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

Energies

Arild Helseth²  Hallvard Braaten¹ 

[1] Department of Mathematical Sciences, The Norwegian University of Science and Technology, Trondheim 7491, Norway;;SINTEF Energy, Sem Sælands vei 11, Trondheim 7465, Norway

关键词: hydropower scheduling;    stochastic programming;    dynamic programming;    parallel processing;   

DOI  :  10.3390/en81212431

来源: mdpi

【 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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.