Skip to main content

Part of the book series: Power Systems ((POWSYS))

  • 100 Accesses

Abstract

This chapter introduces the areas of computational intelligence and agent technologies for the application within autonomous systems. The key topic is the modeling of knowledge to establish intelligent behavior of an autonomous component, which also can be described and implemented as an agent.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Poole D, Mackworth A, Goebel R (1998) Computational Intelligence: a logical approach. Oxford University Press Inc., New York

    MATH  Google Scholar 

  2. McDonald JR, McArthur S, Burt G, Zielinski J (1997) Intelligent Knowledge Based Systems in Electrical Power Engineering. Kluwer Academic Publishers, Boston

    Book  Google Scholar 

  3. Madan S, Bollinger KE (1997) Applications of artificial intelligence in power systems. Electric Power Systems Research, Elsevier, no 41, pp 117–131

    Google Scholar 

  4. Dahhaghchi I, Christie RD, Rosenwald GW, Liu CC (1997) AI application areas in power systems. IEEE Intelligent Systems & Their Applications, vol 12, no 1, pp 58–66

    Google Scholar 

  5. Liu CC, Pierce DA, Song H (1997) Intelligent system applications to power systems. IEEE Computer Applications in Power, vol 10, no 4, pp 21–24

    Article  Google Scholar 

  6. Bann J, Irisarri G, Kirschen D, Miller B, Mokhtari S (1996) Integration of Artificial Intelligence Applications in the EMS: Issues and Solutions. IEEE Transactions on Power Systems, vol 11, no 1, pp 475–482

    Article  Google Scholar 

  7. Dillon TS, Niebur D (1996) Neural Networks Applications in Power Systems. CRL Publishing, Leics

    Google Scholar 

  8. Lai LL (1998) Intelligent system applications in power engineering: evolutionary programming and neural networks. John Wiley & Sons, Chichester

    Google Scholar 

  9. King RL (1998) Artificial neural networks and computational intelligence. IEEE Computer Applications in Power, vol 11, no 4, pp 14–16

    Article  Google Scholar 

  10. Aggarwal R, Song Y (1997) Artificial neural networks in power systems. I. General introduction to neural computing. Power Engineering Journal, IEE, vol 11, no 3, pp 129–134

    Article  Google Scholar 

  11. Aggarwal R, Song Y (1998) Artificial neural networks in power systems. II. Types of artificial neural networks. Power Engineering Journal, IEE, vol 12, no 1, pp 41–47

    Article  Google Scholar 

  12. Aggarwal R, Song Y (1998) Artificial neural networks in power systems. III. Examples of applications in power systems. Power Engineering Journal, IEE, vol 12, no 6, pp 279–287

    Article  Google Scholar 

  13. Wehenkel LA (1998) Automatic Learning Techniques in Power Systems. Kluwer Academic Publishers, Dordrecht

    Book  MATH  Google Scholar 

  14. Kohonen T (1984) Self-Organization and Assoziative Memory. Springer-Verlag, Berlin

    Google Scholar 

  15. Kohonen T (1995) Self-Organizing Maps. Springer-Verlag, Berlin

    Book  Google Scholar 

  16. Song Y, Johns AT (1997) Applications of fuzzy logic in power systems. I. General introduction to fuzzy logic. Power Engineering Journal, IEE, vol 11, no 5, pp 219–222

    Article  Google Scholar 

  17. Song Y, Johns AT(1998) Application of fuzzy logic in power systems. II. Comparison and integration with expert systems, neural networks and genetic algorithms. Power Engineering Journal, IEE, vol 12, no 4, pp 185–190

    Google Scholar 

  18. Song Y, Johns AT (1999) Applications of fuzzy logic in power systems. III. Example applications. Power Engineering Journal, IEE, vol 13, no 2, pp 97–103

    Article  Google Scholar 

  19. Sarfi RJ, Salama MMA, Chikhani AY (1996) Applications of fuzzy sets theory in power systems planning and operation: a critical review to assist in implementation. Electric Power Systems Research, Elsevier, vol 39, no 2, pp 89–101

    Google Scholar 

  20. Srinivasan D, Liew AC, Chang CS (1995) Applications of fuzzy systems in power systems. Electric Power Systems Research, Elsevier, vol 35, no 1, pp 39–43

    Google Scholar 

  21. Momoh JA, Ma XW, Tomsovic K (1995) Overview and literature survey of fuzzy set theory in power systems. IEEE Transactions on Power Systems, vol 10, no 3, pp 1676–1690

    Article  Google Scholar 

  22. Dillon TS, Laughton MA (1990) Expert System Applications in Power Systems. Prentice Hall International

    Google Scholar 

  23. Germond A, Fink L, Bretthauer G, Wollenberg BF, Liu CC (1993) Exploring user requirements of expert systems in power system operation and control. Electra, no 146, pp 68–83

    Google Scholar 

  24. Bretthauer G, Handschin E, Hoffmann W (1992) Expert systems application to power systems-state-of-the-art and future trends. Control of Power Plants and Power Systems, Selected Papers from the IFAC Symposium, Pergamon, Oxford, pp 463–468

    Google Scholar 

  25. Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison Wesley

    Google Scholar 

  26. Schwefel HP (1995) Evolutionary and Optimum Seeking. John Wiley & Sons, Inc., New York

    Google Scholar 

  27. Miranda V, Srinivasan D, Proenca LM (1998) Evolutionary computation in power systems. International Journal of Electrical Power & Energy Systems, Elsevier, vol 20, no 2, pp 89–98

    Google Scholar 

  28. Yao X (1999) Evolving Artificial Neural Networks. IEEE Proceedings, vol 87, no 9

    Google Scholar 

  29. Kiendl H (1998) Self-Organizing Adaptive Moment-Based Clustering. IEEE International Conference on Fuzzy Systems, Anchorage, Alaska, IEEE Press, Piscataway, NJ, vol 2, pp 1470–1475

    Google Scholar 

  30. Martinetz T, Schulten K (1991) A ‘neural gas’ network learns topologies. in Kohonen T, et al, Artificial Neural Networks, North Holland, Amsterdam, vol I, pp 397–402

    Google Scholar 

  31. Fritzke B (1995) A growing neural gas network learns topologies. Advances in Neural Information Processing Systems 7, MIT Press, Cambridge

    Google Scholar 

  32. Shafer G (1976) A mathematical theory of evidence. Princeton Univ. Press, London

    MATH  Google Scholar 

  33. Dempster A (1967) Upper and lower probabilities induced by a multivalued mapping. Annals of Mathematical Statistics, vol 38, pp 325–339

    Article  MathSciNet  MATH  Google Scholar 

  34. Woolrigde M (2002) Introduction to Multiagent Systems. John Wiley & Sons

    Google Scholar 

  35. Weiss G (2000) Mutliagent Systems: A Modern Approach to Distributed Artificial Intelligence. MIT Press

    Google Scholar 

  36. Stephens LM, Huhns MN (2000) Multiagent Systems and Societies of Agents. in Weiss G, Mutliagent Systems: A Modern Approach to Distributed Artificial Intelligence. MIT Press, pp 79–120

    Google Scholar 

  37. Haddadi A (1995) Towards a Pragmatic Theory of Interactions. Proceeding of International Conference on Multiagent Systems, San Francisco

    Google Scholar 

  38. Rosenschein JS, Zlotkin G (1994) Designing Conventions for Automated Negotiation. AI Magazine, pp 29–46

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Rehtanz, C. (2003). Computational Intelligence and Agent Technologies for Autonomous Systems. In: Autonomous Systems and Intelligent Agents in Power System Control and Operation. Power Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05955-5_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-05955-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-07290-1

  • Online ISBN: 978-3-662-05955-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics