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author:

Tang, Junyi (Tang, Junyi.) [1] | Gao, Wei (Gao, Wei.) [2] (Scholars:高伟)

Indexed by:

EI Scopus

Abstract:

This paper presents a novel approach that simultaneously enables photovoltaic (PV) inversion and flexible arc suppression during single-phase grounding faults. Inverters compensate for ground currents through an arc-elimination function, while outputting a PV direct current (DC) power supply. This method effectively reduces the residual grounding current. To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models, an adaptive fuzzy neural network imitating a sliding mode controller was designed. An online adaptive adjustment law for network parameters was developed, based on the Lyapunov stability theorem, to improve the robustness of the inverter to fault and connection locations. Furthermore, a new arc-suppression control exit strategy is proposed to allow a zero- sequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time. Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults. Compared to other methods, the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations. © 2024 Global Energy Interconnection Group Co. Ltd.

Keyword:

Adaptive control systems Fuzzy inference

Community:

  • [ 1 ] [Tang, Junyi]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Gao, Wei]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China

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Source :

Global Energy Interconnection

ISSN: 2096-5117

Year: 2024

Issue: 4

Volume: 7

Page: 513-527

1 . 9 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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