Abstract
Primal-dual interior point method is used to minimize the predispatch generation costs and transmission losses on short-term operation planning of hydrothermal power systems with previously scheduled maneuvers and ramp rate constraints. Despite the efficiency shown by interior point methods for very large-scale problems, they generally perform only reasonably when applied to multiple-dimensional flow problems, the new specialized interior point algorithm performed here, overcomes this disadvantage. This specialization uses the preconditioned conjugated gradient method with an incomplete Cholesky factorization to solve a linear system in each iteration of the algorithm. The preconditioner developed exploring the structure of the problem is fundamental to ensure the efficiency of the method.
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References
Adler, I., Resende, M. G. C., Veiga, G., & Karmarkar, N. (1989). An implementation of Karmarkar’s algorithm for linear programming. Mathematical Programming, 44, 297–335.
ANEEL. (2018). Atlas da energia elétrica no brasil (pp. 1–199).
Benzi, M. (2002). Preconditioning techniques for large linear systems: A survey. Journal of Computational Physics, 182, 418–477.
Bocanegra, S., Campos, F. F., & Oliveira, A. R. L. (2005). Using a hybrid preconditioner for solving large-scale linear systems arising from interior point methods. In International conference on preconditioning techniques for large sparse matrix problems in scientific and industrial applications - SIAM (pp. 2–4).
Bonaert, A. P., El-Abiad, A. H., & Koivo, A. J. (1971). Optimal scheduling of hydrothermal power systems. AIEE Transactions on Power Apparatus and System, 1, 263–271.
Campos, F. F. (1995). Analysis of conjugate gradients type methods for solving linear equations. Ph.D. thesis. PhDthesis.
Carvalho, S., & Oliveira, A. R. L. (2012). Interior point method applied to the predispatch problem of a hydroelectric with scheduled line manipulations. American Journal of Operations Research, 2, 266–271.
Carvalho, S. M. S., & Oliveira, A. R. L. (2015). Interior point methods applied to the predispatch hydroelectric system with simulated modification in the network topology. Magazine IEEE Latin America, 13, 143–149.
Carvalho, S. M. S., Oliveira, A. R. L., Coelho, M. V. (2017). Métodos de pontos interiores aplicados ao problema de pré-despacho do sistema hidroelétrico com manobras e reserva girante. Trends in Applied and Computational Mathematics, 55–67.
Carvalho, M. F., Soares, S., & Ohishi, T. (1988). Optimal active power dispatch by network flow approach. IEEE Transactions on Power Systems, 3(3), 1640–1647.
Castro, J. (2000). A specialized interior-point algorithm for multcommodity network flows. SIAM Journal of Optimization, 10(3), 852–877.
Castro, J. (2015). Interior-point solver for convex separable block-angular problems. Optimization Methods & Software, 11(3), 88–109.
Chiavegato, F. G., Oliveira, A. R. L., Soares, S. (2001). Pré-despacho de sistemas de energia elétrica via relaxa Lagrangeana e métodos de pontos interiores. Anais do XXII Iberian Latin-American Congress on Computational Methods in Engineering – CILAMCE, Campinas SP, CIL110 (pp. 1–24).
Czyzyk, J., Mehrotra, S., Wagner, M., & Wright, S. J. (1999). PCx an interior point code for linear programming. Optimization Methods & Software, 11–2(1–4), 397–430.
de Minas e Energia, M. (2019). Balanço Energético Nacional. 168p, Brasília, DF.
de Minas e Energia., M. (2020). Plano decenal de expansão de energia 2020. Secretaria de Planejamento e Desenvolvimento Energético (pp. 1–345).
do Sistema, O. O. N. (2020). Plano de opera energética. Relatorio PEEN, 2020, 1–26.
Golub, G. H., & Van Loan, F. C. (1989). Matrix computations (2nd ed.). Baltimore: The Johns Hopkins University Press.
Golub, G. H., & Van Loan, F. C. (1996). Matrix computations (3rd ed.). Baltimore: The Johns Hopkins University Press.
Gondzio, J. (1996). Multiple centrality corrections in a primal-dual method for linear programming. Computational Optimization and Applications, 6, 137–156.
Lasdon, L. (1970). Optimization theory for large systems. New York: Macmillan.
Luenberger, D. G. (1984). Linear and nonlinear programming. Reading, MA: Addison-Wesley.
Lustig, I. J., Marsten, R. E., & Shanno, D. F. (1992). On implementing Mehrotra’s predictor-corrector interior point method for linear programming. SIAM Journal on Optimization, 2, 435–449.
Lyra, C., , S. M. S., Oliveira, A. R. L. (2018). Predispatch of hydroelectric power systems with modifications in network topologies. Annals of Operations Research (pp. 1–19). Springer.
Manteuffel, T. (1980). An incomplete factorization technique for positive definite linear systems. Mathematics of Computation, 34, 473–497.
Mehrotra, S. (1992). Implementations of affine scaling methods: Approximate solutions of systems of linear equations using preconditioned conjugate gradient methods. ORSA Journal on Computing, 4, 103–118.
Nepomuceno, L., Oliveira, A. R. L., Ohishi, T., & Soares, S. (2002). Incorporating voltage/reactive representation to short-term generation scheduling models. Proceedings of the 2000 IEEE Power Engineering Society Summer Meeting, 3, 1541–1546.
Oliveira, A. R. L., Lyra, C., Nascimento, M. A. (1991). An interior point method specialized to the \({L}_1\) regression problem. Technical report, DENSIS RT001, FEEC-UNICAMP.
Oliveira, A. R. L., & Probst, R. W. (2005). Métodos de pontos interiores aplicados ao problema de pré-despacho de um sistema hidrotérmico. XXVIII Congresso Nacional de Matemática Aplicada e Computacional, São Paulo, SP.
Oliveira, A. R. L., & Soares, S. (2000). Métodos de pontos interiores para a minimizaç ao das perdas no problema de pré-despacho. XXXII Simpósio Brasileiro de Pesquisa Operacional - SBPO, Viçosa MG.
Oliveira, A. R. L., Soares, S., & Nepomuceno, L. (2005). Short term hydroelectric scheduling combining network flow and interior point approaches. Electrical Power & Energy Systems, 27(2), 91–99.
Resende, M., Veiga, G. (1993). An efficient implementation of a network interior point method. In D. S. Johnson, and C. C. McGeoch, (Eds.), Network flows and matching: First DIMACS implementation challenge, DIMACS series on discrete mathematics and theoretical computer science (vol. 12, pp. 299–348).
Soares, S., & Salmazo, C. T. (1997). Minimum loss predispatch model for hydroelectric systems. IEEE Transactions on Power Systems, 12(3), 1220–1228.
Tolmasquim, M. T. (2012). Perspectivas e planejamento do setor energético no brasil. Estud. av, 1–19.
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We thank FAPESP Fundação de Amparo à Pesquisa do Estado de São Paulo and CNPq Conselho Nacional de Desenvolvimento Científico e Tecnológico for its financial support of this study.
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Carvalho, S.M.S., Oliveira, A.R.L. & Coelho, M.V. Predispatch Linear System Solution With Preconditioned Iterative Methods. J Control Autom Electr Syst 32, 145–152 (2021). https://doi.org/10.1007/s40313-020-00659-9
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DOI: https://doi.org/10.1007/s40313-020-00659-9