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Efficient parallelization of the stochastic dual dynamic programming algorithm applied to hydropower scheduling

Sammendrag

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
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Kategori

Vitenskapelig artikkel

Oppdragsgiver

  • Research Council of Norway (RCN) / 225873

Språk

Engelsk

Forfatter(e)

Institusjon(er)

  • SINTEF Energi AS / Energisystemer
  • Norges teknisk-naturvitenskapelige universitet

År

2015

Publisert i

Energies

ISSN

1996-1073

Forlag

MDPI

Årgang

8

Hefte nr.

12

Side(r)

14287 - 14297

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