A Scalable Nyquist Stability Criterion with Application to Power System Small-Signal Stability
Joakim Bj\"ork, Karl Henrik Johansson

TL;DR
This paper introduces a decentralized, scalable Nyquist stability criterion for power systems that guarantees stability with only local information, accommodating heterogeneous subsystems including renewable energy sources.
Contribution
It develops a generalized Nyquist-based stability criterion applicable to diverse agents, enabling stability analysis of large, complex power networks with minimal information.
Findings
Validates the method on a nonlinear power system model
Ensures stability guarantees for systems with renewable energy integration
Applicable to systems with delays, unstable dynamics, and nonminimum phase actuators
Abstract
A decentralized stability criterion is derived for a power system with heterogeneous subsystems. A condition for frequency stability and stability of interarea modes is derived using the generalized Nyquist criterion. The resulting scalable Nyquist stability criterion requires only locally available information and gives a priori stability guarantees for connecting new subsystems to an arbitrarily large network. The method can be applied to a general set of agents. For instance, agents with time-delays, nonminimum phase actuators or even unstable dynamics. The scalable Nyquist criterion makes no distinction between nodes with or without synchronous inertia, making it easy to include converter-interfaced renewable energy in the analysis. The method is validated on a detailed nonlinear power system model with frequency droop provided by hydro governors assisted by wind power.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsPower System Optimization and Stability · Power Systems and Renewable Energy · Microgrid Control and Optimization
