AI-Driven Stabilization in Power Grids through Controlling Line Admittances

TL;DR

This paper presents an AI-based adaptive control algorithm that stabilizes power grids by tuning admittance regulators in real time, reducing frequency deviations and system complexity, demonstrated on a UK grid.

Contribution

The introduced AAC algorithm unifies grid planning and real-time control, adaptively stabilizing power systems and identifying key regulators for intervention, enhancing reliability and reducing costs.

Findings

Significantly reduces frequency deviations in real-world tests.

Identifies critical regulators, lowering system complexity.

Rapidly stabilizes frequency and power flow under various faults.

Abstract

The global transition from traditional power plants to renewable energy sources introduces new challenges in grid stability, primarily because inverter-based technologies provide insufficient inertia. To address this, we introduce an artificial intelligence algorithm that autonomously stabilizes power grids by adaptively tuning admittance regulators in response to disturbances. This Adaptive Admittance Controller (AAC) algorithm not only stabilizes the system in real time but also identifies the best regulator locations, thereby unifying grid planning and real time control within a single framework. When tested on a real UK power grid, the AAC markedly reduces frequency deviations and rapidly restores nominal operation. In addition, the algorithm isolates a small number of key regulators and intervenes only on these, lowering both system complexity and cost. The AAC algorithm further reduces the nonlinearity effect, quickly stabilizing the frequency and power flow. This intelligent control scheme enables power grids to reliably return to stable operating conditions under a broad spectrum of fault scenarios. The proposed framework can also be used to mitigate cascading failures by adaptively controlling critical links in a variety of networked infrastructures, such as cascades of traffic congestion on road networks or fuse failures in energy-saving systems.