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Energies 2015, 8(12), 14287-14297; doi:10.3390/en81212431

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

1
SINTEF Energy, Sem Sælands vei 11, Trondheim 7465, Norway
2
Department of Mathematical Sciences, The Norwegian University of Science and Technology, Trondheim 7491, Norway
*
Author to whom correspondence should be addressed.
Academic Editor: Juan Ignacio Pérez-Díaz
Received: 6 November 2015 / Revised: 4 December 2015 / Accepted: 10 December 2015 / Published: 18 December 2015
(This article belongs to the Special Issue Hydropower)
View Full-Text   |   Download PDF [753 KB, uploaded 18 December 2015]   |  

Abstract

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. View Full-Text
Keywords: hydropower scheduling; stochastic programming; dynamic programming; parallel processing hydropower scheduling; stochastic programming; dynamic programming; parallel processing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Helseth, A.; Braaten, H. Efficient Parallelization of the Stochastic Dual Dynamic Programming Algorithm Applied to Hydropower Scheduling. Energies 2015, 8, 14287-14297.

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