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

被引：13

作者：

Helseth, Arild ^{[1
]}

Braaten, Hallvard ^{[2
]}

机构：

[1] SINTEF Energy, N-7465 Trondheim, Norway

[2] Norwegian Univ Sci & Technol, Dept Math Sci, N-7491 Trondheim, Norway

来源：

ENERGIES | 2015年 / 8卷 / 12期

关键词：

hydropower scheduling; stochastic programming; dynamic programming; parallel processing; SYSTEMS; POWER; MODEL;

D O I：

10.3390/en81212431

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

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.

引用

页码：14287 / 14297

页数：11

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