IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i5p1260-d1605317.html
   My bibliography  Save this article

Voltage Stability Estimation Considering Variability in Reactive Power Reserves Using Regression Trees

Author

Listed:
  • Masato Miyazaki

    (Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan)

  • Mutsumi Aoki

    (Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan)

  • Yuta Nakamura

    (Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan)

Abstract

The rapid integration of renewable energy sources, such as photovoltaic power systems, has reduced the necessary for synchronous generators, which traditionally contributed to grid stability during disturbances. This shift has led to a decrease in reactive power reserves (RPRs), raising concerns about voltage stability. Real-time monitoring of voltage stability is crucial for transmission system operators to implement timely corrective actions. However, conventional methods, such as continuation power flow calculations, are computationally intensive and unsuitable for large-scale power systems. Machine learning techniques using data from phasor measurement units have been proposed to estimate voltage stability. However, these methods do not consider changes in generator operating conditions and fluctuating RPRs. As renewable energy generation increases, the operating conditions of generators vary, which leads to significant changes in system RPRs and voltage stability. In this paper, a voltage stability margin is proposed using regression trees with RPRs varying based on generator operation conditions. Simulations based on the IEEE 9-bus system demonstrate that the proposed approach provides an accurate and efficient voltage stability estimation.

Suggested Citation

  • Masato Miyazaki & Mutsumi Aoki & Yuta Nakamura, 2025. "Voltage Stability Estimation Considering Variability in Reactive Power Reserves Using Regression Trees," Energies, MDPI, vol. 18(5), pages 1-16, March.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1260-:d:1605317
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/5/1260/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/5/1260/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daisuke Iioka & Takahiro Fujii & Toshio Tanaka & Tsuyoshi Harimoto & Junpei Motoyama, 2020. "Voltage Reduction in Medium Voltage Distribution Systems Using Constant Power Factor Control of PV PCS," Energies, MDPI, vol. 13(20), pages 1-17, 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. Daisuke Iioka & Kenichi Kusano & Takahiro Matsuura & Hiromu Hamada & Teru Miyazaki, 2022. "Appropriate Volt–Var Curve Settings for PV Inverters Based on Distribution Network Characteristics Using Match Rate of Operating Point," Energies, MDPI, vol. 15(4), pages 1-19, February.
    2. Fumiya Matsushima & Mutsumi Aoki & Yuta Nakamura & Suresh Chand Verma & Katsuhisa Ueda & Yusuke Imanishi, 2025. "Multi-Timescale Voltage Control Method Using Limited Measurable Information with Explainable Deep Reinforcement Learning," Energies, MDPI, vol. 18(3), pages 1-28, January.
    3. Kwang-Hoon Yoon & Joong-Woo Shin & Tea-Yang Nam & Jae-Chul Kim & Won-Sik Moon, 2022. "Operation Method of On-Load Tap Changer on Main Transformer Considering Reverse Power Flow in Distribution System Connected with High Penetration on Photovoltaic System," Energies, MDPI, vol. 15(17), pages 1-17, September.
    4. Joao Soares & Bruno Canizes & Zita Vale, 2021. "Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation," Energies, MDPI, vol. 14(23), pages 1-4, November.

    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:18:y:2025:i:5:p:1260-:d:1605317. 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.