Advertisement

Metaheuristics Applied to Power Systems

  • Manuel A. Matos
  • M. Teresa Ponce de Leão
  • J. Tomé Saraiva
  • J. Nuno Fidalgo
  • Vladimiro Miranda
  • J. Peças Lopes
  • J. Rui Ferreira
  • Jorge M. C. Pereira
  • L. Miguel Proença
  • J. Luís Pinto
Part of the Applied Optimization book series (APOP, volume 86)

Abstract

Most optimization and decision problems in power systems include integer or binary variables, leading to combinatorial problems. In this paper, several approaches using metaheuristics and genetic algorithms are presented that deal with real problems of the power industry. Most of these methodologies are now implemented in distribution management systems (DMS) used by several utilities.

Keywords

Metaheuristics Power systems Simulated annealing Genetic algorithms. 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. J. R. Ferreira. Voltage stability evaluation considering fuzzy injection scenarios and identification of control procedures (in Portuguese). PhD thesis, University of Porto, 1999.Google Scholar
  2. J. N. Fidalgo. Feature selection based on ANN sensitivity analysis — A practical study. In International Conference on Neural Networks and Applications WSES2001February 2001.Google Scholar
  3. S. Granville, J. C. O. Mello, and A. C. G. Melo. Application of interior point methods to power flow unsolvability. IEEE Transactions on PWRS, 11 (1), February 1996.Google Scholar
  4. P. S. Hang. Evolutionary computing and fuzzy logic applied to generation scheduling in systems with renewables. Master’s thesis, University of Porto, December 1999.Google Scholar
  5. C. Lemâitre, J. P. Paul, J. M. Tesseron, Y. Harmand, and Y. S. Zhao. An indicator of the risk of voltage profile instability for real-time control applications. In IEEE/PES Summer Meeting. IEEE/PES, 1989.Google Scholar
  6. S. Mahfoud. Niching methods for genetic algorithms. PhD thesis, University of Illinois at Urbana-Champaign, 1995.Google Scholar
  7. M. Matos and P. Melo. Multi-objective reconfiguration for loss reduction and service restoration using simulated annealing. In Proceedings of IEEE Budapest Power Tech’99. IEEE, August 1999. Google Scholar
  8. J. A. Peças Lopes. On-line dynamic security assessment of isolated networks integrating large wind power production. Wind Engineering Review, 23 (2), 1999.Google Scholar
  9. Jorge Pereira, J. Tomé Saraiva, and M. T. Ponce de Leâo. Identification of operation strategies of distribution networks using a simulated annealing approach. In Proceedings of the IEEE Budapest Power Tech’99. IEEE, August 1999.Google Scholar
  10. M. T. Ponce de Leâo and M. Matos. Multicriteria distribution network planning using simulated annealing. International Transactions on Operational Research, 6: 377–391, 1999.CrossRefGoogle Scholar
  11. F. Resende. Optimization of the electrical internal network of wind farms. Master’s thesis, University of Porto, December 1999. In Portuguese.Google Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Manuel A. Matos
    • 1
    • 2
  • M. Teresa Ponce de Leão
    • 1
    • 2
  • J. Tomé Saraiva
    • 1
    • 2
  • J. Nuno Fidalgo
    • 1
    • 2
  • Vladimiro Miranda
    • 1
    • 2
  • J. Peças Lopes
    • 1
    • 2
  • J. Rui Ferreira
    • 1
    • 2
  • Jorge M. C. Pereira
    • 3
    • 2
  • L. Miguel Proença
    • 2
  • J. Luís Pinto
    • 2
  1. 1.FEUP — Faculty of EngineeringUniversity of PortoPortoPortugal
  2. 2.INESC PortoPower Systems UnitPortoPortugal
  3. 3.FEP — Faculty of EconomicsUniversity of PortoPortoPortugal

Personalised recommendations