Small Signal Stability Analysis of Grid-Connected Converter Models

With the continuous increase in the installed capacity of new energy sources in advanced power systems, the capability for voltage control in grids becomes increasingly weak. Grid-connected renewable energy converters, due to their inherent voltage support capabilities, are particularly favored in weak grid scenarios. However, current research on the characteristics of such grid-connected renewable energy converters is still inconclusive, and there is an urgent need for an analysis of their stability properties. This paper addresses the issue of stability in single-machine grid-connected systems of these converters by deriving a small signal model for a grid-connected renewable energy converter in a single-machine grid connection system. Through eigenvalue analysis of the model's characteristics, the study further validates the correctness of this analysis by constructing a model in Matlab/Simulink and performing Fast Fourier Transform (FFT) analysis on the active power output of the model. By combining the examination of system eigenvalue root loci with analyses of the active power output from simulation models, the paper investigates the impact of factors such as line connection impedance, parameters of active power loop control, and parameters of reactive power loop control on the low-frequency oscillation modes of the system. This comprehensive approach not only deepens our understanding of the stability characteristics of grid-connected renewable energy converters but also provides a practical methodology for assessing and optimizing the control strategies in the context of an increasingly renewables-dominated grid infrastructure.

Authors

Institutions

Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/neessc62857.2024.10733520
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Small Signal Stability Analysis of Grid-Connected Converter Models

Fusuo Liu, Ling Zhu, Zengyao Li, Chong Ren et al.
Power Systems and Renewable Energy
article

Small Signal Stability Analysis of Grid-Connected Converter Models

Fusuo Liu, Ling Zhu, Zengyao Li, Chong Ren, Lin Cheng
article en

Abstract

With the continuous increase in the installed capacity of new energy sources in advanced power systems, the capability for voltage control in grids becomes increasingly weak. Grid-connected renewable energy converters, due to their inherent voltage support capabilities, are particularly favored in weak grid scenarios. However, current research on the characteristics of such grid-connected renewable energy converters is still inconclusive, and there is an urgent need for an analysis of their stability properties. This paper addresses the issue of stability in single-machine grid-connected systems of these converters by deriving a small signal model for a grid-connected renewable energy converter in a single-machine grid connection system. Through eigenvalue analysis of the model's characteristics, the study further validates the correctness of this analysis by constructing a model in Matlab/Simulink and performing Fast Fourier Transform (FFT) analysis on the active power output of the model. By combining the examination of system eigenvalue root loci with analyses of the active power output from simulation models, the paper investigates the impact of factors such as line connection impedance, parameters of active power loop control, and parameters of reactive power loop control on the low-frequency oscillation modes of the system. This comprehensive approach not only deepens our understanding of the stability characteristics of grid-connected renewable energy converters but also provides a practical methodology for assessing and optimizing the control strategies in the context of an increasingly renewables-dominated grid infrastructure.

NARI Group (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 82%
Power Systems and Renewable Energy
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.