Optimal Placement of Phasor Measurement Units by Genetic Algorithm

Allagui B.; Marouani I.; Hadj Abdallah H.

doi:doi:10.11648/j.ijepe.20130201.12

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Optimal Placement of Phasor Measurement Units by Genetic Algorithm

Allagui B., Marouani I., Hadj Abdallah H.

Published in International Journal of Energy and Power Engineering (Volume 2, Issue 1)

Published: 20 February 2013

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Abstract

Monitoring and supervision of power systems are provided by the control center, whose role is the design, coordination and network management. This paper presents a control technique based on the implantation of measurement units at the network buses. This technique should meet two requirements: ensure the complete system observability and find the optimal locations of PMUs with the minimum cost. The problem was formulated as a mono-objective optimization problem and its resolution was made by implementing a genetic algorithm (GA). The proposed method is tested on three tests networks and the results are compared with other resolution techniques. The simulation results ensure the complete system observability and validate the presented technique.

Published in	International Journal of Energy and Power Engineering (Volume 2, Issue 1)
DOI	10.11648/j.ijepe.20130201.12
Page(s)	12-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

PMU, Optimal Placement, Complete System Observability, Genetic Algorithm

References

[1]	B. Xu and A. Abur, "Optimal placement of phasor mea-surement units for state estimation," Final Project Report, PSERC, Oct. 2005.
[2]	B. Xu and A. Abur, "Observability analysis and measurement placement for systems with PMUs," in proc. IEEE Power Eng. Soc. Power Systems Conf. Expo., Oct. 2004, pp. 943–946.
[3]	A. Abur and A. G. Exposito, Power System State Estimation: Theory and Implementation. New York: Mercel Dekker, 2004.
[4]	B. Milosevic, M. Begovic, "Nondominated sorting genetic algorithm for optimal phasor measurement placement", IEEE Transactions on. Power Systems Vol.18, No.1, Feb. 2003, pp. 69–75.
[5]	Bei Gou, ’’Generalized Integer Linear Programming Formu-lation for Optimal PMU Placement,’’ IEEE TRANSAC-TIONS ON POWER SYSTEMS, VOL. 23, NO. 3, AU-GUST 2008.
[6]	IEEE Working Group H-7, "Synchronized Sampling and Phasor Measurements for Relaying and Control", IEEE Transactions on Power Delivery, Vol. 9, No.1, January 1994, pp. 442-452.
[7]	IEEE Working Group H-8, "IEEE Standard for Synchro-phasors for Power Systems", IEEE Transactions on Power Delivery, Vol. 13, No. 1, January 1998.
[8]	Sanjay Dambhare, ’’Optimal zero Injection Considetrations in PMU Placement : An ILP Approach,’’ 16th PSCC, Glasgow, Scotland, July 14-18,2008.
[9]	J.R.Altman, "A Practical Comprehensive Approach to PMU Placement for Full Observability", Master of Science In Electrical Engineering, January 28, 2007 Blacksburg, Vir-ginia.
[10]	T.A.Baldwin, L. Mili M. B. Boisen, Jr. R. Adapa, "Power system observability with minimal phasor measurement placement", IEEE Transaction. on Power Systems, Vol. 8, No. 2, May 1993, pp 2381- 2388.
[11]	CHIH-WEN LIU, ’’Genetic Algorithms as a Reactive Power Source Dispatching Aid Genetic Algorithms as a Reactive Power Source Dispatching Aid,’’ Proc. Natl. Sci. Counc. ROC(A). Proc. Natl. Sci. Counc. ROC(A).

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APA Style

Allagui B., Marouani I., Hadj Abdallah H. (2013). Optimal Placement of Phasor Measurement Units by Genetic Algorithm. International Journal of Energy and Power Engineering, 2(1), 12-17. https://doi.org/10.11648/j.ijepe.20130201.12

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ACS Style

Allagui B.; Marouani I.; Hadj Abdallah H. Optimal Placement of Phasor Measurement Units by Genetic Algorithm. Int. J. Energy Power Eng. 2013, 2(1), 12-17. doi: 10.11648/j.ijepe.20130201.12

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AMA Style

Allagui B., Marouani I., Hadj Abdallah H. Optimal Placement of Phasor Measurement Units by Genetic Algorithm. Int J Energy Power Eng. 2013;2(1):12-17. doi: 10.11648/j.ijepe.20130201.12

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@article{10.11648/j.ijepe.20130201.12,
  author = {Allagui B. and Marouani I. and Hadj Abdallah H.},
  title = {Optimal Placement of Phasor Measurement Units by Genetic Algorithm},
  journal = {International Journal of Energy and Power Engineering},
  volume = {2},
  number = {1},
  pages = {12-17},
  doi = {10.11648/j.ijepe.20130201.12},
  url = {https://doi.org/10.11648/j.ijepe.20130201.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20130201.12},
  abstract = {Monitoring and supervision of power systems are provided by the control center, whose role is the design, coordination and network management. This paper presents a control technique based on the implantation of measurement units at the network buses. This technique should meet two requirements: ensure the complete system observability and find the optimal locations of PMUs with the minimum cost. The problem was formulated as a mono-objective optimization problem and its resolution was made by implementing a genetic algorithm (GA). The proposed method is tested on three tests networks and the results are compared with other resolution techniques. The simulation results ensure the complete system observability and validate the presented technique.},
 year = {2013}
}

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TY  - JOUR
T1  - Optimal Placement of Phasor Measurement Units by Genetic Algorithm
AU  - Allagui B.
AU  - Marouani I.
AU  - Hadj Abdallah H.
Y1  - 2013/02/20
PY  - 2013
N1  - https://doi.org/10.11648/j.ijepe.20130201.12
DO  - 10.11648/j.ijepe.20130201.12
T2  - International Journal of Energy and Power Engineering
JF  - International Journal of Energy and Power Engineering
JO  - International Journal of Energy and Power Engineering
SP  - 12
EP  - 17
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20130201.12
AB  - Monitoring and supervision of power systems are provided by the control center, whose role is the design, coordination and network management. This paper presents a control technique based on the implantation of measurement units at the network buses. This technique should meet two requirements: ensure the complete system observability and find the optimal locations of PMUs with the minimum cost. The problem was formulated as a mono-objective optimization problem and its resolution was made by implementing a genetic algorithm (GA). The proposed method is tested on three tests networks and the results are compared with other resolution techniques. The simulation results ensure the complete system observability and validate the presented technique.
VL  - 2
IS  - 1
ER  -

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Author Information

Allagui B.

ENIS, Dép. Génie Electrique
Marouani I.

ENIS, Dép. Génie Electrique
Hadj Abdallah H.

ENIS, Dép. Génie Electrique

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APA Style

Allagui B., Marouani I., Hadj Abdallah H. (2013). Optimal Placement of Phasor Measurement Units by Genetic Algorithm. International Journal of Energy and Power Engineering, 2(1), 12-17. https://doi.org/10.11648/j.ijepe.20130201.12

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ACS Style

Allagui B.; Marouani I.; Hadj Abdallah H. Optimal Placement of Phasor Measurement Units by Genetic Algorithm. Int. J. Energy Power Eng. 2013, 2(1), 12-17. doi: 10.11648/j.ijepe.20130201.12

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AMA Style

Allagui B., Marouani I., Hadj Abdallah H. Optimal Placement of Phasor Measurement Units by Genetic Algorithm. Int J Energy Power Eng. 2013;2(1):12-17. doi: 10.11648/j.ijepe.20130201.12

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@article{10.11648/j.ijepe.20130201.12,
  author = {Allagui B. and Marouani I. and Hadj Abdallah H.},
  title = {Optimal Placement of Phasor Measurement Units by Genetic Algorithm},
  journal = {International Journal of Energy and Power Engineering},
  volume = {2},
  number = {1},
  pages = {12-17},
  doi = {10.11648/j.ijepe.20130201.12},
  url = {https://doi.org/10.11648/j.ijepe.20130201.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20130201.12},
  abstract = {Monitoring and supervision of power systems are provided by the control center, whose role is the design, coordination and network management. This paper presents a control technique based on the implantation of measurement units at the network buses. This technique should meet two requirements: ensure the complete system observability and find the optimal locations of PMUs with the minimum cost. The problem was formulated as a mono-objective optimization problem and its resolution was made by implementing a genetic algorithm (GA). The proposed method is tested on three tests networks and the results are compared with other resolution techniques. The simulation results ensure the complete system observability and validate the presented technique.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Optimal Placement of Phasor Measurement Units by Genetic Algorithm
AU  - Allagui B.
AU  - Marouani I.
AU  - Hadj Abdallah H.
Y1  - 2013/02/20
PY  - 2013
N1  - https://doi.org/10.11648/j.ijepe.20130201.12
DO  - 10.11648/j.ijepe.20130201.12
T2  - International Journal of Energy and Power Engineering
JF  - International Journal of Energy and Power Engineering
JO  - International Journal of Energy and Power Engineering
SP  - 12
EP  - 17
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20130201.12
AB  - Monitoring and supervision of power systems are provided by the control center, whose role is the design, coordination and network management. This paper presents a control technique based on the implantation of measurement units at the network buses. This technique should meet two requirements: ensure the complete system observability and find the optimal locations of PMUs with the minimum cost. The problem was formulated as a mono-objective optimization problem and its resolution was made by implementing a genetic algorithm (GA). The proposed method is tested on three tests networks and the results are compared with other resolution techniques. The simulation results ensure the complete system observability and validate the presented technique.
VL  - 2
IS  - 1
ER  -

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