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Multi-objective Discrete Artificial Bee Colony Based Phasor Measurement Unit Placement for Complete and Incomplete Observability Analysis

  • K. Mahapatra
  • M. R. Nayak
  • P. K. Rout
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 308)

Abstract

The paper presents a multi-objective discrete artificial bee colony (DABC)-based optimization algorithm for deciding placement sites for phasor measurement units (PMU) in a power system for both complete and incomplete observability studies. The influence of depths of unobservabilities of some of the buses on the number of optimal PMU placement sites is investigated in this study. Limited availability of communication facilities around the power network is considered as constraints in the optimization problem. The simultaneous optimization of the two conflicting objectives such as minimization of the number of PMUs and minimization of the number of unobserved buses are performed, and the Pareto optimal solutions are obtained using the non-dominated sorting DABC with crowding distance mechanism. The formulation is extended to solve the pragmatic-phased installation of PMUs for complete observability studies. The performance of the suggested approach is tested on three IEEE test systems. The results obtained demonstrate the technique that provides utilities with systematic approaches for incrementally placing PMUs in the best possible way, thereby cushioning their cost impact.

Keywords

Observability Phasor measurement units Discrete ABC 

References

  1. 1.
    Reynaldo F.N., Phadke A.G.: Phasor measurement unit placement techniques for complete and incomplete observability. IEEE Trans. Power Delivery 20(4) (2005)Google Scholar
  2. 2.
    Bei Gou.: Generalized integer linear programming formulation for optimal PMU placement. IEEE Trans. Power Syst. 23(3) (2008)Google Scholar
  3. 3.
    Kashan, M.H., Nahavandi, N., Kashan, A.H.: DisABC.: A new artificial bee colony algorithm for binary optimization. Appl. Soft Comput. 12, 342–352 (2012)Google Scholar
  4. 4.
    Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Glob. Optim. 39(3), 459–471 (2007)MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Siksha ‘O’ Anusandhan UniversityBhubaneswarIndia

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