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Optimal Phasor Measurement Unit Placement using Genetic Algorithms

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Computational Methods in Neural Modeling (IWANN 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2686))

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Abstract

A genetic algorithm-based procedure for solving the optimal phasor measurement units (PMUs) placement problem is presented. A PMU measures voltage and current phasors at the bus where is placed. These measurements must realize the electrical power system observable, in order to perform the state estimation. Our proposal have two essential advantages: (1) it determines the minimal number of PMUs and their geographic distribution making the network observable; (2) it shows the relationship between the number of current phasors that must be measured on each PMUs and the necessary number of PMUs for a given network. The placement algorithm has been tested on 4 standards IEEE-bus, ranging in size from 14 to 118 buses.

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References

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Author information

Authors and Affiliations

  1. Dpto. Electrónica. E. T. S. I. Informática, Universidad de Málaga, Campus Teatinos s/n., 29071, Málaga, Spain

    F. J. Marín

  2. Dpto. Tecnología Electrónica. E. T. S. I. Telecomunicación, Universidad de Málaga, Campus Teatinos s/n, 29071, Málaga, Spain

    F. García-Lagos, G. Joya & F. Sandoval

Authors
  1. F. J. Marín
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  2. F. García-Lagos
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  3. G. Joya
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  4. F. Sandoval
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Editors and Affiliations

  1. E.T.S. de Ingeniería Informática Departamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Juan del Rosal, 16, 28040, Madrid, Spain

    José Mira  & José R. Álvarez  & 

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Marín, F.J., García-Lagos, F., Joya, G., Sandoval, F. (2003). Optimal Phasor Measurement Unit Placement using Genetic Algorithms. In: Mira, J., Álvarez, J.R. (eds) Computational Methods in Neural Modeling. IWANN 2003. Lecture Notes in Computer Science, vol 2686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44868-3_62

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  • DOI: https://doi.org/10.1007/3-540-44868-3_62

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40210-7

  • Online ISBN: 978-3-540-44868-6

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