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Electronics
Special Issues
AI-Based Power System Stability and Control Analysis
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AI-Based Power System Stability and Control Analysis

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

Deadline for manuscript submissions: 20 May 2024 | Viewed by 2986

Special Issue Editors

Dr. Le Zheng

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Interests: power system stability analysis and optimal control; big data, machine learning and artificial intelligence and their applications in power systems; new energy power system optimization and analysis
Dr. Jožef Ritonja

E-Mail Website
Guest Editor
Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, 2000 Maribor, Slovenia
Interests: electric machines; control theory and applications; power systems
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammed Agamy

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University at Albany SUNY, Albany, NY, USA
Interests: resonant power conversion;renewable resources; power factor correction; grid interface of distributed energy resources; modeling and control of power converter systems

Special Issue Information

Dear Colleagues,

Artificial Intelligence (AI) has been extremely successful in many areas. In power systems, AI has been applied in load/renewable forecasting, intrusion detection, customer behavior analysis, etc. This Special Issue will focus on how AI can be leveraged for power system stability analysis and control, which is especially challenging due to the increasing penetration of converter-interfaced generations (CIG) in modern power systems. AI with real-world data and cutting-edge techniques will be discussed.

This Special Issue will present new promising research directions in power system stability analysis and control, and will disseminate and discuss research on AI. Topics of interest include, but are not limited to, the following:

  • Hybrid augmented intelligence for AI in power system stability analysis and control;
  • Interpretable AI in power system stability analysis and control;
  • Casual inference in power system stability analysis and control;
  • Observability and controllability assessment of AI-based power system stability analysis and control;
  • Benchmark dataset creation requirements for power system stability analysis;
  • AI in measurements-based online stability assessment and emergency control;
  • AI in multiple time-scale system dynamics dominated by CIGs;
  • AI in non-linear and complex system dynamics.

Dr. Le Zheng
Dr. Jožef Ritonja
Dr. Mohammed Agamy
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • hybrid augmented intelligence
  • interpretability
  • CIGs

Published Papers (3 papers)

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Research

18 pages, 7193 KiB  
Article
An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin
by Luojia Yang, Yuhong Wang, Shilin Gao, Zongsheng Zheng, Qiliang Jiang and Chenyu Zhou
Electronics 2023, 12(17), 3603; https://doi.org/10.3390/electronics12173603 - 25 Aug 2023
Viewed by 586
Abstract
Aiming at the difficult problem of broadband oscillation localization in power systems, the intelligent localization method of an oscillation source based on a digital twin is proposed, and the oscillation source localization system is thus constructed. Firstly, a digital twin-based oscillation source localization [...] Read more.
Aiming at the difficult problem of broadband oscillation localization in power systems, the intelligent localization method of an oscillation source based on a digital twin is proposed, and the oscillation source localization system is thus constructed. Firstly, a digital twin-based oscillation source localization method and its system architecture are proposed. Furthermore, an intelligent positioning method of the oscillation source, based on data-driven and mechanism fusion, is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the super-resolution technique is used to realize the super-resolution measurement of broadband oscillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, branch potential energy is used as the input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately. Full article
(This article belongs to the Special Issue AI-Based Power System Stability and Control Analysis)
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16 pages, 2790 KiB  
Article
Enhancing System Reliability and Transient Voltage Stability through Optimized Power Sources and Network Planning
by Fan Li, Dong Liu, Dan Wang, Wei Wang, Zhongjian Liu, Haoyang Yu, Xiaofan Su, De Zhang and Xiaoman Wu
Electronics 2023, 12(14), 3190; https://doi.org/10.3390/electronics12143190 - 23 Jul 2023
Viewed by 992
Abstract
Renewable energy is an important means of addressing climate change and achieving carbon peaking and carbon neutrality goals. However, the uncertainty and randomness of renewable energy also have a certain impact on the flexibility, reliability, and transient voltage stability of the power system. [...] Read more.
Renewable energy is an important means of addressing climate change and achieving carbon peaking and carbon neutrality goals. However, the uncertainty and randomness of renewable energy also have a certain impact on the flexibility, reliability, and transient voltage stability of the power system. These effects also pose great challenges to power system planning. In order to address the impact of renewable energy on power system planning, this paper proposes a two-layer optimization model for power sources and network planning which takes into account both reliability and transient voltage stability requirements. The upper-layer grid planning problem is formulated with consideration of the system reliability index, and the transient stability requirements and construction and operation costs are included in the lower-layer problem to determine a construction scheme for power generation and energy storage units. To solve the complex nonlinear problem efficiently, a two-layer iterative algorithm utilizing the adaptive particle swarm optimization (PSO) technique is proposed. The effectiveness of the proposed method is demonstrated via its application to the IEEE 33 test system. The results show that the proposed optimization approach effectively addresses the power system transmission and generation planning problem while improving the efficiency and reliability of the system’s operation. The findings can guide the design and implementation of future power system planning and operation strategies. Full article
(This article belongs to the Special Issue AI-Based Power System Stability and Control Analysis)
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19 pages, 5046 KiB  
Article
Calculation Method of DC Fault Overvoltage Peak Value for Multi-Send HVDC Systems with Wind Power
by Fan Li, Dong Liu, Xiaonan Han, Boyu Qin, Zhongjian Liu, Haoyang Yu, De Zhang, Xiaofan Su and Mingjie Wang
Electronics 2023, 12(14), 3157; https://doi.org/10.3390/electronics12143157 - 20 Jul 2023
Viewed by 826
Abstract
Commutation failure (CF) and DC blocking (DCB) faults are common occurrences in high-voltage direct current (HVDC) systems, and their impact on the power grid can be significant due to sudden power fluctuations. These issues pose particular challenges in multi-send HVDC systems due to [...] Read more.
Commutation failure (CF) and DC blocking (DCB) faults are common occurrences in high-voltage direct current (HVDC) systems, and their impact on the power grid can be significant due to sudden power fluctuations. These issues pose particular challenges in multi-send HVDC systems due to the intricate interaction between AC and DC components. To tackle these challenges, this paper proposes a method for analyzing the peak overvoltage at the converter bus resulting from DC faults in multi-send HVDC systems. The proposed method comprehensively considers the influence of DC/DC coupling and wind turbine low-voltage ride through (LVRT) characteristics on overvoltage. It offers a straightforward approach to calculate the peak overvoltage following a DC fault without the need for complex modeling or dynamic simulation software. By leveraging the equivalent parameters of the AC system and operational parameters of the DC system, the method effectively quantifies the overvoltage. The primary objective of this study is to address multi-send HVDC systems and establish computational formulas that enable a quantitative assessment of transient overvoltage resulting from DC faults. The analysis explores several influencing factors, uncovering that fault-induced overvoltage is influenced by aspects such as system strength and wind turbine reactive power dynamics. In a single-send HVDC system, the level of overvoltage in the system is primarily affected by the short-circuit ratio. A higher short-circuit ratio results in a lower overvoltage level. On the other hand, in multi-send HVDC systems, the overvoltage level is determined by the equivalent impedance of the individual systems. In DC systems where turbines are present in the DC near zone, the overvoltage level at the converter bus is influenced by the power characteristics of the turbines during the LVRT. To validate the accuracy of the proposed method, a comprehensive verification process is conducted. Through this research, the paper aims to contribute to the understanding and management of transient overvoltage in multi-send HVDC systems. By considering relevant factors and employing an equivalent model, the proposed method offers a practical approach for assessing overvoltage and facilitating the design and operation of such systems. Full article
(This article belongs to the Special Issue AI-Based Power System Stability and Control Analysis)
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