Abstract
This paper proposes a novel environmental/economic load dispatch model by considering the fuel cost and emissionfunctions with uncertain co-efficients and the constraints of a ramp rate. The uncertain coefficients are represented by fuzzy numbers, and the model is known as fuzzy dynamic environmental/economic load dispatch (FDEELD) model. A novel weighted ideal point method (WIPM) is developed to solve the FDEELD problem. The FDEELD problem is first converted into a single objective fuzzy nonlinear programming by using the WIPM. A hybrid evolutionary algorithm with quasi-simplex techniques is then used to solve the corresponding single objective optimization problem. A method of disposing constraint and a fuzzy number ranking method are also applied to compare fuzzy weighted objective function values of different points. Experimental results show that FDEELD model is more practical; the algorithm and techniques proposed are efficient to solve FDEELD problems.
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References
Abido, M.A.: Environmental/economic power dispatch using multiobjective evolutionary algorithms. IEEE Transactions on Power Systems 18(4), 1529–1537 (2003)
Venkatesh, P., Gnanadass, R., Padhy, N.P.: Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints. IEEE Transactions on Power Systems 18(2), 688–697 (2003)
Rughooputh, H.C.S., Ah King, R.T.F.: Environmental/economic dispatch of thermal units using an elitist multiobjective evolutionary algorithm. In: 2003 IEEE International Conference on Industrial Technology, vol. 1, pp. 48–53 (2003)
Kiyota, T., Tsuji, Y., Kondo, E.: Unsatisfying functions and multiobjective fuzzy satisfaction design using genetic algorithms. IEEE Transactions on Systems, Man and Cybernetics, Part B 33(6), 889–897 (2003)
Wang, K.P., Yuryevich, J.: Evolutionary programming based algorithm for environmentally constrained economic dispatch. IEEE Transactions on Power Systems 13(2), 301–306 (1998)
Huang, C.-M., Yang, H.-T., Huang, C.-L.: Bi-objective power dispatch using fuzzy satisfaction-maximizing decision approach. IEEE Transactions on Power Systems 12(4), 1715–1721 (1997)
Watts, D., Atienza, P., Rudnick, H.: Application of the Power Exchange-Independent System Operator Model in Chile. In: Power Engineering Society Summer Meeting, 2002 IEEE, vol. 3, pp. 1392–1396 (2002)
Wen, F., David, A.K.: Coordination of bidding strategies in day-ahead energy and spinning reserve markets. International Journal of Electrical Power & Energy Systems 24(4), 251–261 (2002)
Albuyeh, F., Alaywan, Z.: California ISO formation and implementation. IEEE Computer Applications in Power 12(4), 30–34 (1999)
Nelder, J.A., Mead, R.: A simplex method for function minimization. The Computer Journal 5 (1965)
Zhang, G., Wu, Y.-H., Remias, M., Lu, J.: Formulation of fuzzy linear programming problems as four-objective constrained optimization problems. Applied Mathematics and Computation 139(2-3), 383–399 (2003)
Lee, E.S., Li, R.L.: Comparison of fuzzy numbers based on the probability measure of fuzzy events. Comput. Math. Appl. 15, 887–896 (1988)
Cheng, C.-H.: A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets and Systems 95(3), 307–317 (1998)
Tran, L., Duckstein, L.: Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Sets and Systems 130(3), 331–341 (2002)
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhang, Gl., Li, Gy., Xie, H., Ma, Jw. (2006). Application of Weighted Ideal Point Method to Environmental/Economic Load Dispatch. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_46
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DOI: https://doi.org/10.1007/11739685_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
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