Abstract
In this paper we present a motivation for using the Truncated Newton methodology and a multiple superbasic activating line search in an algorithm that maximize the hydropower generation in a multi reservoir, multi period power system. The decision variables are the water to be released from and stored in each reservoir in each time period over a given time horizon. The function that relates the hydropower generation to the decision variables has a special structure that allows the use of second-order information without requiring too much computer time and storage.
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References
R.S. Dembo and J.C. Klincewicz, “A scaled reduced gradient algorithm for network flow problems with convex separable costs”, Mathematical Programming 15 (1981) 125–147.
R.S. Dembo, “The design and implementation of algorithms for large-scale nonlinear network optimization”, Yale School of Organization and Management, working paper B-72, 1983.
R.S. Dembo and T. Steihaug, “Truncated-Newton algorithms for large-scale unconstrained optimization”, Mathematical Programming 26 (1983) 190–212.
L.F. Escudero, “On diagonally-preconditioning the Truncated Newton method for super-scale linearly constrained nonlinear programming”, European Journal of Operational Research 17 (1984) 401–414.
B. Murtagh and M. Saunders, “Large-scale linearly constrained optimization”, Mathematical Programming 14 (1978) 41–72.
R.E. Rosenthal, “A nonlinear network flow algorithm for maximization of benefit in a hydroelectric power system”, Operations Research 29 (1981) 763–786.
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© 1986 The Mathematical Programming Society, Inc.
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Escudero, L.F. (1986). A motivation for using the truncated Newton approach in a very large scale nonlinear network problem. In: Gallo, G., Sandi, C. (eds) Netflow at Pisa. Mathematical Programming Studies, vol 26. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0121105
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DOI: https://doi.org/10.1007/BFb0121105
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Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-00923-5
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