Data-Driven Fast Frequency Control using Inverter-Based Resources

TL;DR

This paper presents a data-driven, model-free fast frequency control method for inverter-based resources that uses historical data to quickly restore system balance without explicit system models.

Contribution

It introduces a novel area-based control scheme combining low-gain estimation and data-driven control, enabling rapid frequency regulation without system model knowledge.

Findings

Effective frequency stabilization demonstrated in simulations

No explicit system model required for control implementation

Applicable to inverter-based resources in power systems

Abstract

We develop and test a data-driven and area-based fast frequency control scheme, which rapidly redispatches inverter-based resources to compensate for local power imbalances within the bulk power system. The approach requires no explicit system model information, relying only on historical measurement sequences for the computation of control actions. Our technical approach fuses developments in low-gain estimator design and data-driven control to provide a model-free and practical solution for fast frequency control. Theoretical results and extensive simulation scenarios on a three area system are provided to support the approach.