IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i17p4330-d1467135.html
   My bibliography  Save this article

Research Methods for Transient Stability Analysis of Power Systems under Large Disturbances

Author

Listed:
  • Hao Wu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Jing Li

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Haibo Yang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract

Transient stability analysis is critical for maintaining the reliability and security of power systems. This paper provides a comprehensive review of research methods for transient stability analysis under large disturbances, detailing the modeling concepts and implementation approaches. The research methods for large disturbance transient stability analysis are categorized into five main types: simulation methods, direct methods, data-driven methods, analytical methods, and other methods. Within the analytical method category, several common analytical strategies are introduced, including the asymptotic expansion method, intrusive approximation method, and other analytical methods. The fundamental principles, characteristics, and recent research advancements of these methods are detailed, with particular attention to their performance in various aspects such as computational efficiency, accuracy, applicability to different system models, and stability region estimation. The advantages and disadvantages of each method are compared, offering insights to support further research into transient stability analysis for hybrid power grids under large disturbances.

Suggested Citation

  • Hao Wu & Jing Li & Haibo Yang, 2024. "Research Methods for Transient Stability Analysis of Power Systems under Large Disturbances," Energies, MDPI, vol. 17(17), pages 1-25, August.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4330-:d:1467135
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/17/4330/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/17/4330/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bullich-Massagué, Eduard & Cifuentes-García, Francisco-Javier & Glenny-Crende, Ignacio & Cheah-Mañé, Marc & Aragüés-Peñalba, Mònica & Díaz-González, Francisco & Gomis-Bellmunt, Oriol, 2020. "A review of energy storage technologies for large scale photovoltaic power plants," Applied Energy, Elsevier, vol. 274(C).
    2. Petar Sarajcev & Antonijo Kunac & Goran Petrovic & Marin Despalatovic, 2022. "Artificial Intelligence Techniques for Power System Transient Stability Assessment," Energies, MDPI, vol. 15(2), pages 1-21, January.
    3. Jun Liu & Zhanhong Wei & Wanliang Fang & Chao Duan & Junxian Hou & Zutao Xiang, 2015. "Modified Quasi-Steady State Model of DC System for Transient Stability Simulation under Asymmetric Faults," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-12, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nawaz Edoo & Robert T. F. Ah King, 2021. "Techno-Economic Analysis of Utility-Scale Solar Photovoltaic Plus Battery Power Plant," Energies, MDPI, vol. 14(23), pages 1-22, December.
    2. Qiu, Rui & Zhang, Haoran & Wang, Guotao & Liang, Yongtu & Yan, Jinyue, 2023. "Green hydrogen-based energy storage service via power-to-gas technologies integrated with multi-energy microgrid," Applied Energy, Elsevier, vol. 350(C).
    3. Angel L. Cedeño & Reinier López Ahuar & José Rojas & Gonzalo Carvajal & César Silva & Juan C. Agüero, 2022. "Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming," Energies, MDPI, vol. 15(17), pages 1-21, September.
    4. Shen, Boyang & Chen, Yu & Li, Chuanyue & Wang, Sheng & Chen, Xiaoyuan, 2021. "Superconducting fault current limiter (SFCL): Experiment and the simulation from finite-element method (FEM) to power/energy system software," Energy, Elsevier, vol. 234(C).
    5. Ting Zhang & Shuaishuai Cao & Lingying Pan & Chenyu Zhou, 2020. "A Policy Effect Analysis of China’s Energy Storage Development Based on a Multi-Agent Evolutionary Game Model," Energies, MDPI, vol. 13(23), pages 1-35, November.
    6. Paweł Pijarski & Piotr Kacejko & Piotr Miller, 2023. "Advanced Optimisation and Forecasting Methods in Power Engineering—Introduction to the Special Issue," Energies, MDPI, vol. 16(6), pages 1-20, March.
    7. Ziqi Liu & Tingting Su & Zhiying Quan & Quanli Wu & Yu Wang, 2023. "Review on the Optimal Configuration of Distributed Energy Storage," Energies, MDPI, vol. 16(14), pages 1-17, July.
    8. Wang, Ji-Xiang & Zhong, Mingliang & Wu, Zhe & Guo, Mengyue & Liang, Xin & Qi, Bo, 2022. "Ground-based investigation of a directional, flexible, and wireless concentrated solar energy transmission system," Applied Energy, Elsevier, vol. 322(C).
    9. Yong Zhu & Mingyi Liu & Lin Wang & Jianxing Wang, 2022. "Potential Failure Prediction of Lithium-ion Battery Energy Storage System by Isolation Density Method," Sustainability, MDPI, vol. 14(12), pages 1-14, June.
    10. Ji, Zhengsen & Li, Wanying & Niu, Dongxiao, 2024. "Optimal investment decision of agrivoltaic coupling energy storage project based on distributed linguistic trust and hybrid evaluation method," Applied Energy, Elsevier, vol. 353(PA).
    11. Sui, Yunren & Lin, Haosheng & Ding, Zhixiong & Li, Fuxiang & Sui, Zengguang & Wu, Wei, 2024. "Compact, efficient, and affordable absorption Carnot battery for long-term renewable energy storage," Applied Energy, Elsevier, vol. 357(C).
    12. Kebede, Abraham Alem & Kalogiannis, Theodoros & Van Mierlo, Joeri & Berecibar, Maitane, 2022. "A comprehensive review of stationary energy storage devices for large scale renewable energy sources grid integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    13. Ali M. Hakami & Kazi N. Hasan & Mohammed Alzubaidi & Manoj Datta, 2022. "A Review of Uncertainty Modelling Techniques for Probabilistic Stability Analysis of Renewable-Rich Power Systems," Energies, MDPI, vol. 16(1), pages 1-26, December.
    14. Zhao, Chunyang & Andersen, Peter Bach & Træholt, Chresten & Hashemi, Seyedmostafa, 2023. "Grid-connected battery energy storage system: a review on application and integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    15. Álex Omar Topa Gavilema & José Domingo Álvarez & José Luis Torres Moreno & Manuel Pérez García, 2021. "Towards Optimal Management in Microgrids: An Overview," Energies, MDPI, vol. 14(16), pages 1-25, August.
    16. Johanna Pucker-Singer & Christian Aichberger & Jernej Zupančič & Camilla Neumann & David Neil Bird & Gerfried Jungmeier & Andrej Gubina & Andreas Tuerk, 2021. "Greenhouse Gas Emissions of Stationary Battery Installations in Two Renewable Energy Projects," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
    17. Paulo Rotella Junior & Luiz Célio Souza Rocha & Sandra Naomi Morioka & Ivan Bolis & Gianfranco Chicco & Andrea Mazza & Karel Janda, 2021. "Economic Analysis of the Investments in Battery Energy Storage Systems: Review and Current Perspectives," Energies, MDPI, vol. 14(9), pages 1-29, April.
    18. Adedayo Owosuhi & Yskandar Hamam & Josiah Munda, 2023. "Maximizing the Integration of a Battery Energy Storage System–Photovoltaic Distributed Generation for Power System Harmonic Reduction: An Overview," Energies, MDPI, vol. 16(6), pages 1-22, March.
    19. Panagiota M. Deligianni & George J. Tsekouras & Costas D. Tsirekis & Vassiliki T. Kontargyri & Fotis D. Kanellos & Panagiotis A. Kontaxis, 2020. "Techno-Economic Optimization Analysis of an Autonomous Photovoltaic Power System for a Shoreline Electrode Station of HVDC Link: Case Study of an Electrode Station on the Small Island of Stachtoroi fo," Energies, MDPI, vol. 13(21), pages 1-49, October.
    20. Dimitris A. Barkas & Stavros D. Kaminaris & Konstantinos K. Kalkanis & George Ch. Ioannidis & Constantinos S. Psomopoulos, 2022. "Condition Assessment of Power Transformers through DGA Measurements Evaluation Using Adaptive Algorithms and Deep Learning," Energies, MDPI, vol. 16(1), pages 1-17, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4330-:d:1467135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.