PowerDynamics.jl -- An experimentally validated open-source package for the dynamical analysis of power grids

TL;DR

PowerDynamics.jl is an open-source Julia package designed for high-performance, time-domain stability analysis of power grids with renewable energy, supporting custom models and machine learning integration, validated through experimental testing.

Contribution

The paper introduces PowerDynamics.jl, a novel, open-source, and experimentally validated Julia package for power grid stability analysis with customizable models and machine learning compatibility.

Findings

Validated against microgrid measurements

Supports large-scale systems with high renewable share

Enables dynamical optimization and control strategy testing

Abstract

PowerDynamics.jl is a Julia package for time-domain modeling of power grids that is specifically designed for the stability analysis of systems with high shares of renewable energies. It makes use of Julia's state-of-the-art differential equation solvers and is highly performant even for systems with a large number of components. Further, it is compatible with Julia's machine learning libraries and allows for the utilization of these methods for dynamical optimization and parameter fitting. The package comes with a number of predefined models for synchronous machines, transmission lines and inverter systems. However, the strict open-source approach and a macro-based user-interface also allows for an easy implementation of custom-built models which makes it especially interesting for the design and testing of new control strategies for distributed generation units. This paper presents how the modeling concept, implemented component models and fault scenarios have been experimentally tested against measurements in the microgrid lab of TECNALIA.