Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm

Jie Chen; Muyang Liu; Junru Chen; Kamran Zeb; Hassaan Khaliq Qureshi

doi:10.1109/EPEE59859.2023.10351947

Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm

Jie Chen, Muyang Liu^*, Junru Chen, Kamran Zeb, Hassaan Khaliq Qureshi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Virtual synchronous generator (VSG) control simulates the external characteristics of synchronous generators (SG) so that can provide inertia and frequency support to the grid in the similar behaviors of SGs. The classic VSG control use the fixed control parameters, which, however does not take advantage of the potential of fast-response feature of the power electronics. Basing on the stability features of the power system with high penetrations of inverter-based sources, the paper proposes an adaptive VSG control strategy with the virtual inertia and damping coefficients adaptively varied according to dynamic frequency of the power system. The paper analyses the effect of the proposed adaptive VSG control through the root-loci method and the small-signal stability analysis. The coefficients of the adaptive control can be optimized through the particle swarm algorithm to fulfill the best potential of the control on improving the frequency stability of the power system. A micro-grid model is served to validate the proposed adaptive VSG control and the coefficient optimization method.

Original language	English
Title of host publication	2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1399-1404
Number of pages	6
ISBN (Electronic)	9798350318180
DOIs	https://doi.org/10.1109/EPEE59859.2023.10351947
State	Published - 2023
Externally published	Yes
Event	3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023 - Hybrid, Wuhan, China Duration: 15 Sep 2023 → 17 Sep 2023

Publication series

Name	2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

Conference

Conference	3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023
Country/Territory	China
City	Hybrid, Wuhan
Period	15/09/23 → 17/09/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Adaptive Control
Particle Swarm Algorithm
Virtual Synchronous Machine

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Control and Optimization

Access to Document

10.1109/EPEE59859.2023.10351947

Cite this

Chen, J., Liu, M., Chen, J., Zeb, K., & Qureshi, H. K. (2023). Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm. In 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023 (pp. 1399-1404). (2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EPEE59859.2023.10351947

Chen, Jie ; Liu, Muyang ; Chen, Junru et al. / Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm. 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 1399-1404 (2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023).

@inproceedings{89bf741b04e944bf8536a771d9be05d2,

title = "Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm",

abstract = "Virtual synchronous generator (VSG) control simulates the external characteristics of synchronous generators (SG) so that can provide inertia and frequency support to the grid in the similar behaviors of SGs. The classic VSG control use the fixed control parameters, which, however does not take advantage of the potential of fast-response feature of the power electronics. Basing on the stability features of the power system with high penetrations of inverter-based sources, the paper proposes an adaptive VSG control strategy with the virtual inertia and damping coefficients adaptively varied according to dynamic frequency of the power system. The paper analyses the effect of the proposed adaptive VSG control through the root-loci method and the small-signal stability analysis. The coefficients of the adaptive control can be optimized through the particle swarm algorithm to fulfill the best potential of the control on improving the frequency stability of the power system. A micro-grid model is served to validate the proposed adaptive VSG control and the coefficient optimization method.",

keywords = "Adaptive Control, Particle Swarm Algorithm, Virtual Synchronous Machine",

author = "Jie Chen and Muyang Liu and Junru Chen and Kamran Zeb and Qureshi, {Hassaan Khaliq}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023 ; Conference date: 15-09-2023 Through 17-09-2023",

year = "2023",

doi = "10.1109/EPEE59859.2023.10351947",

language = "English",

series = "2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1399--1404",

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Chen, J, Liu, M, Chen, J, Zeb, K & Qureshi, HK 2023, Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm. in 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023. 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023, Institute of Electrical and Electronics Engineers Inc., pp. 1399-1404, 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023, Hybrid, Wuhan, China, 15/09/23. https://doi.org/10.1109/EPEE59859.2023.10351947

Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm. / Chen, Jie; Liu, Muyang; Chen, Junru et al.
2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 1399-1404 (2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm

AU - Chen, Jie

AU - Liu, Muyang

AU - Chen, Junru

AU - Zeb, Kamran

AU - Qureshi, Hassaan Khaliq

PY - 2023

Y1 - 2023

N2 - Virtual synchronous generator (VSG) control simulates the external characteristics of synchronous generators (SG) so that can provide inertia and frequency support to the grid in the similar behaviors of SGs. The classic VSG control use the fixed control parameters, which, however does not take advantage of the potential of fast-response feature of the power electronics. Basing on the stability features of the power system with high penetrations of inverter-based sources, the paper proposes an adaptive VSG control strategy with the virtual inertia and damping coefficients adaptively varied according to dynamic frequency of the power system. The paper analyses the effect of the proposed adaptive VSG control through the root-loci method and the small-signal stability analysis. The coefficients of the adaptive control can be optimized through the particle swarm algorithm to fulfill the best potential of the control on improving the frequency stability of the power system. A micro-grid model is served to validate the proposed adaptive VSG control and the coefficient optimization method.

AB - Virtual synchronous generator (VSG) control simulates the external characteristics of synchronous generators (SG) so that can provide inertia and frequency support to the grid in the similar behaviors of SGs. The classic VSG control use the fixed control parameters, which, however does not take advantage of the potential of fast-response feature of the power electronics. Basing on the stability features of the power system with high penetrations of inverter-based sources, the paper proposes an adaptive VSG control strategy with the virtual inertia and damping coefficients adaptively varied according to dynamic frequency of the power system. The paper analyses the effect of the proposed adaptive VSG control through the root-loci method and the small-signal stability analysis. The coefficients of the adaptive control can be optimized through the particle swarm algorithm to fulfill the best potential of the control on improving the frequency stability of the power system. A micro-grid model is served to validate the proposed adaptive VSG control and the coefficient optimization method.

KW - Adaptive Control

KW - Particle Swarm Algorithm

KW - Virtual Synchronous Machine

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DO - 10.1109/EPEE59859.2023.10351947

M3 - Conference contribution

AN - SCOPUS:85182567456

T3 - 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

SP - 1399

EP - 1404

BT - 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

Y2 - 15 September 2023 through 17 September 2023

ER -

Chen J, Liu M, Chen J, Zeb K, Qureshi HK. Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm. In 2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 1399-1404. (2023 3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023). doi: 10.1109/EPEE59859.2023.10351947

Adaptive VSG Control with Coefficient Optimization via Improved Particle Swarm Algorithm

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this