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Application of heuristic algorithms to optimal PMU placement in electric power systems: An updated review

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  • Nazari-Heris, M.
  • Mohammadi-Ivatloo, B.

Abstract

Phasor measurement unit (PMU) plays an important role in operation, protection, and control of modern power systems. PMU provides real time, synchronized measurements of bus voltage and branch current phasors. It is neither economical nor possible to place all the buses of the system with PMUs because of their high cost and communication facilities. Attaining the minimal number of PMUs to access an observable power system is the main objective of optimal PMU placement (OPP) problem, which is solved by utilizing different techniques. Graph theoretic and mathematical programming procedures have been first introduced to solve OPP problem, aiming to access power system observability. Heuristic method as an experience-based technique is defined as a quick method for obtaining solutions for optimization problems, in which optimal solutions are not achievable using mathematical methods in finite time. This paper provided the literature review on different heuristic optimization methods to solve the OPP problem. Then, the available methods were classified and compared with different points of views. Results from the tests of researches on heuristic algorithms with and without the consideration of zero-injection buses were compared and superiorities of the introduced heuristic concepts were demonstrated with relative to each other.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:rensus:v:50:y:2015:i:c:p:214-228
    DOI: 10.1016/j.rser.2015.04.152
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    1. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
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    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. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Gharehpetian, G.B., 2018. "A comprehensive review of heuristic optimization algorithms for optimal combined heat and power dispatch from economic and environmental perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2128-2143.
    3. Bargos, Fabiano Fernandes & Lamas, Wendell de Queiroz & Bargos, Danubia Caporusso & Neto, Morun Bernardino & Pardal, Paula Cristiane Pinto Mesquita, 2016. "Location problem method applied to sugar and ethanol mills location optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 274-282.
    4. Muhammad Faisal Shehzad & Mainak Dan & Valerio Mariani & Seshadhri Srinivasan & Davide Liuzza & Carmine Mongiello & Roberto Saraceno & Luigi Glielmo, 2021. "A Heuristic Algorithm for Combined Heat and Power System Operation Management," Energies, MDPI, vol. 14(6), pages 1-22, March.
    5. 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.
    6. Ting Yang & Feng Zhai & Jialin Liu & Meng Wang & Haibo Pen, 2018. "Self-organized cyber physical power system blockchain architecture and protocol," International Journal of Distributed Sensor Networks, , vol. 14(10), pages 15501477188, October.
    7. Mohammad Shoaib Shahriar & Ibrahim Omar Habiballah & Huthaifa Hussein, 2018. "Optimization of Phasor Measurement Unit (PMU) Placement in Supervisory Control and Data Acquisition (SCADA)-Based Power System for Better State-Estimation Performance," Energies, MDPI, vol. 11(3), pages 1-15, March.
    8. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Haghrah, A., 2017. "Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation," Energy, Elsevier, vol. 128(C), pages 77-85.
    9. Su, Hongzhi & Wang, Chengshan & Li, Peng & Liu, Zhelin & Yu, Li & Wu, Jianzhong, 2019. "Optimal placement of phasor measurement unit in distribution networks considering the changes in topology," Applied Energy, Elsevier, vol. 250(C), pages 313-322.
    10. Zhi Wu & Xiao Du & Wei Gu & Ping Ling & Jinsong Liu & Chen Fang, 2018. "Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks," Energies, MDPI, vol. 11(7), pages 1-19, July.
    11. Mohammed Amroune & Ismail Musirin & Tarek Bouktir & Muhammad Murtadha Othman, 2017. "The Amalgamation of SVR and ANFIS Models with Synchronized Phasor Measurements for On-Line Voltage Stability Assessment," Energies, MDPI, vol. 10(11), pages 1-18, October.

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