bpalmintier
commented
1 year ago Updates/Additions for HELICS:
Name: HELICS, the Hierarchical Engine for Large-scale Infrastructure Co-Simulation
Focus Topic
Co-simulation of multi-energy systems
Primary Purpose
Flexible and scalable open-source co-simulation framework is designed to integrate simulators designed for separate energy domains to simulate regional and interconnection-scale power system behaviors at unprecedented levels of detail and speed. Co-simulation enables multiple existing simulators to act like one large simulation by coordinating time and exchanging data at every timestep.
Description
Flexible and scalable open-source co-simulation framework is designed to integrate simulators designed for separate energy system domains--such as transmission, distribution, communications, natural gas, buildings, transportation, natural gas, water, control schemes, etc. Together these simulations can co-simulate a wide range of grid-related applications ranging in spatial scale from a single controller managing an electric vehicle charging station up to regional and interconnection-scale power system behaviors at unprecedented levels of detail and speed. For example, HELICS can link multi-faceted large-scale (20,000+ node) bulk power simulations (markets, powerflow, dynamics) with thousands of distribution simulations (each with thousands of nodes), in combination with hundreds of thousands of controllers, communication simulation with hundreds of thousands of communication points, and more.
This comprehensive multi-energy simulation tool is fundamental for investment decision-making by industry. It's also important to help quantify the impact of the ever-increasing high penetration variable generation, DERs, control schemes, and other changes on the power grid reliability and resiliency; and to simulate possible solutions at scale in silico.
Documentation
https://docs.helics.org/en/latest/index.html
Source
https://github.com/GMLC-TDC/HELICS
Year
2018 (First release)
Institution
NREL, PNNL, LLNL
Funding Source
DOE GMLC
Publications
Lots, please add the following, plus some extras coming from PNNL and other locations and then update the sum
_(Additional) Publication List
Note: the current list is mostly presentations, not sure if you would want to include all of these or are focussed more on papers.
- (should list first, current standard HELICS reference, although we are working on an updated one expected mid-2023) Palmintier, Bryan, Dheepak Krishnamurthy, Philip Top, Steve Smith, Jeff Daily, and Jason Fuller. 2017. “Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework.” In Proc. of the 2017 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems. Pittsburgh, PA. https://doi.org/10.1109/MSCPES.2017.8064542.
- Panossian, Nadia, Tarek Elgindy, Bryan Palmintier, and Diana Wallison. 2021. “Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking.” In 2021 IEEE Texas Power and Energy Conference (TPEC), 1–5. https://doi.org/10.1109/TPEC51183.2021.9384935.
- Panossian, Nadia V., Haitam Laarabi, Keith Moffat, Heather Chang, Bryan Palmintier, Andrew Meintz, Timothy E. Lipman, and Rashid A. Waraich. 2023. “Architecture for Co-Simulation of Transportation and Distribution Systems with Electric Vehicle Charging at Scale in the San Francisco Bay Area.” Energies 16 (5): 2189. https://doi.org/10.3390/en16052189.
- Wang, Jing, Jeff Simpson, Rui Yang, Bryan Palmintier, Soumya Tiwari, and Yingchen Zhang. 2021. “Hardware-in-the-Loop Evaluation of an Advanced Distributed Energy Resource Management Algorithm.” In 2021 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT), 1–5. https://doi.org/10.1109/ISGT49243.2021.9372182.
- Wang, Jing, Jeff Simpson, Rui Yang, Bryan Palmintier, Soumya Tiwari, and Yingchen Zhang. 2021. “Performance Evaluation of an Advanced Distributed Energy Resource Management Algorithm.” In 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm).
- Barbierato, Luca, Pietro Rando Mazzarino, Marco Montarolo, Alberto Macii, Edoardo Patti, and Lorenzo Bottaccioli. 2022. “A Comparison Study of Co-Simulation Frameworks for Multi-Energy Systems: The Scalability Problem.” Energy Informatics 5 (4): 53. https://doi.org/10.1186/s42162-022-00231-6.
- Sergi, Brian, and Kwabena Pambour. 2022. “An Evaluation of Co-Simulation for Modeling Coupled Natural Gas and Electricity Networks.” Energies 15 (14): 5277. https://doi.org/10.3390/en15145277.
If you do want more Presentations:
- Huang, Henry, Liang Min, Jason Fuller, Bryan Palmintier, Philip Top, and Shrirang Abhaynkar. 2018. “GMLC 1.4.15: Integrated Transmission, Distribution, and Communication (TDC) System Model: HELICS.” Presented at the Workshop on Co-Simulation Platforms for the Power Grid, Berkeley, CA, May 21.
- Palmintier, Bryan. 2019. “Integrated Transmission-Distribution-Communication/Control Modeling with HELICS.” Presented at the InnovationXLab: Grid Modernization Technology Showcase, Seattle, WA, January 25.
- Palmintier, Bryan. 2019. “HELICS for Integrated Transmission, Distribution, Communication, & Control (TDC+C) Modeling.” Presented at the SETO Challenges for Distribution Planning, Operational and Real-time Planning Analytics Workshop, Washington, DC, May 17.
Use Cases
I'll point @lmramirea1 to some slides from various workshops showcasing past use cases
What Infrastructure Sector does this software tool model?
Note: only included relevant ones
Buildings Communications Electric District heating Hydrogen Liquid fuels Natural Gas Transportation Water
Represented Behavior
What is the represented behavior that the tool is modeling?
Built Infrastructure
Modeling Paradigm
What modeling Paradigm does this software tool follow?
Discrete Simulation Dynamic Simulation (assumed to focus on msec grid dynamics, term might be confusing in entry form) Engineering/Design Time series Simulation (should be added to the list)
Capabilities
In addition to the summary in original issue entry
- Scalable: 2-1,000,000+ federates
- Modular: mix and match existing tools.
- Differentiates physical values exchange from communication/control messages
- Supports co-iteration to converge physical values between federates before advancing time (aka tight coupling)
- Built-in support for communication message "Filters" to add delays, drop packets, change data, reroute to different simulators, etc.
- Built-in unit management
- Tools for managing large runs
- Existing interfaces for: PSS/E, GridDyn, PowerWorld, SIIP, MATPOWER, CYME, PyDSS, OpenDSS, GridLAB-D, NS-3, SAInt, NG-Fast, NG-Transient, BEAM, Polaris, Opal-RT, and others
- Supports multiple simulation types including: Time series, dynamics, discrete event
- Interfaces for FMI
Programming Language
C – ISO/IEC 9899 (written in) C++ (C plus plus) – ISO/IEC 14882 C# (C sharp) – ISO/IEC 23270 Java Julia MATLAB Octave Python
Required Dependencies
Only other open-source libraries
What is the software tool's license?
BSD-3
Operating System Support
Windows Mac OSX Linux
User Interface
What user interfaces are supported by the software tool?
Programmatic Command line Web based
Parallel Computing Paradigm
Multi-threaded computing Multi-core computing Distributed computing Cluster computing Massively parallel computing
What is the highest temporal resolution supported by the tool?
Instant
What is the typical temporal resolution supported by the tool?
1 ms to 1 hr depending on application and which other tools are connected
What is the largest temporal scope supported by the tool?
Arbitrary, 1 year common max
What is the typical temporal scope supported by the tool?
1-hour (e.g. dynamic response to grid outage) to 1-year (e.g. integrated T&D production cost) depending on application and which other tools are connected
What is the highest spatial resolution supported by the tool?
Component
What is the typical spatial resolution supported by the tool?
Varies by use case, component common,
What is the largest spatial scope supported by the tool?
Grid intercection (e.g. Western US, Europe, etc.)
What is the typical spatial scope supported by the tool?
Varies by application, data, and which other tools are connected
Input Data Format
Varies by tools integrated.
Input Data Description
Interconnected tools generally use their own native input formats. HELICS provides built-in "player" file support (CSV) to substitute for missing simulators during development or to provide known inputs to subsets of a federation
Output Data Format
Varies by tools integrated
Output Data Description
Interconnected tools generally use their own native output formats. In addition, HELICS provides built-in "recorder" file support (CSV) to capture data exchanged as desired
Interface, Integration, and Linkage
See list above
lmramirea1
Name
HELICS
Screenshots
Focus Topic
Co-simulation of multi-energy systems
Primary Purpose
Flexible and scalable open-source co-simulation framework is designed to integrate simulators designed for separate energy domains to simulate regional and interconnection-scale power system behaviors at unprecedented levels of detail and speed. Co-simulation enables multiple existing simulators to act like one large simulation by coordinating time and exchanging data at every timestep.
Description
Flexible and scalable open-source co-simulation framework is designed to integrate simulators designed for separate energy system domains--such as transmission, distribution, communications, natural gas, buildings, transportation, natural gas, water, control schemes, etc. Together these simulations can co-simulate a wide range of grid-related applications ranging in spatial scale from a single controller managing an electric vehicle charging station up to regional and interconnection-scale power system behaviors at unprecedented levels of detail and speed. For example, HELICS can link multi-faceted large-scale (20,000+ node) bulk power simulations (markets, powerflow, dynamics) with thousands of distribution simulations (each with thousands of nodes), in combination with hundreds of thousands of controllers, communication simulation with hundreds of thousands of communication points, and more.
This comprehensive multi-energy simulation tool is fundamental for investment decision-making by industry. It's also important to help quantify the impact of the ever-increasing high penetration variable generation, DERs, control schemes, and other changes on the power grid reliability and resiliency; and to simulate possible solutions at scale in silico.
Mathematical Description
No response
Website
https://helics.org/
Documentation
https://docs.helics.org/en/latest/user-guide/index.html
Source
https://github.com/GMLC-TDC/HELICS
Year
2018 (First release)
Institution
NREL, PNNL, LLNL
Funding Source
DOE GMLC
Publications
More than 20
Publication List
Use Cases
Infrastructure Sector
Represented Behavior
Modeling Paradigm
Capabilities
-Co-simulation platform that has been designed to allow integration of these simulators across a variety of computation platforms and languages. -Scalable: 2-1,000,000+ federates -Modular: mix and match existing tools. -Differentiates physical values exchange from communication/control messages -Supports co-iteration to converge physical values between federates before advancing time (aka tight coupling) -Built-in support for communication message "Filters" to add delays, drop packets, change data, reroute to different simulators, etc. -Built-in unit management -Tools for managing large runs -Existing interfaces for: PSS/E, GridDyn, PowerWorld, SIIP, MATPOWER, CYME, PyDSS, OpenDSS, GridLAB-D, NS-3, SAInt, NG-Fast, NG-Transient, BEAM, Polaris, Opal-RT, and others -Supports multiple simulation types including: Time series, dynamics, discrete event -Interfaces for FMI
Programming Language
Required Dependencies
Only other open-source libraries
What is the software tool's license?
BSD-3
Operating System Support
User Interface
Parallel Computing Paradigm
What is the highest temporal resolution supported by the tool?
Instant
What is the typical temporal resolution supported by the tool?
1 ms to 1 hr depending on application and which other tools are connected
What is the largest temporal scope supported by the tool?
Arbitrary, 1 year common max
What is the typical temporal scope supported by the tool?
1-hour (e.g. dynamic response to grid outage) to 1-year (e.g. integrated T&D production cost) depending on application and which other tools are connectedNone
What is the highest spatial resolution supported by the tool?
Component
What is the typical spatial resolution supported by the tool?
Varies by use case, component common,
What is the largest spatial scope supported by the tool?
Grid intersection (e.g. Western US, Europe, etc.)
What is the typical spatial scope supported by the tool?
Varies by application, data, and which other tools are connected
Input Data Format
Varies by tools integrated.
Input Data Description
Interconnected tools generally use their own native input formats. HELICS provides built-in "player" file support (CSV) to substitute for missing simulators during development or to provide known inputs to subsets of a federation
Output Data Format
Varies by tools integrated
Output Data Description
Interconnected tools generally use their own native output formats. In addition, HELICS provides built-in "recorder" file support (CSV) to capture data exchanged as desired
Contact Details
helicsteam@helics.org
Interface, Integration, and Linkage
No response