Fuzzy Control pp 387-396 | Cite as

Fuzzy Modeling of Uncertainty in a Decision Support System for Electric Power System Planning

  • Izebe O. Egwaikhide
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 6)


This paper reports on the specification of a fuzzy logic based knowledge modeling concept for the development of a decision support system (DSS) christened “Power System Outage-plan Validator” (PSOV), which is expected to assist utility engineers in the medium-term outage planning of the Nigerian Electric Power System (NEPS). The object-oriented (OO) development concept for PSOV is tailored to facilitate intemet/web-enabled interactive decision making in the medium-term (yearly) generation outage planning process of an increasingly deregulated power market, with new stakeholders and structural components. The varying types of uncertainties, ambiguities and contradictions in the semi-structured problem domain necessitate a robust modeling system for knowledge analysis and user interface development, which fuzzy logic provides.


Membership Function Fuzzy Logic Unify Modeling Language Power Generation Unit Outage Planning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Arlow, J.: Literate Modeling: Capturing Business Knowledge with the UML. In: Proc. The Unified Modeling Language, UML’98, Lecture Notes in Computer Science (LNCS), Vol. 1618. Springer-Verlag, Heildelberg (1998)Google Scholar
  2. 2.
    Arroyo-Figueroa, G., et al.: SADEP–A Fuzzy Diagnostic System Shell–an Application to Fossil Power Plant Operation. Expert Systems with Applications 14 (1998) 43–52CrossRefGoogle Scholar
  3. 3.
    Bretthauer, G., et al.: RESEDA — A Program Package for Securing a given Security of Supply in Electric Power Generation Systems. Energietechnik 39 (1989) 289–292 (in German)Google Scholar
  4. 4.
    Dillon, T.S., Chang, E.: Solution of Power System Problems through the Use of the Object-Oriented Paradigm. International Journal of Electrical Power & Energy Systems 16 (1994) 157–165CrossRefGoogle Scholar
  5. 5.
    Egwaikhide, I.O.: COOKADLC: An Introduction: URL: http://cookadlc.homepage.com/Google Scholar
  6. 6.
    Egwaikhide, I.O.: Specification of the NEPS as a Model for the Simulation and Test of a KBS for Maintenance Scheduling. Research Report, Institute of Automatic Control, TU B.A. Freiberg, Germany (1996)Google Scholar
  7. 7.
    Felice, P.-D.: Why Engineering Software is not Reusable: Empirical Data from an Experiment. Advances in Engineering Software 29 (1998) 151–163CrossRefGoogle Scholar
  8. 8.
    Handschin, E., et al.: Coordination of the Long- and Mid-Term Electric Power Generation System Operation Plans with Fuzzy Logic. Elektrizitätswirtschaft 93 (1994) 204–210 (in German)Google Scholar
  9. 9.
    Harmelen, F.V., Fensel, D.: Formal Methods in Knowledge Engineering. The Knowledge Engineering Review 10 (1995) 345–360CrossRefGoogle Scholar
  10. 10.
    Hendricks, P.: Envisioning Knowledge-based Systems Impacts: A GroupWare facilitated Simulation Approach. Expert Systems with Applications 15 (1998) 143–154CrossRefGoogle Scholar
  11. 11.
    IEC Homepage: URL: http://www.iec.ch/Google Scholar
  12. 12.
    ISO Homepage: URL: http://www.iso.ch/Google Scholar
  13. 13.
    Kunnathur, A.S., et al.: Expert Systems Adoption: An analytical Study of Managerial Issues and Concerns. Information & Management 30 (1996) 15–25CrossRefGoogle Scholar
  14. 14.
    Kruse, R., et al.: Foundations of Fuzzy Systems. Teubner, Stuttgart (1994)Google Scholar
  15. 15.
    Lieberman, H.: Integrating User Interface Agents with Conventional Applications: In: Proc. of the Int. Conference on Intelligent User Interfaces, San Francisco, (1990)Google Scholar
  16. 16.
    Merrill, H.M., Wood, A.J.: Risk and Uncertainty in Power System Planning. Electric Power & Energy Systems 13 (1991) 81–90CrossRefGoogle Scholar
  17. 17.
    Neumann, U., Handschin, E., Bretthauer, G., et. al.: Computer Aided Planning System in Electric Power Systems. VDI Report, No. 1252. (1996) 213–222 (in German)Google Scholar
  18. 18.
    Newell, A. The Knowledge Level. Artificial Intelligence, Vol. 18. (1982) 87–127CrossRefGoogle Scholar
  19. 19.
    Nwana, H. S., Ndumu, D.T.: A Perspective on Software Agents Research. The Knowledge Engineering Review 14 (1999) 1–18CrossRefGoogle Scholar
  20. 20.
    Nwana, H. S.: Software Agents: An Overview. Knowledge Engineering Review 11 (1996) 1–40CrossRefGoogle Scholar
  21. 21.
    OECD (Ed.): Application of Competition to the Electricity Sector. Report OCDE/GD(97)132, Paris (1997)Google Scholar
  22. 22.
    OMG Task Force on UML, Homepage: URL: http://uml.shl.com/Google Scholar
  23. 23.
    Rahimi, F.A., Vojdani, A.: Meet the Emerging Transmission Market Segments. IEEE Computer Applications in Power 12 (1999)Google Scholar
  24. 24.
    Schreiber, S. Th., et al.: Knowledge Engineering and Management: The CommonKADS Methodology. The MIT Press, Massachusetts (1999)Google Scholar
  25. 25.
    Si1er, W.: Building Fuzzy Expert Systems: URL: http://members.aol.com/wsiler/Google Scholar
  26. 26.
    Studer, R. et al.: Knowledge Engineering: Survey and Future Directions. In: Puppe, F. (ed.): Proc. of the 5th German Conference on Knowledge-based Systems, Lecture Notes in Artificial Intelligence (LNAI), Vol. 1570. Springer-Verlag, Heidelberg (1999)Google Scholar
  27. 27.
    Sun Microsystems Inc.: JAVA Homepage: URL: http://java.sun.com/Google Scholar
  28. 28.
    Turban, E.: Decision Support and Expert Systems: Management Support Systems. Macmillan Publishing Company, New York (1993)Google Scholar
  29. 29.
    UML Resource Center: Rational Software: URL: http://rational.com/uml/Google Scholar
  30. 30.
    Utesch, M., Egwaikhide, I.O., Bretthauer, G.: Application of Genetic Algorithms for the Query Optimization in the Data Management of a KBS. In: Proc. of the 42. Int. Scientific Colloquium, TU Ilmenau, Ilmenau (1997) 359–364 (in German)Google Scholar
  31. 31.
    Varga, L.Z., Jennings N. R., Cockburn, D.: Integrating Intelligent Systems into a Cooperating Community for Electricity Distribution Management. Expert Systems With Applications 7 (1994) 563–579CrossRefGoogle Scholar
  32. 32.
    Verstege, J., et al.: Liberalization of the Power Supply–Effects on Planning and Optimization Tasks, VDI Reports, No. 1352 (1997) 9–24 (in German)Google Scholar
  33. 33.
    Wooldridge, M., Jennings, N. R.: Pitfalls of Agent-Oriented Development. In: Proc. 2 Int. Conf. On Autonomous Agents (Agents-98), Mineapolis, USA, (1998) 385–391CrossRefGoogle Scholar
  34. 34.
    Zadeh, L.A.: Fuzzy Sets. In: Information and Control, 8 (1965) 333–353Google Scholar
  35. 35.
    Zadeh, L.A.: The Role of Fuzzy Logic in the Management of Uncertainty in Expert Systems. Fuzzy Sets and Systems 11 (1983) 199–227MathSciNetMATHCrossRefGoogle Scholar
  36. 36.
    Zadeh, L.A.: Is Probability Theory sufficient for dealing with Uncertainty in AI: A negative View. In: Kanal, L.N and Lemmer, J. F. (eds.): Uncertainty in AI. Amsterdam (1986)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Izebe O. Egwaikhide
    • 1
  1. 1.Institute of Applied Informatics (IAI)Forschungszentrum Karlsruhe GmbHKarlsruheGermany

Personalised recommendations