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

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 S...

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Vydané v:Energies (Basel) Ročník 8; číslo 12; s. 14287 - 14297
Hlavní autori: Helseth, Arild, Braaten, Hallvard
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: MDPI AG 01.12.2015
Predmet:
dynamic programming
hydropower scheduling
parallel processing
stochastic programming
ISSN:1996-1073, 1996-1073
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Shrnutí: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en81212431