The U.S. Department of Energy's Office of Scientific and Technical Information

This paper describes the design rationale for the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS), a new open-source, cyber-physical-energy co-simulation framework for electric power systems. HELICS is designed to support very-large-scale (100,000+ federates) co-simulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross-platform operating system support, the integration of both event-driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step. After describing the requirements, we evaluate existing co-simulation frameworks, including High-Level Architecture (HLA) and Functional Mockup Interface (FMI), and we conclude that none provide the required features. Then we describe the design for the new, layered HELICS architecture.

This paper demonstrates a novel cosimulation architecture that integrates hardware testing using power hardware-in-the-loop (PHIL) techniques with larger-scale electric grid models using off-the-shelf non-PHIL software tools. This test bed for distributed integration enables utilities to study the impacts of emerging energy technologies on their system and manufacturers to explore the interactions of new devices with existing and emerging devices on the power system, both without the need to convert existing grid models to a new platform or to conduct in-field trials. This paper describes an implementation of this architecture for testing two residential-scale advanced solar inverters at separate points of common coupling (PCCs). The same hardware setup is tested with two different distribution feeders (IEEE 123 and 8500 node test systems) modeled using GridLAB-D. In addition to simplifying testing with multiple feeders, the architecture demonstrates additional flexibility with hardware testing in one location linked via the Internet to software modeling in a remote location. In testing, the inverter current, real and reactive power, and PCC voltage are well captured by the cosimulation platform. Testing of the inverter advanced control features is currently somewhat limited by the software model time step (1 s) and tested communication latency (24 ms). These limitations could be overcome using faster modeling and communication within the same cosimulation architecture.

Under the increasing penetration of distributed energy resources and new smart network technologies, distribution utilities face new challenges and opportunities to ensure reliable operations, manage service quality, and reduce operational and investment costs. Simultaneously, the research community is developing algorithms for advanced controls and distribution automation that can help to address some of these challenges. However, there is a shortage of realistic test systems that are publically available for development, testing, and evaluation of such new algorithms. Concerns around revealing critical infrastructure details and customer privacy have severely limited the number of actual networks published and that are available for testing. In recent decades, several distribution test feeders and US-featured representative networks have been published, but the scale, complexity, and control data vary widely. This paper presents a first-of-a-kind structured literature review of published distribution test networks with a special emphasis on classifying their main characteristics and identifying the types of studies for which they have been used. This both aids researchers in choosing suitable test networks for their needs and highlights the opportunities and directions for further test system development. In particular, we highlight the need for building large-scale synthetic networks to overcome the identified drawbacks of current distribution test feeders.

As both the generation resources and load types have changed and grown over the past few decades, there is a growing need for analysis that spans traditional simulation boundaries; for example, evaluating the impact of distribution-level assets (e.g. rooftop solar, EV chargers) on bulk-power system operation. Co-simulation is a technique that allows simulators to trade information during run-time, effectively creating larger and more complex models. HELICS is a co-simulation platform that has been developed to enable these kinds of power system analysis, incorporating tools from a variety of domains including the electrical power grid, natural gas, transportation, and communications. This paper summarizes the technical design of HELICS, describes how tools can be integrated into the platform, and reviews a number of analyses that have been performed using HELICS. A short video summary of this paper can be found at https://youtu.be/BIUiR_K87Wc.