Using Fuzzy Arithmetic for Power Flow Analysis with Uncertainty


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/irena.v5i2.12442

Abstract


The uncertainty treatment of power injections is one of the most important problems in load flow studies. One method is called the Fuzzy Load Flow (FLF), where uncertainty of input variables is modeled with fuzzy numbers. In FLF fuzzy numbers are traditionally decomposed in alpha-cuts and interval arithmetic is used. This paper introduces the use of LR fuzzy numbers’ arithmetic and the transformation method for the solution of FLF. This last method counteracts the short-comings of the interval arithmetic. Adequate fuzzy numbers implementations and appropriate fuzzy arithmetic contribute to precision and improve the general outcome. A comparison between three types of fuzzy arithmetic is made. Finally, the approaches presented are applied in a test system.
Copyright © 2017 Praise Worthy Prize - All rights reserved.

Keywords


Fuzzy Load Flow; Load Flow Studies; Fuzzy Arithmetic; Transformation Method

Full Text:

PDF


References


A. Torres, Teoría básica de la probabilidad, Procesos estocásticos (Notas de Clase. Universidad de los Andes. Colombia, 2002. Chapter 1, pp. 2-4).

F. Alvarado, H. Yi, R. Adapa, Uncertainty in power system modeling and computation, Proc. IEEE International Conference on Systems, Man and Cybernetics, October 1992, Vol. 1, pp. 18-21.
http://dx.doi.org/10.1109/icsmc.1992.271535

J.T. Saraiva, N. Fonseca, M.A. Matos, Fuzzy power flow –An AC model addressing correlated data. Proc. 8th International Conference on Probabilistic Methods Applied to Power Systems, 12-16 September 2004, pp. 519-524.

B. Borkowska, Probabilistic load flow, IEEE Transactions Power Apparatus System, Vol. PAS-93, May 1974, pp. 752–759.
http://dx.doi.org/10.1109/tpas.1974.293973

R. N. Allan, M. R. G. Al-Shakarchi, Probabilistic techniques in AC load flow analysis, IEE Proceedings, Vol. 124, February 1977, pp. 154-160.
http://dx.doi.org/10.1049/piee.1977.0027

A. P. Meliopoulos, A. G. Bakirtzis and R. Kovacs, Power system reliability evaluation using stochastic load flows, IEEE Transactions on Power Apparatus & Systems, Vol. 103, No. 5, May 1984, pp. 1084-1091.
http://dx.doi.org/10.1109/tpas.1984.318715

R. N. Allan, A. M. Leite da Silva, Probabilistic load flow using multilinearizations, IEE Proceedings, Vol. 128, No. 5, September 1981, pp. 280–287.
http://dx.doi.org/10.1049/ip-c.1981.0047

T. S. Karatsanis and N. D. Hatziargyriou, Probabilistic constrained load flow based on sensitivity analysis, IEEE Transactions on Power Systems, Vol. 9, No. 4, November 1994, pp. 1853-1860.

S. Chun-Lien, Probabilistic load-flow computation using point estimate method, IEEE Transactions on Power Systems, Vol. 20, No. 4, November 2005, pp. 1843-1851.
http://dx.doi.org/10.1109/tpwrs.2005.857921

V. Miranda, M.A. Matos, Distribution system planning with fuzzy models and techniques, Proc. CIRED 89, Brighton 1989.
http://dx.doi.org/10.1049/ip-c.1989.0057

V. Miranda, M.A. Matos, J.T. Saraiva, Fuzzy load flow – new algorithm incorporating uncertain generation and load representation, Proc. 10th Power Systems Computing Conference, Graz, Austria, 1990, pp. 621-627.

J.T. Saraiva, V. Miranda, M.A. Matos, Generation and load uncertainties incorporated in load flow studies, Proc. MELECON 91, Ljubljana, May 1991.
http://dx.doi.org/10.1109/melcon.1991.162089

V. Miranda, J.T. Saraiva, Fuzzy modeling of power system optimal load flow, IEEE Transactions on Power Systems, Vol. 7, No. 2, May 1992.

J. Hao, L. Shi, G. Xu, Y. Xie, Study on the fuzzy AC power flow model, Proc. 5th World Congress on Intelligent Control and Automation. Hangzhou, P.R. China, June 15-19, 2004, pp. 5092-5096.
http://dx.doi.org/10.1109/wcica.2004.1343689

H. Sun, D.C. Yu, Y. Xie, Application of fuzzy set theory to power flow analysis with uncertain power injections, Proc. IEEE Power Engineering Society Winter Meeting 2000, Vol. 2, 23-27 Jan. 2000, pp. 1191 – 1196.
http://dx.doi.org/10.1109/pesw.2000.850116

A. Dimitrovski, K. Tomsovic, Boundary load flow solutions, IEEE Transactions on Power Systems, Vol. 19, No. 1, February 2003, pp. 348-455.
http://dx.doi.org/10.1109/tpwrs.2003.821469

M. Hanss, A nearly strict fuzzy arithmetic for solving problems with uncertainties, Proc. 19th International Conference of the North American Fuzzy Information Processing Society, Atlanta, USA 2000, pp. 439-443.
http://dx.doi.org/10.1109/nafips.2000.877469

M. Hanss, On using fuzzy arithmetic to solve problems with uncertain model parameters, Proc. Euromech 405 Colloquium, Valenciennes France, November 17-19, 1999, pp. 85-92.

M. Laviolette, J.W. Seaman, The efficacy of fuzzy representations of uncertainty. IEEE Transactions on Fuzzy Systems, Vol. 2, Issue 1, Feb. 1994, pp. 4 –15.

W. Sheridan, Coping with ignorance in the information age, In Sensible Signage (3rd Ed., 2003, The Thinking Person's Portal).

B. Kosko. Fuzziness vs. probability. International Journal of General Systems, vol. 17, no. 1, pp. 211-240, 1990.

W.F. Tinney, C.E. Hart, Power flow solution by Newton’s method, IEEE Transactions on Power Apparatus and Systems PAS-90, 1987.

N.D. Hatziargyriou, T.S. Karakatsanis, Probabilistic load flow for assessment of voltage instability. IEE Proceedings of Generation, Transmission and Distribution. Vol. 145, Issue 2, March 1999, pp. 196 – 202.
http://dx.doi.org/10.1049/ip-gtd:19981695

D. Dubois, H. Prade, Fuzzy sets and systems: theory and applications, Mathematics in Science and Engineering, Vol. 144, Academic Press, New York, 1980.

A. Kaufmann, M. Gupta, Introduction to fuzzy arithmetic (Van Nostrand Reinhold, New York-London, 1980).

G. Klir , Fuzzy arithmetic with requisite constraints, Fuzzy Sets and Systems, Vol. 91, 1997, pp. 165-175.

A. Klimke, An efficient implementation of transformation method of fuzzy arithmetic, Proc. 22nd International Conference of the North American of Fuzzy Information Processing Society, 24-26 July 2003, pp. 468 – 473.
http://dx.doi.org/10.1109/nafips.2003.1226830

W.M. Dong, F.S. Wong, Fuzzy weighted averages and implementation of the extension principle. Fuzzy Sets and Systems, Vol. 21, 1987, pp. 183-189.

L. Zadeh, Fuzzy sets as the basis for a theory of possibility, Fuzzy Sets and Systems, Vol. 1, 1978, pp. 3-28, (Reprinted in Fuzzy Sets and Systems 100, 1999, pp. 9-34).

D. Dubois, H. Prade. Théorie des posibilités: Application à la représentation des connaissances en informatique (Editeur Masson, Paris, 1985).

D. Dubois, H. Prade, Possibility theory, probability theory and multiple-valued logics: A clarification, Annals of Mathematics and Artificial Intelligence Vol 32, 2001, pp. 35-66.

P. M. Anderson , A. A. Fouad, Power System Control and Stability (The Iowa State University Press, Ames, Iowa, 1977).

P.W Sauer, M.A. Pai, Power System Dynamics and Stability (Prentice Hall, New Jersey, 1998. pp. 170–177).


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize