Control of Power Quality and System Stability

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 1434

Special Issue Editors


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Guest Editor
School of Electrical Engineering, Sichuan University, Chengdu 610065, China
Interests: stability analysis and control of power electronic-based power systems

E-Mail Website
Guest Editor
School of Electrical Engineering, Sichuan University, Chengdu 610065, China
Interests: dispatch, operation, control of power systems; information techniques of power systems

E-Mail Website
Guest Editor
School of Electrical Engineering, Sichuan University, Chengdu 610065, China
Interests: energy storage technology; especially battery voltage equalizer; hybrid energy storage technology

Special Issue Information

Dear Colleagues,

We are inviting researchers to make submissions to this Special Issue of Electronics on the subject area of “Control of Power Quality and System Stability”.

With the integration of many new energy sources into power systems, the number of power electronic equipment in the power system is quickly increasing. However, due to the complex control and nonlinear switching processes of power electronic equipment, many new power quality and stability issues have emerged, such as voltage/current distortions, harmonic oscillations under a wide frequency range, and so on. These issues may cause equipment damage and protection tripping, further deteriorating the safety and reliability of power systems. Therefore, this Special Issue focuses on the studies of advanced control methods at the equipment and system levels to improve the power quality and stability of high-proportion power electronic equipment power systems. The topics of interest include, but are not limited to, the following:

  1. Disturbance source localization and oscillation type identification;
  2. Modeling and stability analysis of high-proportion power electronic equipment power systems;
  3. New designs for power quality compensators based on wideband semiconductors;
  4. Customized design of compensator controllers, including damping, inertia, harmonic and reactive power compensation, etc.;
  5. Grid-forming control;
  6. Optimization control, dispatch, and planning of all kinds of compensators;
  7. Advanced artificial intelligence (AI) methods in the control of power quality and system stability;
  8. Large-scale real-time simulation technology.

Dr. Yi Zhou
Prof. Dr. Buxiang Zhou
Dr. Lizhou Liu
Guest Editors

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Keywords

  • power quality
  • stability of power systems
  • power electronics
  • grid forming
  • modeling and control
  • optimization dispatch and planning
  • artificial intelligence

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Published Papers (1 paper)

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Research

18 pages, 8680 KiB  
Article
An Improved Prevention Strategy Based on Fault Probability Detection for Commutation Failure in Line-Commutated Converter-Based High-Voltage Direct Current Transmission Systems
by Ying Xu, Yi Zou, Lei Liu, Xiaopeng Li, Yufei Teng and Zijian Gao
Electronics 2024, 13(19), 3804; https://doi.org/10.3390/electronics13193804 - 25 Sep 2024
Viewed by 1115
Abstract
Commutation failure (CF) is one of the most prevalent events in line-commutated converter-based high-voltage direct current (LCC–HVDC) systems. The frequent occurrence of CF poses a significant threat to the safe and stable operation of power grids. The commutation failure prevention control (CFPREV) is [...] Read more.
Commutation failure (CF) is one of the most prevalent events in line-commutated converter-based high-voltage direct current (LCC–HVDC) systems. The frequent occurrence of CF poses a significant threat to the safe and stable operation of power grids. The commutation failure prevention control (CFPREV) is the main method to prevent the initial CF, which relies on the detection of a drop in AC voltage. However, its slow fault detection hinders the rapid response of post-fault control, thereby affecting the effectiveness of CF suppression. Therefore, this paper proposes a fast fault detection method based on Bayesian theory. This algorithm can calculate the conditional probability of each variable in a given dataset, effectively mitigating the impact of noise and errors in data to yield precise and dependable results. By processing the collected continuous data and calculating the probability of the existence of a fault point, it determines whether a fault occurs. Based on this method, an improved prevention strategy is proposed, which can effectively enhance the CF resilience of LCC–HVDC systems under AC faults. Finally, using the power systems computer-aided design (PSCAD) platform, the accuracy of the fault probability detection algorithm was verified based on actual engineering data. The effectiveness of the proposed strategy was further validated under three typical fault scenarios, leading to significant improvements: a 64.12% reduction in detection time for three-phase grounding faults, a 69.88% decrease for single line-to-ground faults, and a 36.84% improvement in phase-to-phase fault detection. Additionally, the overall performance of the strategy was thoroughly assessed through extensive simulations covering various fault cases within a selected range of typical faults. The simulations demonstrated the superiority of the proposed strategy in CF mitigation, with a significant reduction in incidents from 89 to 34 out of 150 tested scenarios. This highlights the robustness and reliability of the proposed strategy. Full article
(This article belongs to the Special Issue Control of Power Quality and System Stability)
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