This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Parallel Processing Applied to the Planning of Hydrothermal Systems
August 2003 (vol. 14 no. 8)
pp. 721-729

Abstract—The objective of the long-term operating planning problem is to determine the optimum strategy for the generation of electricity, aiming toward the minimization of total operating cost over the planning period. In a competitive electricity market, with the participation of a significant number of hydroplants, such as in Brazil, precision modeling for operating planning is required so that a better use of hydraulic resources can be obtained. Therefore, in this paper, we present a long-term operating planning model based on an individual power plant representation. In order to support the high computational burden, a suitable parallel processing algorithm is proposed.

[1] M.E.P. Maceira, Stochastic Dual Dynamic Programming Applied to the Operating Planning of Hydrothermal Systems with Representation of the Inflows through the Use of Auto-Regressive Models Project NEWAVE Technical Report: CEPEL 237/93, 1993.
[2] N.V. Arvanitidis and J. Rosing, Optimal Operation of Multi-Reservoir Using a Composite Representation IEEE Trans. PAS, vol. 89, no. 2, pp. 327-335, Feb. 1970.
[3] N.V. Arvanitidis and J. Rosing, Composite Representation of Multireservoir Hydroelectric Power System IEEE Trans. PAS, vol. 89, no. 2, pp. 319-326, Feb. 1970.
[4] R.E. Bellman Dynamic Programming. Princeton, N.J.: Princeton Univ. Press, 1957.
[5] R. Bellman, Adaptive Control Processes. Princeton Univ. Press, 1961.
[6] R. Bellman and S. Dreyfus, Applied Dynamic Programming. Princeton Univ. Press, 1962.
[7] R.E. Larson and W.G. Keckler, Applications of Dynamic Programming to the Control of Water Resource Systems Automatica, vol. 5, pp. 15-26, Pergamon Press, 1969.
[8] R.E. Larson, State Increment Dynamic Programming. New York: Am. Elsevier, 1968.
[9] R.E. Larson, A Dynamic Programming Successive Approximations Technique Proc. Joint Automatic Control Conf., June 1968.
[10] A.J. Korsak and R.E. Larson, Convergence Proofs for a Dynamic Programming Successive Approximation Technique Fourth IFAC Congress, June 1969.
[11] R. Bellman and R.E. Kalaba, Quasilinearization and Nonlinear Boundary-Value Problems. New York: Am. Elsevier, 1965.
[12] L.F. Escudero and M.V.F. Pereira, Power Play Goals Int'l OR, OR/MS Today, pp. 42-46, Apr. 2000.
[13] J.F. Benders, Partitioning Procedures for Solving Mixed Variables Programming Problems Numerische Mathematik, vol. 4, pp. 238-252, 1962.
[14] F.B. Hanson, Techniques in Computational Stochastic Dynamic Programming Digital and Control System Techniques and Applications, C.T. Leondes, ed. New York: Academic Press, pp. 103-162, 1996.
[15] J.J. Westman and F.B. Hanson, Nonlinear State Dynamics: Computational Methods and Manufacturing Example Int'l J. Control, vol. 73, pp. 464-480, Apr. 2000.
[16] J.J. Westman and F.B. Hanson, State Dependent Jump Models in Optimal Control Proc. 38th Conf. Decision and Control, pp. 2378-2383, Dec. 1999.
[17] M.V.F. Pereira and L.M.V.G. Pinto, Stochastic Optimization of Multireservoir Hydroelectric System: A Decomposition Approach Water Resources Research, vol. 21, no. 6, pp. 779-792, June 1985.
[18] M.V.F. Pereira, Optimal Scheduling of Hydrothermal Systems An Overview IFAC Electric Energy Systems, pp. 1-9, 1985.
[19] M.V.F. Pereira, Optimal Stochastic Operations of Large Hydroelectric Systems Electrical Power and Energy Systems, vol. 11, no. 3, pp. 161-169, July 1989.
[20] B. Gorenstin, J.P. Costa, and M.V.F. Pereira, Stochastic Optimization of a Hydro-Thermal System IEEE Trans. Power Systems, vol. 7, no. 2, May 1992.
[21] R.P. Sundarraj, S.K. Gnanendran, and J.K. Ho, Distributed Price-Directive Decomposition Applications in Powers Systems Operations IEEE Trans. Power Systems, vol. 10, no. 3, Aug. 1995.
[22] S.W. Otto, S.H. Lederman, and M. Snir, MPI: The Complete Reference. Mass.: MIT Press, 1997.
[23] IBM; OSL Optimization Subroutine Library: Guide and Reference, Release 2.1, Feb. 1995.

Index Terms:
Hydrothermal systems, stochastic optimization, control problems, parallel and distributed processing.
Citation:
Edson Luiz da Silva, Erlon Cristian Finardi, "Parallel Processing Applied to the Planning of Hydrothermal Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 8, pp. 721-729, Aug. 2003, doi:10.1109/TPDS.2003.1225052
Usage of this product signifies your acceptance of the Terms of Use.