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
收藏
页码：14287 / 14297
页数：11
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