PDF Печать E-mail

MULTICRITERIA POWER ENGINEERING PROBLEMS AND FUZZY SET BASED METHODS OF THEIR SOLUTION

Journal Tekhnichna elektrodynamika
Publisher Institute of Electrodynamics National Academy of Science of Ukraine
ISSN 1607-7970 (print), 2218-1903 (online)
Issue № 6, 2014 (November/December)
Pages 60 – 69

 

Authors
P.Ya. Ekel1,2, I.V. Kokshenev1,2, R.O. Parreiras1,2, G.B. Alves2,3, J.G. Pereira Jr.3, P.M.N. Souza4
1 – Graduate Program in Electrical Engineering, Pontifical Catholic University of Minas Gerais,
e-mail: Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript
2 – Advanced System Optimization Technologies, Belo Horizonte, Brazil
3 – Graduate Program in Electrical Engineering, Federal University of Minas Gerais
4 – Administration of Relationship Centers, CEMIG Distribution, Belo Horizonte, Brazil.

 

Abstract

The results of research into the use of models and methods of multicriteria decision making in a fuzzy environment for solving power engineering problems are presented. Two general classes of models related to multiobjective ( models) and multiattribute ( models) problems as well as methods of their analysis based on the application of the Bellman-Zadeh approach to decision making in a fuzzy environment and techniques of fuzzy preference modeling, respectively, are briefly considered. A review of the authors’ results associated with the application of these models and methods for solving diverse types of problems of power system and subsystems planning, operation, and control is presented. The recent results on the use of and models and methods of their analysis for the allocation of reactive power sources in distribution systems and for the prioritization in maintenance planning in distribution systems, respectively, are considered. References 35, table 1.

 

Key words: electromechanical propulsion performance characteristics, coaxial-linear motor, constant magnets, magnet bracket.

 

Received:     30.01.2014
Accepted:     13.03.2014
Published:   10.11.2014

 

References

1. Popov V.A., Ekel P.Ya. Fuzzy set theory and problems of controlling the design and operation of electric power systems // Proceedings of the Academy of Sciences of USSR. Technical Cybernetics. – 1986. – Vol. 25. – № 4. – Pp. 143–157. (Rus)
2. Zimmermann H.J. Fuzzy Set Theory and Its Applications. – Boston: Kluwer Academic Publishers, 1990.
3. Pedrycz W., Gomide F. An Introduction to Fuzzy Sets: Analysis and Design. – Cambridge, MA: MIT Press, 1998.
4. Ekel P.Ya. Methods of Decision making in fuzzy environment and their applications // Nonlinear Analysis: Theory, Methods and Applications. – 2001. – Vol. 47. – № 5. – Pp. 979–990.
5. Pedrycz W., Ekel P., Parreiras R. Fuzzy Multicriteria Decision-Making: Models, Methods, and Applications. – New York, NY: John Wiley & Sons, 2011.
6. Larichev O.I. Psychological validation of decision methods // Journal of Applied System Analysis. – 1984. – Vol. 11. – № 1. – Pp. 37–46.
7. Ekel P.Ya. Fuzzy sets and models of decision making // Computers and Mathematics with Applications. – 2002. – Vol. 44. – № 7. – Pp. 863–875.
8. Pareto V. Cours d’Economie Politique. – Lousanne: Lousanne Rouge, 1886.
9. Rao S. Engineering Optimization: Theory and Practice. – New York, NY: John Wiley & Sons, 1996.
10. Ehrgott M. Multicriteria Optimization. – Berlin: Springer-Verlag, 2005.
11. Ekel P.Ya., Galperin E.A. Box-triangular multiobjective linear programs for resource allocation with application to load management and energy market problems // Mathematical and Computer Modelling. – 2003. – Vol. 37. – № 1. – Pp. 1–17.
12. Ekel P., Menezes M., Schuffner Neto F. Decision making in fuzzy environment and its application to power engineering problems // Nonlinear Analysis: Hybrid Systems. – 2007. – Vol. 1. – № 4. – Pp. 527– 536.
13. Bellman R.E., Zadeh L.A. Decision-making in a fuzzy environment // Management Science. – 1970. – Vol. 17. – № 1. – Pp. 141–164.
14. Sklyarov V.F., Prakhovnik A.V., Ekel P.Ya. On the multicriteria power consumption control // Electronic Modeling. – 1987. – Vol. 9. – № 5. – Pp. 61–65. (Rus)
15. Ekel P.Ya., Terra L.D.B., Junges M.F.D., Prakhovnik A.V., Razumovsky O.V. Multicriteria load management in power systems // in Proceedings of the IEEE and IEE International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. – London, 2000. – Pp. 167–172.
16. Prakhovnik A.V., Nakhodov V.F., Ekel P.Ya., Sklyarov V.F., Voitov V.L., Osinskaya E.L. Optimality criteria in problems of power shortage allocation // Power Engineering and Electrification. – 1989. – Vol. 30. – № 4. – Pp. 38–41. (Rus)
17. Berredo R.C., Ekel P.Ya., Martini J.S.C., Palhares R.M., Parreiras R.O., Pereira J.G. Jr. Decision making in fuzzy environment and multicriteria power engineering problems // International Journal of Electric Power and Energy Systems. – 2011. – Vol. 33. – № 3. – Pp. 623–632.
18. Ekel P., Junges M., Kokshenev I., Parreiras R. Sensitivity and functionally oriented models for power system planning, operation, and control // International Journal of Electric Power and Energy Systems. – 2013. – Vol. 45. – № 1. – Pp. 489–500.
19. Ekel P.Ya., Schuffner Neto F.H. Algorithms of discrete optimization and their application to problems with fuzzy coefficients // Information Sciences. – 2006. – Vol. 176. – № 19. – Pp. 2846-2868.
20. Araujo W.J., Berredo R.C., Ekel P.Ya., Palhares R.M. Discrete optimization algorithms and problems of decision making in a fuzzy environment // Nonlinear Analysis: Hybrid Systems. – 2007. – Vol. 1. – № 4. – Pp. 593- 602.
21. Popov V.A., Ekel P.Ya. Application of fuzzy set theory to choosing disconnection locations in electrical distribution networks by several criteria // Tekhnicheskaia Elektrodinamika. – 1983. – Vol. 5. – № 6. – Pp. 50-55. (Rus)
22. Ekel P.Ya., Martini J.S.C., Palhares R.M. Multicriteria analysis in decision making under information uncertainty // Applied Mathematics and Computation. – 2008. – Vol. 200. – № 2. – Pp. 501-516.
23. Fodor J., Roubens M. Fuzzy Preference Modelling and Multicriteria Decision Support. – Boston, MA: Kluwer Academic Publishers, 1994.
24. Ekel P., Pedrycz W., Schinzinger R. A general approach to solving a wide class of fuzzy optimization problems // Fuzzy Sets and Systems. – 1998. – Vol. 97. – № 1. – Pp. 49-66.
25. Zhang Q., Wang Y., Yang Y. Fuzzy multiple attribute decision making with eight types of preference information // in Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Multicrieria Decision Making, Honolulu, 2007. – Pp. 288-293.
26. Orlovsky S.A. Problems of Decision Making with Fuzzy Information. – Moskva: Nauka, 1981. (Rus)
27. Barrett C.R., Patanalk P.K., Salles M. On choosing rationally when preferences are fuzzy // Fuzzy Sets and Systems. – 1990. – Vol. 34. – № 2. – Pp. 197-212.
28. Bouyssou D. Acyclic fuzzy preference and the Orlovski choice function: a note // Fuzzy Sets and Systems. – 1997. – Vol. 89. – № 1. – Pp. 107-111.
29. Yager R.R. On ordered weighted averaging aggregation operators in multi-criteria decision making // IEEE Transactions on Systems, Man and Cybernetics. – 1988. – Vol. 18. – № 2. – Pp. 183-190.
30. Wei-xiang L., Bang-yi L. An extension of the Promethee ii method based on generalized fuzzy numbers // Expert Systems with Applications. – Vol. 37. – № 7. – Pp. 5314-5319.
31. Parreiras R.O., Ekel P.Ya., Martini J.S.C., Palhares R.M. A Flexible consensus scheme for multicriteria group decision making under linguistic assessments // Information Sciences. – 2010. – Vol. 180. – № 7. – Pp. 1075-1089.
32. Parreiras R.O., Ekel P.Ya., Morais D.C. Fuzzy set based consensus schemes for multicriteria group decision making applied to strategic planning // Group Decision and Negotiation. – 2012. – Vol. 21. – № 2. – Pp. 153-183.
33. Parreiras R., Ekel P., Bernandes F. Jr. A dynamic consensus scheme based on a nonreciprocal fuzzy preference relation modeling // Information Sciences. – 2012. – Vol. 211. – № 1. – Pp. 1-17.
34. Fontoura Filho R.N., Ales J.C.O., Tortelly D.L.S. Uncertainty models applied to the substation planning // 4th International Conference on Probabilistic Methods Applied to Power Systems, Rio de Janeiro, 1994.
35. Beccali M., Cellura M., Ardente D. Decision making in energy planning: The ELECTRE multicriteria analysis approach compared to a fuzzy-sets methodology // Energy Conversion and Management. – 1998. – Vol. 39. – № 16-18. – Pp. 1869-1881.