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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Energies (Basel) Ročník 8; číslo 12; s. 14287 - 14297
Hlavní autoři: Helseth, Arild, Braaten, Hallvard
Médium: Journal Article
Jazyk:angličtina
Vydáno: MDPI AG 01.12.2015
Témata:
dynamic programming
hydropower scheduling
parallel processing
stochastic programming
ISSN:1996-1073, 1996-1073
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
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