An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response

Jinxin Ouyang; Xinyu Pan; Junjun Ye; Chao Xiao; Yanbo Diao; Qingwu Zhang

doi:10.1186/s41601-023-00323-9

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An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response

Original Research | 更新时间：2026-09-30

- An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response
- An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response
- 现代电力系统保护与控制（英文） 2023年8卷第3期页码：1-11
- 作者机构：
  
  1. State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University,Chongqing,China
  2. Electric Power Research Institute of State Grid Henan Electric Power Company, Zhenazhou,China
  3. Chongqing City Management College,Chongqing,China
  4. NR Electric Co., Ltd,Nanjing,China
- 作者简介：
- 基金信息：
- DOI：10.1186/s41601-023-00323-9
  中图分类号：
- 纸质出版：2023-07-01
- 稿件说明：
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Jinxin Ouyang, Xinyu Pan, Junjun Ye, 等. An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response[J]. 现代电力系统保护与控制（英文）, 2023,8(3):1-11.

Jinxin Ouyang, Xinyu Pan, Junjun Ye, et al. An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response[J]. Protection and Control of Modern Power Systems, 2023, 8(3): 1-11.
Jinxin Ouyang, Xinyu Pan, Junjun Ye, 等. An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response[J]. 现代电力系统保护与控制（英文）, 2023,8(3):1-11. DOI： 10.1186/s41601-023-00323-9.

Jinxin Ouyang, Xinyu Pan, Junjun Ye, et al. An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response[J]. Protection and Control of Modern Power Systems, 2023, 8(3): 1-11. DOI： 10.1186/s41601-023-00323-9.

摘要

Subsequent commutation failure (SCF) can be easily generated during the first commutation failure (CF) recovery process in a line-commutated converter-based high voltage direct-current system. SCF poses a significant threat to the safe and stable operation of power systems

and accurate prediction of CF is thus important. However

SCF is affected by the operating characteristics of the main circuit and the coupling effects of sequential control response in the inverter station. These are difficult to predict accurately. In this paper

a new SCF prediction method considering the control response is proposed based on the physical principle of SCF. The time sequence and switching conditions of the controllers at different stages of the first CF recovery process are described

and the corresponding equations of commutation voltage affected by different controllers are derived. The calculation method of the SCF threshold voltage is proposed

and the prediction method is established. Simulations show that the proposed method can predict SCF accurately and provide useful tools to suppress SCF.

Abstract

Subsequent commutation failure (SCF) can be easily generated during the frst commutation failure (CF) recovery process in a line-commutated converter-based high voltage direct-current system. SCF poses a signifcant threat to the safe and stable operation of power systems

and accurate prediction of CF is thus important. However

SCF is afected by the operating characteristics of the main circuit and the coupling efects of sequential control response in the inverter station. These are difcult to predict accurately. In this paper

a new SCF prediction method considering the control response is proposed based on the physical principle of SCF. The time sequence and switching conditions of the controllers at diferent stages of the frst CF recovery process are described

and the corresponding equations of commutation voltage afected by diferent controllers are derived. The calculation method of the SCF threshold voltage is proposed

and the prediction method is established. Simulations show that the proposed method can predict SCF accurately and provide useful tools to suppress SCF

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