IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i2p345-d307278.html
   My bibliography  Save this article

Assessment of Unintentional Islanding Operations in Distribution Networks with Large Induction Motors

Author

Listed:
  • Pau Casals-Torrens

    (Department of Electrical Engineering, Polytechnic University of Catalonia, ETSEIB-Av. Diagonal 647, 08028 Barcelona, Spain)

  • Juan A. Martinez-Velasco

    (Department of Electrical Engineering, Polytechnic University of Catalonia, ETSEIB-Av. Diagonal 647, 08028 Barcelona, Spain)

  • Alexandre Serrano-Fontova

    (Department of Electrical Engineering, Polytechnic University of Catalonia, ETSEIB-Av. Diagonal 647, 08028 Barcelona, Spain)

  • Ricard Bosch

    (Department of Electrical Engineering, Polytechnic University of Catalonia, ETSEIB-Av. Diagonal 647, 08028 Barcelona, Spain)

Abstract

This paper is aimed at assessing the impact of unintentional islanding operations (IOs) in the presence of large induction motors (IMs) within distribution networks (DNs). When a fault occurs, following the circuit breaker (CB) fault clearing, the IMs act transiently as generators, due to its inertia, until the CB reclosing takes place. The present work is the outcome of a project carried out in a small DN, where field measurements were recorded over two years. This paper provides a detailed description of the test system, a selected list of field measurements, and a discussion on modeling guidelines used to create the model of the actual power system. The main goal is to validate the system model by comparing field measurements with simulation results. The comparison of simulations and field measurements prove the appropriateness of the modeling guidelines used in this work and highlight the high accuracy achieved in the implemented three-phase Matlab/Simulink model.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:345-:d:307278
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/2/345/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/2/345/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhe Zhang & Hang Yang & Xianggen Yin & Jiexiang Han & Yong Wang & Guoyan Chen, 2018. "A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment," Energies, MDPI, vol. 11(4), pages 1-17, March.
    2. Alexandre Serrano-Fontova & Pablo Casals Torrens & Ricard Bosch, 2019. "Power Quality Disturbances Assessment during Unintentional Islanding Scenarios. A Contribution to Voltage Sag Studies," Energies, MDPI, vol. 12(16), pages 1-21, August.
    3. Fabio Bignucolo & Alberto Cerretti & Massimiliano Coppo & Andrea Savio & Roberto Turri, 2017. "Impact of Distributed Generation Grid Code Requirements on Islanding Detection in LV Networks," Energies, MDPI, vol. 10(2), pages 1-16, January.
    4. Haifeng Li & Qing Chen & Chang Fu & Zhe Yu & Di Shi & Zhiwei Wang, 2019. "Bayesian Estimation on Load Model Coefficients of ZIP and Induction Motor Model," Energies, MDPI, vol. 12(3), pages 1-16, February.
    5. 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.
    6. Anna Rita Di Fazio & Mario Russo & Sara Valeri, 2015. "A New Protection System for Islanding Detection in LV Distribution Systems," Energies, MDPI, vol. 8(5), pages 1-19, April.
    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. 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. Wagner A. Vilela Junior & Antonio P. Coimbra & Gabriel A. Wainer & Joao Caetano Neto & Jose A. G. Cararo & Marcio R. C. Reis & Paulo V. Santos & Wesley P. Calixto, 2021. "Analysis and Adequacy Methodology for Voltage Violations in Distribution Power Grid," Energies, MDPI, vol. 14(14), pages 1-21, July.
    3. Mingang Tan & Chaohai Zhang & Bin Chen, 2022. "Size Estimation of Bulk Capacitor Removal Using Limited Power Quality Monitors in the Distribution Network," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    4. Biyun Chen & Haoying Chen & Yiyi Zhang & Junhui Zhao & Emad Manla, 2019. "Risk Assessment for the Power Grid Dispatching Process Considering the Impact of Cyber Systems," Energies, MDPI, vol. 12(6), pages 1-18, March.
    5. 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.
    6. Pavan Babu Bandla & Indragandhi Vairavasundaram & Yuvaraja Teekaraman & Ramya Kuppusamy & Srete Nikolovski, 2021. "Real Time Sustainable Power Quality Analysis of Non-Linear Load under Symmetrical Conditions," Energies, MDPI, vol. 15(1), pages 1-16, December.
    7. Michael Felix Pacevicius & Marilia Ramos & Davide Roverso & Christian Thun Eriksen & Nicola Paltrinieri, 2022. "Managing Heterogeneous Datasets for Dynamic Risk Analysis of Large-Scale Infrastructures," Energies, MDPI, vol. 15(9), pages 1-40, April.
    8. Maciej Kuboń & Zbigniew Skibko & Sylwester Tabor & Urszula Malaga-Toboła & Andrzej Borusiewicz & Wacław Romaniuk & Janusz Zarajczyk & Pavel Neuberger, 2023. "Analysis of Voltage Distortions in the Power Grid Arising from Agricultural Biogas Plant Operation," Energies, MDPI, vol. 16(17), pages 1-21, August.
    9. Juan-José González de-la-Rosa & Manuel Pérez-Donsión, 2020. "Special Issue “Analysis for Power Quality Monitoring”," Energies, MDPI, vol. 13(3), pages 1-6, January.
    10. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    11. 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.
    12. Menghua Liu & Wei Zhao & Qing Wang & Songling Huang & Kunpeng Shi, 2018. "An Irregular Current Injection Islanding Detection Method Based on an Improved Impedance Measurement Scheme," Energies, MDPI, vol. 11(9), pages 1-18, September.
    13. Fabio Bignucolo & Alberto Cerretti & Massimiliano Coppo & Andrea Savio & Roberto Turri, 2017. "Impact of Distributed Generation Grid Code Requirements on Islanding Detection in LV Networks," Energies, MDPI, vol. 10(2), pages 1-16, January.
    14. Fabio Bignucolo & Manuele Bertoluzzo, 2020. "Application of Solid-State Transformers in a Novel Architecture of Hybrid AC/DC House Power Systems," Energies, MDPI, vol. 13(13), pages 1-18, July.
    15. Fabio Bignucolo & Alberto Cerretti & Massimiliano Coppo & Andrea Savio & Roberto Turri, 2017. "Effects of Energy Storage Systems Grid Code Requirements on Interface Protection Performances in Low Voltage Networks," Energies, MDPI, vol. 10(3), pages 1-20, March.
    16. Jagannath Patra & Nitai Pal, 2022. "A Mathematical Approach of Voltage Sag Analysis Incorporating Bivariate Probability Distribution in a Meshed System," Energies, MDPI, vol. 15(20), pages 1-19, October.
    17. Xiaoming Mao & Junxian Chen, 2019. "A Fast Method to Compute the Dynamic Response of Induction Motor Loads Considering the Negative-Sequence Components in Stability Studies," Energies, MDPI, vol. 12(9), pages 1-19, May.
    18. 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.
    19. Francesco Simmini & Marco Agostini & Massimiliano Coppo & Tommaso Caldognetto & Andrea Cervi & Fabio Lain & Ruggero Carli & Roberto Turri & Paolo Tenti, 2020. "Leveraging Demand Flexibility by Exploiting Prosumer Response to Price Signals in Microgrids," Energies, MDPI, vol. 13(12), pages 1-19, June.
    20. Zhenzhi Lin & Yuxuan Zhao & Shengyuan Liu & Fushuan Wen & Yi Ding & Li Yang & Chang Han & Hao Zhou & Hongwei Wu, 2018. "A New Indicator of Transient Stability for Controlled Islanding of Power Systems: Critical Islanding Time," Energies, MDPI, vol. 11(11), pages 1-10, 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:13:y:2020:i:2:p:345-:d:307278. 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.