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Full Coverage of Optimal Phasor Measurement Unit Placement Solutions in Distribution Systems Using Integer Linear Programming

Author

Listed:
  • Xuebing Chen

    (School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Lu Sun

    (Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore
    Experimental Power Grid Centre (EPGC), A*STAR, Singapore 627590, Singapore)

  • Tengpeng Chen

    (Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen 361102, China)

  • Yuhao Sun

    (National Centre for International Research on Photoelectric and Energy Materials, Yunnan University, Kunming 650091, China
    CTC Intelligence (Shenzhen) Tech Co., Ltd., Shenzhen 518110, China)

  • Rusli

    (School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • King Jet Tseng

    (Department of Engineering, Singapore Institute of Technology, Singapore 138683, Singapore)

  • Keck Voon Ling

    (School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Weng Khuen Ho

    (Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore)

  • Gehan A. J. Amaratunga

    (National Centre for International Research on Photoelectric and Energy Materials, Yunnan University, Kunming 650091, China
    Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK)

Abstract

Integer linear programming (ILP) has been widely applied to solve the optimal phasor measurement unit (PMU) placement (OPP) problem for its computational efficiency. Using ILP, a placement with minimum number of Phasor Measurement Units (PMUs) and maximum measurement redundancy can be obtained while ensuring system observability. Author response: please delete this above sentence. However, the existing ILP-based OPP methods does not guarantee full coverage of solutions to the optimization problem, which may sequentially results in suboptimal supervision of the system. In this paper, a hybrid ILP-based method is proposed to cover all solutions to the OPP problem without any omission. Comparing with the existing exhaustive searching methods, the proposed method is more computationally efficient, which makes finding all solutions in a large system a more feasible problem.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1552-:d:225599
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    Citations

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    Cited by:

    1. Henrique Pires Corrêa & Rafael Ribeiro de Carvalho Vaz & Flávio Henrique Teles Vieira & Sérgio Granato de Araújo, 2019. "Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation," Energies, MDPI, vol. 12(11), pages 1-26, May.
    2. 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.

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