISO/IEC 23270
• Delphi
• GAMS (General Algebraic Modeling System)
• Go
• Haskell
• Java
• JavaScript(Scripting language)
• Julia
• Kotlin
• LabVIEW
• Lua
• MATLAB
• Modelica
• Nim
• Object Pascal
• Octave
• Pascal Script
• Python
• R
• Rust
• Simulink
• Swift (Apple programming language)
• WebAssembly
• Zig

Required Dependencies

No response

What is the software tool's license?

None

Operating System Support

• Windows
• Mac OSX
• Linux
• iOS
• Android

User Interface

• Programmatic
• Command line
• Web based
• Graphical user
• Menu driven
• Form based
• Natural language

Parallel Computing Paradigm

• Multi-threaded computing
• Multi-core computing
• Distributed computing
• Cluster computing
• Massively parallel computing
• Grid computing
• Reconfigurable computing with field-programmable gate arrays (FPGA)
• General-purpose computing on graphics processing units
• Application-specific integrated circuits
• Vector processors

What is the highest temporal resolution supported by the tool?

Not Applicable

What is the typical temporal resolution supported by the tool?

None

What is the largest temporal scope supported by the tool?

Not Applicable

What is the typical temporal scope supported by the tool?

None

What is the highest spatial resolution supported by the tool?

Global

What is the typical spatial resolution supported by the tool?

Global

What is the largest spatial scope supported by the tool?

Global

What is the typical spatial scope supported by the tool?

Global

Input Data Format

NA

Input Data Description

No response

Output Data Format

NA

Output Data Description

No response

Contact Details

Steffen Vogel (post@steffenvogel.de)

Interface, Integration, and Linkage

No response