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Improving stochastic dynamic programming on hydrothermal systems through an iterative process

2015; Elsevier BV; Volume: 123; Linguagem: Inglês

10.1016/j.epsr.2015.02.011

1873-2046

Rafael Bruno S. Brandi, Tales Pulinho Ramos, Bruno Henriques Dias, André Luís Marques Marcato, Ivo Chaves da Silva,

Water Systems and Optimization

This paper proposes an iterative process to select the cuts that model the cost-to-go functions of stochastic dynamic programming (SDP) and stochastic dual dynamic programming (SDDP) algorithms. This approach is applied to the medium/long-term operation planning of hydrothermal systems. The main idea of the proposed algorithm is to improve the performance of the SDP and SDDP methods applied to the problem by iteratively adding cuts to the linear programming instances. Also, some case studies considering the Brazilian power system are presented. The results show a significant reduction in computational time with few modifications to the original algorithm.