Active line model identification protection based on characteristic frequency phase for dual-end weakly-fed AC system

The large-scale integration of renewable energy into the grid through flexible DC transmission systems has become an inevitable trend in power delivery. Model-based protection schemes, unaffected by power source characteristics, have been widely applied in renewable energy grid-connected systems. However, in a dual-end weakly-fed AC system, this results in significant adaptability issues with existing model-based protection schemes. To address this, this paper proposes an active line model identification protection based on characteristic frequency phase for dual-end weakly-fed AC system. First, this paper investigates the adaptability of conventional model recognition principles in a the dual-ended weakly fed AC system. Building on this, a control strategy is proposed that utilizes Modular Multilevel Converters (MMC) for the injection of characteristic frequency signals. The criteria for selecting the injected signals and their extraction methods are outlined. Subsequently, an analysis of the line model under injected characteristic frequency signals is presented, focusing on the differences in the phase characteristics of the line model at various fault locations. Finally, in the PSCAD/EMTDC electromagnetic simulation platform simulation, combined with empirical wavelet transform and Prony (EWT-Prony) algorithm to extract the characteristic frequency phase of the line model, the effectiveness of the proposed protection scheme is verified. The results demonstrate that the proposed scheme can withstand high fault impedance (300Ω) and noise interference (25 dB), confirming its robustness and reliability.

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Publication Details

Journal
Scientific Reports
Published
2025-11-21
DOI
https://doi.org/10.1038/s41598-025-24860-5
Primary Topic
HVDC Systems and Fault Protection
Type
article
Field-Weighted Citation Impact
0.00

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article

Active line model identification protection based on characteristic frequency phase for dual-end weakly-fed AC system

Xiaofang Wu, Guobing Song, Junjie Hou, Zhuofan Zhang et al.
Scientific Reports
HVDC Systems and Fault Protection
article

Active line model identification protection based on characteristic frequency phase for dual-end weakly-fed AC system

Xiaofang Wu, Guobing Song, Junjie Hou, Zhuofan Zhang, Yanfang Fan
article en

Abstract

The large-scale integration of renewable energy into the grid through flexible DC transmission systems has become an inevitable trend in power delivery. Model-based protection schemes, unaffected by power source characteristics, have been widely applied in renewable energy grid-connected systems. However, in a dual-end weakly-fed AC system, this results in significant adaptability issues with existing model-based protection schemes. To address this, this paper proposes an active line model identification protection based on characteristic frequency phase for dual-end weakly-fed AC system. First, this paper investigates the adaptability of conventional model recognition principles in a the dual-ended weakly fed AC system. Building on this, a control strategy is proposed that utilizes Modular Multilevel Converters (MMC) for the injection of characteristic frequency signals. The criteria for selecting the injected signals and their extraction methods are outlined. Subsequently, an analysis of the line model under injected characteristic frequency signals is presented, focusing on the differences in the phase characteristics of the line model at various fault locations. Finally, in the PSCAD/EMTDC electromagnetic simulation platform simulation, combined with empirical wavelet transform and Prony (EWT-Prony) algorithm to extract the characteristic frequency phase of the line model, the effectiveness of the proposed protection scheme is verified. The results demonstrate that the proposed scheme can withstand high fault impedance (300Ω) and noise interference (25 dB), confirming its robustness and reliability.

Scientific ReportsVol. 15(1)
Inner Mongolia Electric Power (China) (CN), Xi'an Jiaotong University (CN), Xinjiang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 65%
HVDC Systems and Fault Protection
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