# A novel Hankel norm approximation-based AGC for a hydro-dominated power system

## TL;DR

This paper introduces a new method for simplifying complex power system models to improve automatic generation control in hydro-dominated systems.

## Contribution

The novel use of Hankel norm approximation for model order reduction in hydro-dominated power system AGC is presented.

## Key findings

- Reduced-order models preserve essential dynamics while lowering computational effort.
- Eigenvalue analysis confirms stability margins of the reduced models.
- Comparative results show HNA outperforms truncation-based reduction.

## Abstract

Analyzing power system disturbances for automatic generation control (AGC) requires solving a large set of differential equations, which remains computationally demanding even in linearized form and hence limits the practical implementation of most control strategies. In addition, the presence of time constants and delays further complicates the modeling by influencing the response of generators, governors, and control mechanisms especially for hydro dominated power systems. To address these challenges, Model Order Reduction (MOR) techniques play an important role in solving these issues for higher order and complex systems. This paper applies the Hankel norm approximation (HNA) method to develop reduced-order models for AGC in a hydro-dominated power system. An eleventh-order model is reduced to seventh, eighth and ninth-order representations. Stability margins of these reduce order models are evaluated through eigenvalue analysis, and the dynamic responses of the reduced order models are compared against the original model. Results demonstrate that the reduced order models preserve the essential dynamics while substantially lowering computational effort in AGC. To further assess the effectiveness of HNA, a Truncation-based reduction approach is also applied, and comparative results are offered to show the benefits of the proposed work.

The online version contains supplementary material available at 10.1038/s41598-026-35235-9.