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SEAS Communication Engine: An Extensible, Flexible Wrapper for Cosimulation Agents

Conference ·
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When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.
Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
AC36-08GO28308; AC36-08GO28308
OSTI ID:
2332743
Report Number(s):
NREL/CP-2C00-87037; MainId:87812; UUID:fec4efbc-0862-4cfa-b360-0ee90d8ccb90; MainAdminId:72265
Country of Publication:
United States
Language:
English

References (7)

The National Solar Radiation Data Base (NSRDB) journal June 2018
GridLAB-D: An Agent-Based Simulation Framework for Smart Grids journal January 2014
A federated simulation toolkit for electric power grid and communication network co-simulation conference April 2015
Open-source software projects for advancing the power systems analysis conference April 2022
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming journal April 2005
Development of HELICS-based High-Performance Cyber-Physical Co-simulation Framework for Distributed Energy Resources Applications conference November 2020
Design of the HELICS high-performance transmission-distribution-communication-market co-simulation framework conference April 2017

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Related Subjects

ESI
HELICS
HPC
Julia
MATHEMATICS AND COMPUTING
POWER TRANSMISSION AND DISTRIBUTION
Python
SEAS
hybrid energy systems