Efficient Parallelization of the Stochastic Dual Dynamic Programming Algorithm Applied to Hydropower Scheduling

Arild Helseth and Hallvard Braaten
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Arild Helseth: SINTEF Energy, Sem Sælands vei 11, Trondheim 7465, Norway
Hallvard Braaten: Department of Mathematical Sciences, The Norwegian University of Science and Technology, Trondheim 7491, Norway

Energies, 2015, vol. 8, issue 12, 1-11

Abstract: Stochastic dual dynamic programming (SDDP) has become a popular algorithm used in practical long-term scheduling of hydropower systems. The SDDP algorithm is computationally demanding, but can be designed to take advantage of parallel processing. This paper presents a novel parallel scheme for the SDDP algorithm, where the stage-wise synchronization point traditionally used in the backward iteration of the SDDP algorithm is partially relaxed. The proposed scheme was tested on a realistic model of a Norwegian water course, proving that the synchronization point relaxation significantly improves parallel efficiency.

Keywords: hydropower scheduling; stochastic programming; dynamic programming; parallel processing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (6)

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