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Optimal Placement of μ PMUs in Distribution Networks with Adaptive Topology Changes

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  • Khaoula Hassini

    (Department of Electrical Engineering and Information Technology, Leipzig University of Applied Sciences, 04277 Leipzig, Germany
    Laboratory of Signals, Systems, Artificial Intelligence and Networks (SM@RTS), Digital Research Center of Sfax, Sfax 3018, Tunisia
    National School of Electronics and Telecommunications of Sfax, Technopole of Sfax, Sfax 3018, Tunisia)

  • Ahmed Fakhfakh

    (Laboratory of Signals, Systems, Artificial Intelligence and Networks (SM@RTS), Digital Research Center of Sfax, Sfax 3018, Tunisia
    National School of Electronics and Telecommunications of Sfax, Technopole of Sfax, Sfax 3018, Tunisia)

  • Faouzi Derbel

    (Department of Electrical Engineering and Information Technology, Leipzig University of Applied Sciences, 04277 Leipzig, Germany)

Abstract

With the increasing integration of energy sources and the growing complexity of distribution networks, it is crucial to monitor and early detection of topological changes to ensure grid stability and resilience. Current methods, for optimizing the placement of micro Phasor Measurement Units ( μ PMUs) focus on achieving observability and efficient monitoring. These algorithms aim to minimize the number of μ PMUs needed while maintaining system observability or meeting criteria for observability. However, they may not consider all real-world constraints and uncertainties. In this study, we introduce a strategy for placing μ PMUs with the objective of enhancing observability and monitoring capabilities. Our proposed algorithm employs a technique that makes optimal decisions at each step to approximate the global optimum. To determine the locations for μ PMUs our algorithm takes into account parameters such as network structure, key nodes, and system stability. One distinguishing feature is its adaptability to distribution networks, including changes, in topology or potential device failures. Unlike classical approaches, our algorithm can continuously provide optimal placement solutions even in evolving network conditions. We have demonstrated that our suggested method achieves better results in terms of observability value and the required number of μ PMUs compared to the state-of-the-art. By strategically placing μ PMUs, operators can improve system observability, quickly detect and locate faults, and make informed decisions for effective network operations. This research helps improve optimal placement strategies for μ PMUs by providing practical and effective solutions to improve distribution network reliability, resilience, and performance in the face of changing dynamics.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7047-:d:1257797
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    References listed on IDEAS

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    1. 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.
    2. Nikolaos P. Theodorakatos & Miltiadis Lytras & Rohit Babu, 2020. "Towards Smart Energy Grids: A Box-Constrained Nonlinear Underdetermined Model for Power System Observability Using Recursive Quadratic Programming," Energies, MDPI, vol. 13(7), pages 1-17, April.
    3. Nazari-Heris, M. & Mohammadi-Ivatloo, B., 2015. "Application of heuristic algorithms to optimal PMU placement in electric power systems: An updated review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 214-228.
    4. Smitha Joyce Pinto & Pierluigi Siano & Mimmo Parente, 2023. "Review of Cybersecurity Analysis in Smart Distribution Systems and Future Directions for Using Unsupervised Learning Methods for Cyber Detection," Energies, MDPI, vol. 16(4), pages 1-24, February.
    5. Ambrosino, Daniela & Grazia Scutella, Maria, 2005. "Distribution network design: New problems and related models," European Journal of Operational Research, Elsevier, vol. 165(3), pages 610-624, September.
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