Skip to main content
SpringerLink
Log in

Non-conventional Overcurrent Relays Coordination

  • Chapter
  • First Online:
Metaheuristics Algorithms in Power Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 822))

Abstract

The Invasive Weed Optimization (IWO) algorithm has been adapted for the high dimension coordination problem. Many utilities follow the criterion of increase use of differential protection in transmission lines which has absolute selectivity with no backup function offered.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. M. Affenzeller, S. Winkler, S. Wagner, A. Beham, Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications, 1st edn. (Chapman & Hall/CRC, London, UK, 2009)

    Book  Google Scholar 

  2. J.H. Holland, Adaptation in Natural and Artificial Systems, 2nd edn. (MITPress, Cambridge, USA, 1992)

    Book  Google Scholar 

  3. M. Mitchell, An Introduction to Genetic Algorithms, 5th edn. (MIT Press, Cambridge, USA, 1999)

    MATH  Google Scholar 

  4. J. Bronowski, The Ascent of Man (British Broadcasting Corporation, London, UK, 1973)

    Google Scholar 

  5. C. Darwin, The Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, 6th edn. (John Murray, London, UK, 1859)

    Google Scholar 

  6. A.R. Wallace, My Life; A Record of Events and Opinions, 1st edn. (Chapman & Hall, London, UK, 1905)

    Book  Google Scholar 

  7. M. Gen, R. Cheng, L. Lin, Network Models and Optimization: Multiobjective Genetic Algorithm Approach (Decision Engineering), 1st edn. (Springer, New York, 2008)

    Google Scholar 

  8. D.E. Goldberg, K. Deb, A comparative analysis of selection schemes used in genetic algorithms, in Foundations of Genetic Algorithms, (Morgan Kaufmann, 1991), pp. 69–93

    Google Scholar 

  9. J.E. Baker, Reducing bias and inefficiency in the selection algorithm, in Proceedings of the Second International Conference on Genetic Algorithms on Genetic Algorithms and Their Application, (Erlbaum Associates Inc, New Jersey, USA, 1987), pp. 14–21

    Google Scholar 

  10. A.R. Mehrabian, C. Lucas, A novel numerical optimization algorithm inspired from weed colonization. Ecol. Inform. 1(4), 355–366 (2006)

    Article  Google Scholar 

  11. H.S. Rad, C. Lucas, A recommender system based on invasive weed optimization algorithm, in Proceedings of the IEEE Congress on Evolutionary Computation, Sept 2007, pp. 4297–4304)

    Google Scholar 

  12. H. Josin ́ski, D. Kostrzewa, A. Michalczuk, A. Switonski, The expanded invasive weed optimization metaheuristic for solving continuous and discrete optimization problems. Sci. World J. 2014(1), 1–14 (2006)

    Google Scholar 

  13. H.G. Baker, G.L, Stebbins, International Union of Biological Sciences, in The genetics of colonizing species: Proceedings (Academic Press, New York, USA, 1965)

    Google Scholar 

  14. Y. Zhou, Q. Luo, H. Chen, A novel differential evolution invasive weed optimization algorithm for solving nonlinear equations systems. J. Appl. Math. (4), 1–18 (2013)

    MathSciNet  MATH  Google Scholar 

  15. IEEE Std. C37.113–1999, Guide for protective relay applications to transmission lines (1999)

    Google Scholar 

  16. A.J. Urdaneta, R. Nadira, L.G. Perez, Optimal coordination of directional overcurrent relays in interconnected power systems. IEEE Trans. Power Del. 3(3), 903–911 (1988)

    Article  Google Scholar 

  17. B. Chattopadhyay, M.S. Sachdev, T.S. Sidhu, An online relay coordination algorithm for adaptive protection using linear programming technique. IEEE Trans. Power Del. 11(1), 165–173 (1996)

    Article  Google Scholar 

  18. C. So, K.K. Li, K.T. Lai, K.Y. Fung, Application of genetic algorithm for overcurrent relay coordination, in Sixth International Conference on Developments in Power System Protection 6 (1997), pp. 66–69

    Google Scholar 

  19. F. Razavi, H.A. Abyaneha, M. Al-Dabbagh, R. Mohammadia, H. Torkaman, A new comprehensive genetic algorithm method for optimal overcurrent relays coordination. Electr. Power Syst. Res. 78, 713–720 (2008)

    Article  Google Scholar 

  20. P.P. Bedekar, S.R. Bhide, Optimum coordination of overcurrent relay timing using continuous genetic algorithm. Expert Syst. Appl. 38, 11286–11292 (2011)

    Article  Google Scholar 

  21. P.P. Bedekar, S.R. Bhide, Optimum coordination of directional overcurrent relays using the hybrid GA-NLP approach. IEEE Trans. Power Deliv. 26(1), 109–119 (2011)

    Article  Google Scholar 

  22. M.M. Mansour, S.F. Mekhamer, N.E.-S. El-Kharbawe, A modified particle swarm optimizer for the coordination of directional overcurrent relays. IEEE Trans. Power Del. 22(3), 1400–1410 (2007)

    Article  Google Scholar 

  23. A. Liu, M.-T. Yang, A new hybrid nelder-mead particle swarm optimization for coordination optimization of directional overcurrent relays. Math. Prob. Eng. 2012, Article 456047 (2012)

    Google Scholar 

  24. M.R. Asadi, S.M. Kouhsari, Optimal overcurrent relays coordination using particle-swarm-optimization algorithm, in IEEE Power Systems Conference and Exposition (Seattle, WA, 15–18 Mar 2009), pp. 1–7

    Google Scholar 

  25. A.S. Noghabi, J. Sadeh, H.R. Mashhadi, Considering different network topologies in optimal overcurrent relay coordination using a hybrid GA. IEEE Trans. Power Del. 24(4), 1857–1863 (2009)

    Article  Google Scholar 

  26. A.M. Girjandi, M. Pourfallah, Optimal coordination of overcurrent relays by mixed genetic and particle swarm optimization algorithm and comparison of both, in International Conference on Signal, Image Processing and Applications, vol. 21 (IACSIT Press, Singapore, 2011)

    Google Scholar 

  27. P.P. Bedekar, S.R. Bhide, Optimum coordination of directional overcurrent relays using the hybrid GA-NLP approach. IEEE Trans. Power Del. 26, 109–119 (2011)

    Article  Google Scholar 

  28. M. Ezzeddine, R. Kaczmarek, A novel method for optimal coordination of directional overcurrent relays considering their available discrete settings and several operation characteristics. Electr. Power Syst. Res. 81, 1475–1481 (2011)

    Article  Google Scholar 

  29. Y. Lu, J.-L. Chung, Detecting and solving the coordination curve intersection problem of overcurrent relays in sub-transmission systems with a new method. Electr. Power Syst. Res. 95, 17–27 (2013)

    Article  Google Scholar 

  30. T.R. Chelliah, R. Thangaraj, S. Allamsetty, M. Pant, Application of genetic algorithm for overcurrent relay coordination. Int. J. Electric. Power Energy Syst. 55, 341–350 (2014)

    Article  Google Scholar 

  31. J.L. Blackburn, T.J. Domin, Introduction and general philosophies, in Protective Relaying, Principles and Applications, 3rd edn. (Taylor and Francis Group, LLC, New York, 2006)

    Google Scholar 

  32. S.H. Horowitz, A.G. Phadke, J.S. Thorp, Adaptive transmission system relaying. IEEE Trans. Power Delivery 3, 1436–1445 (1988)

    Article  Google Scholar 

  33. IEEE, IEEE Standard Inverse, Time Characteristic Equations for Over-current Relays, IEEE Std C37.112-1996 (1997), pp. 1–13

    Google Scholar 

  34. IEC Standard 255-4, Single Input Energizing Measuring Relays with Dependent Specified Time, 1st edn. IEC Publication 255-4 (1976)

    Google Scholar 

  35. J. Otamendi, The importance of the objective function definition and evaluation in the performance of the search algorithms, in 16th European Simulation Symposium (2004)

    Google Scholar 

  36. W. Mock, Pareto optimality, in Encyclopedia of Global Justice, ed. by D.K. Chatterjee (Springer, Netherlands, 2011), pp. 808–809

    Chapter  Google Scholar 

  37. K. Chen, Industrial Power Distribution and Illuminating Systems. Electrical and Computer Engineering (Taylor & Francis, New York, USA, 1990)

    Google Scholar 

  38. A.F. Sleva, Protective Relay Principles, 1st edn. (Taylor & Francis, New York, USA, 2009)

    Book  Google Scholar 

  39. K. Schittkowski, NLPQL: a fortran subroutine solving constrained nonlinear programming problems. Ann. Oper. Res. 5(2) (1986)

    Article  MathSciNet  Google Scholar 

  40. P.T. Boggs, J.W. Tolle, Quasi-Newton methods and their application to function minimisation. Acta Numer. 4(1), 1–54 (1995)

    Google Scholar 

  41. P.E. Gill, E. Wong, Sequential quadratic programming methods, in Mixed Integer Nonlinear Programming, vol. 154, Volumes in Mathematics and its Applications, ed. by J. Lee, S. Leyffer (Springer, New York, USA, 2012), pp. 147–224

    Chapter  Google Scholar 

  42. R.B. Wilson, A Simplicial Algorithm for Concave Programming. Ph.D, thesis, Graduate School of Business Administration, Harvard University, Cambridge, USA, 1963

    Google Scholar 

  43. MATLAB, Find minimum of constrained nonlinear multivariable function. http://www.mathworks.com/help/optim/ug/fmincon.html (2015)

  44. MATLAB, Optimization toolbox. http://www.mathworks.com/products/optimization (2015)

  45. MATLAB, Optimization toolbox user’s guide. http://www.mathworks.com/help/pdf_doc/optim/optim_tb.pdf (2015)

  46. MATLAB, The language of technical computing. http://www.mathworks.com/products/optimization/ (2015)

Download references

Author information

Authors and Affiliations

  1. Departamento de Electrónica, CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas

  2. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Emilio Barocio Espejo

  3. Universidad Autónoma de Nuevo León, San Nicolás de los Garza, Nuevo León, Mexico

    Arturo Conde Enríquez

Authors
  1. Erik Cuevas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Emilio Barocio Espejo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arturo Conde Enríquez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Erik Cuevas .

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Cuevas, E., Barocio Espejo, E., Conde Enríquez, A. (2019). Non-conventional Overcurrent Relays Coordination. In: Metaheuristics Algorithms in Power Systems. Studies in Computational Intelligence, vol 822. Springer, Cham. https://doi.org/10.1007/978-3-030-11593-7_3

Download citation

Publish with us

Policies and ethics

Search

Navigation