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Multi-Federate Co-Convergence with HELICS

Conference ·
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In co-simulation studies, convergence refers to the ability of different simulation tools involved to achieve a consistent and stable solution. Convergence is a critical aspect of co-simulation as it determines the accuracy of the results obtained from the simulation. Convergence in co-simulation studies depends on several factors, this includes system complexity, the accuracy of the models used, and the numerical methods employed by the simulation tools. It is essential to ensure that the coupling interfaces between the different tools are designed to allow for data exchange in a consistent and accurate manner. Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS) is an open-source co-simulation framework developed for the energy domain. This paper explores the convergence performance of a set of co-simulation use cases. We further explore the use of a co-convergence helper federate to help with co-simulation convergence. The convergence efficacy of several algorithms (both gradient-based and gradient-free) is tested against these use cases. Finally, the sensitivity of these algorithms to several factors, such as system scaling and others, is tested and detailed in this paper. Our results show that for a subset of use cases, the co-convergence helper federate is able to improve co-simulation convergence significantly.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Grid Modernization Laboratory Consortium (GMLC); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office; USDOE Office of Electricity (OE)
DOE Contract Number:
AC36-08GO28308
OSTI ID:
2332744
Report Number(s):
NREL/CP-6A40-86941; MainId:87716; UUID:e2fc1ccd-1642-43ac-83ca-eb973cf5232f; MainAdminId:72266
Resource Relation:
Conference: Presented at the 2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 19-22 February 2024, Washington, D.C.
Country of Publication:
United States
Language:
English

References (15)

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Transmission and distribution co‐simulation: a review and propositions September 2020
A literature review of building energy simulation and computational fluid dynamics co-simulation strategies and its implications on the accuracy of energy predictions June 2021
Co-Simulation: Error Estimation and Macro-Step Size Control February 2021
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Transmission-and-Distribution Dynamic Co-Simulation Framework for Distributed Energy Resource Frequency Response January 2022
Co-simulation of Circuit/Circuit type Solvers for EMC Applications Using a New Relaxation Method September 2022
Dynamic Co-Simulation Methods for Combined Transmission-Distribution System With Integration Time Step Impact on Convergence March 2019
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IFOSMONDI Co-simulation Algorithm with Jacobian-Free Methods in PETSc April 2022
Design of the HELICS high-performance transmission-distribution-communication-market co-simulation framework April 2017
Transmission–Distribution Cosimulation: Analytical Methods for Iterative Coupling June 2020
A Scalable Multi-Timescale T&D Co-Simulation Framework using HELICS February 2021
Mosaik: A framework for modular simulation of active components in Smart Grids October 2011
SciPy 1.0: fundamental algorithms for scientific computing in Python February 2020

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Related Subjects

POWER TRANSMISSION AND DISTRIBUTION
co-convergence
co-simulation
HELICS
scipy