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A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems

Author

Listed:
  • Mojgan Hojabri

    (Competence Center of Electronics, Institute of Electrical Engineering, Lucerne University of Applied Sciences and Arts, Horw 6048, Switzerland)

  • Ulrich Dersch

    (Competence Center of Intelligent Sensors and Networks, Institute of Electrical Engineering, Lucerne University of Applied Sciences and Arts, Horw 6048, Switzerland)

  • Antonios Papaemmanouil

    (Competence Center of Electronics, Institute of Electrical Engineering, Lucerne University of Applied Sciences and Arts, Horw 6048, Switzerland)

  • Peter Bosshart

    (Competence Center of Electronics, Institute of Electrical Engineering, Lucerne University of Applied Sciences and Arts, Horw 6048, Switzerland)

Abstract

Synchrophasor technology opens a new window for power system observability. Phasor measurement units (PMUs) are able to provide synchronized and accurate data such as frequency, voltage and current phasors, vibration, and temperature for power systems. Thus, the utilization of PMUs has become quite important in the fast monitoring, protection, and even the control of new and complicated distribution systems. However, data quality and communication are the main concerns for synchrophasor applications. This study presents a comprehensive survey on wide-area monitoring systems (WAMSs), PMUs, data quality, and communication requirements for the main applications of PMUs in a modern and smart distribution system with a variety of energy resources and loads. In addition, the main challenges for PMU applications as well as opportunities for the future use of this intelligent device in distribution systems will be presented in this paper.

Suggested Citation

  • Mojgan Hojabri & Ulrich Dersch & Antonios Papaemmanouil & Peter Bosshart, 2019. "A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems," Energies, MDPI, vol. 12(23), pages 1-23, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4552-:d:292225
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    Cited by:

    1. Khaoula Hassini & Ahmed Fakhfakh & Faouzi Derbel, 2023. "Optimal Placement of μ PMUs in Distribution Networks with Adaptive Topology Changes," Energies, MDPI, vol. 16(20), pages 1-27, October.
    2. Karthikeyan Subramanian & Ashok Kumar Loganathan, 2020. "Islanding Detection Using a Micro-Synchrophasor for Distribution Systems with Distributed Generation," Energies, MDPI, vol. 13(19), pages 1-31, October.
    3. Alessandro Mingotti & Federica Costa & Lorenzo Peretto & Roberto Tinarelli, 2021. "Closed-Form Expressions to Estimate the Mean and Variance of the Total Vector Error," Energies, MDPI, vol. 14(15), pages 1-15, July.
    4. Mussawir Ul Mehmood & Abasin Ulasyar & Abraiz Khattak & Kashif Imran & Haris Sheh Zad & Shibli Nisar, 2020. "Cloud Based IoT Solution for Fault Detection and Localization in Power Distribution Systems," Energies, MDPI, vol. 13(11), pages 1-19, May.
    5. Jing Zhang & Yiqi Li & Zhi Wu & Chunyan Rong & Tao Wang & Zhang Zhang & Suyang Zhou, 2021. "Deep-Reinforcement-Learning-Based Two-Timescale Voltage Control for Distribution Systems," Energies, MDPI, vol. 14(12), pages 1-15, June.
    6. Chinmayee Biswal & Binod Kumar Sahu & Manohar Mishra & Pravat Kumar Rout, 2023. "Real-Time Grid Monitoring and Protection: A Comprehensive Survey on the Advantages of Phasor Measurement Units," Energies, MDPI, vol. 16(10), pages 1-34, May.
    7. Zunaib Ali & Komal Saleem & Robert Brown & Nicholas Christofides & Sandra Dudley, 2022. "Performance Analysis and Benchmarking of PLL-Driven Phasor Measurement Units for Renewable Energy Systems," Energies, MDPI, vol. 15(5), pages 1-22, March.
    8. David Granados-Lieberman, 2020. "Global Harmonic Parameters for Estimation of Power Quality Indices: An Approach for PMUs," Energies, MDPI, vol. 13(9), pages 1-17, May.
    9. Nikolaos-Antonios I. Livanos & Sami Hammal & Nikolaos Giamarelos & Vagelis Alifragkis & Constantinos S. Psomopoulos & Elias N. Zois, 2023. "OpenEdgePMU: An Open PMU Architecture with Edge Processing for Future Resilient Smart Grids," Energies, MDPI, vol. 16(6), pages 1-29, March.
    10. Do-In Kim, 2021. "Complementary Feature Extractions for Event Identification in Power Systems Using Multi-Channel Convolutional Neural Network," Energies, MDPI, vol. 14(15), pages 1-15, July.
    11. Phylicia Cicilio & David Glennon & Adam Mate & Arthur Barnes & Vishvas Chalishazar & Eduardo Cotilla-Sanchez & Bjorn Vaagensmith & Jake Gentle & Craig Rieger & Richard Wies & Mohammad Heidari Kapourch, 2021. "Resilience in an Evolving Electrical Grid," Energies, MDPI, vol. 14(3), pages 1-25, January.
    12. Muhammad Musadiq Ahmed & Muhammad Amjad & Muhammad Ali Qureshi & Kashif Imran & Zunaib Maqsood Haider & Muhammad Omer Khan, 2022. "A Critical Review of State-of-the-Art Optimal PMU Placement Techniques," Energies, MDPI, vol. 15(6), pages 1-25, March.
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