Model-based Design Tool for Cyber-physical Power Systems using SystemC-AMS

TL;DR

This paper introduces a model-based design tool using SystemC-AMS for simulating cyber-physical power systems and microgrids, enabling accurate electromagnetic transient analysis and faster simulation compared to Simulink.

Contribution

The paper presents a novel application of SystemC-AMS for modeling and simulating cyber-physical power systems, including microgrids, with improved speed and accuracy.

Findings

SystemC-AMS accurately models electromagnetic transients.

The tool enables faster simulations than Simulink.

It supports informed microgrid component selection.

Abstract

Cyber-physical power systems, such as grids, integrate computational and communication components with physical systems to introduce novel functions and improve resilience and fault tolerance. These systems employ computational components and real-time controllers to meet power demands. Microgrids, comprising interconnected components, energy resources within defined electrical boundaries, computational elements, and controllers, offer a solution for integrating renewable energy sources and ensuring resilience in electricity demand. Simulating these cyber-physical systems (CPS) is vital for grid design, as it facilitates the modeling and control of both continuous physical processes and discrete-time power converters and controllers. This paper presents a model-based design tool for simulating cyber-physical power systems, including microgrids, using SystemC-AMS. The adoption of SystemC-AMS enables physical modeling with both native components from the SystemC-AMS library and user-defined computational elements. We observe that SystemC-AMS can accurately produce the electromagnetic transient responses essential for analyzing grid stability. Additionally, we demonstrate the effectiveness of SystemC-AMS through use cases that simulate grid-following inverters. Comparing the SystemC-AMS implementation to one in Simulink reveals that SystemC-AMS offers a more rapid simulation. A design tool like this could support microgrid designers in making informed decisions about the selection of microgrid components prior to installation and deployment.