Multi-Federate Co-Convergence with HELICS

Aadil Latif, Bryan Palmintier, Farzam Nejabatkhah, Patrick Jacques

Research output: Contribution to conferencePaper


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.
Original languageAmerican English
Number of pages5
StatePublished - 2024
Event2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) - Washington, D.C.
Duration: 19 Feb 202422 Feb 2024


Conference2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
CityWashington, D.C.

NREL Publication Number

  • NREL/CP-6A40-86941


  • co-convergence
  • co-simulation
  • scipy


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