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Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search

Author

Listed:
  • Lourdusamy Ramya Hyacinth

    (Department of Electrical and Electronics Engineering, Loyola-ICAM College of Engineering and Technology, Chennai 600034, India)

  • Venugopal Gomathi

    (Department of Electrical and Electronics Engineering, College of Engineering Guindy, Anna University, Chennai 600025, India)

Abstract

This paper proposes a method for the optimal placement of phasor measurement units (PMUs) for the complete observability of a power system based on the degree of the neighbourhood vertices. A three-stage algorithm is used to determine the minimum number of PMUs needed to make the system observable. The key objective of the proposed methodology is to minimize the total number of PMUs to completely observe a power system network and thereby minimize the installation cost. In addition, the proposed technique also focuses on improving the measurement redundancy. The proposed method is applied on standard IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 57-bus and IEEE 118-bus test systems and a hybrid AC/DC microgrid test system. The results obtained are compared with already existing methods in terms of the Bus Observability Index (BOI) and System Observability Redundancy Index (SORI). The results show that the proposed method is simple to implement and provides better placement locations for effective monitoring compared to other existing methods.

Suggested Citation

  • Lourdusamy Ramya Hyacinth & Venugopal Gomathi, 2021. "Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search," Energies, MDPI, vol. 14(16), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4782-:d:609579
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    References listed on IDEAS

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    1. Xuebing Chen & Lu Sun & Tengpeng Chen & Yuhao Sun & Rusli & King Jet Tseng & Keck Voon Ling & Weng Khuen Ho & Gehan A. J. Amaratunga, 2019. "Full Coverage of Optimal Phasor Measurement Unit Placement Solutions in Distribution Systems Using Integer Linear Programming," Energies, MDPI, vol. 12(8), pages 1-19, April.
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    Cited by:

    1. Wei Qiu & Kaiqi Sun & Huangqing Xiao, 2022. "Advances in Urban Power Distribution System," Energies, MDPI, vol. 15(19), pages 1-4, October.
    2. 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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