IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i1p143-d125806.html
   My bibliography  Save this article

PMU Measurement-Based Intelligent Strategy for Power System Controlled Islanding

Author

Listed:
  • Yi Tang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Feng Li

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Chenyi Zheng

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Qi Wang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Yingjun Wu

    (College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Abstract

Controlled islanding is an effective remedy to prevent large-area blackouts in a power system under a critically unstable condition. When and where to separate the power system are the essential issues facing controlled islanding. In this paper, both tasks are studied to ensure higher time efficiency and a better post-splitting restoration effect. A transient stability assessment model based on extreme learning machine (ELM) and trajectory fitting (TF) is constructed to determine the start-up criterion for controlled islanding. This model works through prompt stability status judgment with ELM and selective result amendment with TF to ensure that the assessment is both efficient and accurate. Moreover, a splitting surface searching algorithm, subject to minimal power disruption, is proposed for determination of the controlled islanding implementing locations. A highlight of this algorithm is a proposed modified electrical distance concept defined by active power magnitude and reactance on transmission lines that realize a computational burden reduction without feasible solution loss. Finally, the simulation results and comparison analysis based on the New England 39-bus test system validates the implementation effects of the proposed controlled islanding strategy.

Suggested Citation

  • Yi Tang & Feng Li & Chenyi Zheng & Qi Wang & Yingjun Wu, 2018. "PMU Measurement-Based Intelligent Strategy for Power System Controlled Islanding," Energies, MDPI, vol. 11(1), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:143-:d:125806
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/1/143/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/1/143/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Rahman, 2014. "The Power of Communication," American Economic Review, American Economic Association, vol. 104(11), pages 3737-3751, November.
    2. Honglei Song & Junyong Wu & Kui Wu, 2014. "A Wide-Area Measurement Systems-Based Adaptive Strategy for Controlled Islanding in Bulk Power Systems," Energies, MDPI, vol. 7(4), pages 1-27, April.
    3. Yanzhen Zhou & Junyong Wu & Zhihong Yu & Luyu Ji & Liangliang Hao, 2016. "A Hierarchical Method for Transient Stability Prediction of Power Systems Using the Confidence of a SVM-Based Ensemble Classifier," Energies, MDPI, vol. 9(10), pages 1-20, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Arash Abyaz & Habib Panahi & Reza Zamani & Hassan Haes Alhelou & Pierluigi Siano & Miadreza Shafie-khah & Mimmo Parente, 2019. "An Effective Passive Islanding Detection Algorithm for Distributed Generations," Energies, MDPI, vol. 12(16), pages 1-19, August.
    2. Andrey Pazderin & Inga Zicmane & Mihail Senyuk & Pavel Gubin & Ilya Polyakov & Nikita Mukhlynin & Murodbek Safaraliev & Firuz Kamalov, 2023. "Directions of Application of Phasor Measurement Units for Control and Monitoring of Modern Power Systems: A State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-43, August.
    3. Ziad M. Ali & Seyed-Ehsan Razavi & Mohammad Sadegh Javadi & Foad H. Gandoman & Shady H.E. Abdel Aleem, 2018. "Dual Enhancement of Power System Monitoring: Improved Probabilistic Multi-Stage PMU Placement with an Increased Search Space & Mathematical Linear Expansion to Consider Zero-Injection Bus," Energies, MDPI, vol. 11(6), pages 1-17, June.
    4. Gyul Lee & Do-In Kim & Seon Hyeog Kim & Yong-June Shin, 2019. "Multiscale PMU Data Compression via Density-Based WAMS Clustering Analysis," Energies, MDPI, vol. 12(4), pages 1-17, February.

    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. Bayrak, Gökay & Kabalci, Ersan, 2016. "Implementation of a new remote islanding detection method for wind–solar hybrid power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1-15.
    2. David Spector, 2022. "Cheap Talk, Monitoring and Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 60(2), pages 193-216, March.
    3. Tao Jin & Fuliang Chu & Cong Ling & Daniel Legrand Mon Nzongo, 2015. "A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology," Energies, MDPI, vol. 8(4), pages 1-19, April.
    4. B. Douglas Bernheim & Erik Madsen, 2017. "Price Cutting and Business Stealing in Imperfect Cartels," American Economic Review, American Economic Association, vol. 107(2), pages 387-424, February.
    5. M. Hasanuzzaman & Ummu Salamah Zubir & Nur Iqtiyani Ilham & Hang Seng Che, 2017. "Global electricity demand, generation, grid system, and renewable energy polices: a review," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 6(3), May.
    6. Julio B. Clempner & Alexander S. Poznyak, 2021. "Analytical Method for Mechanism Design in Partially Observable Markov Games," Mathematics, MDPI, vol. 9(4), pages 1-15, February.
    7. William López-Castrillón & Héctor H. Sepúlveda & Cristian Mattar, 2021. "Off-Grid Hybrid Electrical Generation Systems in Remote Communities: Trends and Characteristics in Sustainability Solutions," Sustainability, MDPI, vol. 13(11), pages 1-29, May.
    8. Escobar, Juan F. & Llanes, Gastón, 2018. "Cooperation dynamics in repeated games of adverse selection," Journal of Economic Theory, Elsevier, vol. 176(C), pages 408-443.
    9. Zhen Chen & Xiaoyan Han & Chengwei Fan & Tianwen Zheng & Shengwei Mei, 2019. "A Two-Stage Feature Selection Method for Power System Transient Stability Status Prediction," Energies, MDPI, vol. 12(4), pages 1-15, February.
    10. David Spector, 2022. "Cheap Talk, Monitoring and Collusion," Post-Print halshs-03760756, HAL.
    11. Pau Casals-Torrens & Juan A. Martinez-Velasco & Alexandre Serrano-Fontova & Ricard Bosch, 2020. "Assessment of Unintentional Islanding Operations in Distribution Networks with Large Induction Motors," Energies, MDPI, vol. 13(2), pages 1-25, January.
    12. Porter, Robert H., 2020. "Mergers and coordinated effects," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    13. Fei Tang & Chufei Xiao & Xin Gao & Yifan Zhang & Nianchun Du & Benxi Hu, 2020. "Research on Transmission Network Expansion Planning Considering Splitting Control," Sustainability, MDPI, vol. 12(5), pages 1-20, February.
    14. Dan Huang & Qiyu Chen & Shiying Ma & Yichi Zhang & Shuyong Chen, 2018. "Wide-Area Measurement—Based Model-Free Approach for Online Power System Transient Stability Assessment," Energies, MDPI, vol. 11(4), pages 1-20, April.
    15. Sofana Reka. S & Tomislav Dragičević & Pierluigi Siano & S.R. Sahaya Prabaharan, 2019. "Future Generation 5G Wireless Networks for Smart Grid: A Comprehensive Review," Energies, MDPI, vol. 12(11), pages 1-17, June.
    16. Tóbiás, Áron, 2023. "Rational Altruism," Journal of Economic Behavior & Organization, Elsevier, vol. 207(C), pages 50-80.
    17. Yixing Du & Zhijian Hu, 2021. "Power System Transient Stability Assessment Based on Snapshot Ensemble LSTM Network," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
    18. Renchu Guan & Aoqing Wang & Yanchun Liang & Jiasheng Fu & Xiaosong Han, 2022. "International Natural Gas Price Trends Prediction with Historical Prices and Related News," Energies, MDPI, vol. 15(10), pages 1-14, May.
    19. Awaya, Yu & Krishna, Vijay, 2019. "Communication and cooperation in repeated games," Theoretical Economics, Econometric Society, vol. 14(2), May.
    20. Ruoyu Zhang & Junyong Wu & Yan Xu & Baoqin Li & Meiyang Shao, 2019. "A Hierarchical Self-Adaptive Method for Post-Disturbance Transient Stability Assessment of Power Systems Using an Integrated CNN-Based Ensemble Classifier," Energies, MDPI, vol. 12(17), pages 1-20, August.

    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:11:y:2018:i:1:p:143-:d:125806. 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.