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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-01-16
DOI
https://doi.org/10.1038/s41598-026-35235-9
Primary Topic
Frequency Control in Power Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

S. K. Naqvi, Gaurav Sharma, Ibraheem, Sachin Sharma et al.
Scientific Reports
Frequency Control in Power Systems
article

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

S. K. Naqvi, Gaurav Sharma, Ibraheem, Sachin Sharma, Rajesh Kumar
article en

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.

Scientific ReportsVol. 16(1)
Manipal Academy of Higher Education (IN), University of Johannesburg (ZA), Netaji Subhas University of Technology (IN), Jamia Millia Islamia (IN), Malaviya National Institute of Technology Jaipur (IN)
Affordable and clean energy
Openalex Percentile: Top 86%
Frequency Control in Power Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.