Finding Most Influential Distributed Generators for Microgrids Control with Switching Communication Networks

This paper focuses on identifying the most influential distributed generators (DGs) to improve the control performance of islanded microgrids with switching communication networks. Based on the secondary control scheme, frequency regulation and active power sharing are achieved in microgrids by pinning only a fraction of DGs. To improve the dynamic response of microgrids under limited control resources, a method is proposed to identify the most influential DG set that guarantees the fastest synchronization speed. By analyzing the impacts of the switching frequency of communication networks, an effective threshold is calculated to ensure performance. Furthermore, the proposed results are tested on a modified IEEE 34-bus system to evaluate the performance.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10905461
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00

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article

Finding Most Influential Distributed Generators for Microgrids Control with Switching Communication Networks

Mahdi Jalili, Guangrui Zhang, Xinghuo Yu, Zhaohui Liu et al.
Smart Grid Security and Resilience
article

Finding Most Influential Distributed Generators for Microgrids Control with Switching Communication Networks

Mahdi Jalili, Guangrui Zhang, Xinghuo Yu, Zhaohui Liu, Zhiyi Chen
article en

Abstract

This paper focuses on identifying the most influential distributed generators (DGs) to improve the control performance of islanded microgrids with switching communication networks. Based on the secondary control scheme, frequency regulation and active power sharing are achieved in microgrids by pinning only a fraction of DGs. To improve the dynamic response of microgrids under limited control resources, a method is proposed to identify the most influential DG set that guarantees the fastest synchronization speed. By analyzing the impacts of the switching frequency of communication networks, an effective threshold is calculated to ensure performance. Furthermore, the proposed results are tested on a modified IEEE 34-bus system to evaluate the performance.

RMIT University (AU)
Australian Research Council
Affordable and clean energy
Openalex Percentile: Top 65%
Smart Grid Security and Resilience
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