dc.contributor.advisor | Kvamsdal, Trond | |
dc.contributor.advisor | Kvarving, Arne Morten | |
dc.contributor.advisor | Helseth, Arild | |
dc.contributor.author | Braaten, Hallvard | |
dc.date.accessioned | 2015-10-06T10:56:54Z | |
dc.date.available | 2015-10-06T10:56:54Z | |
dc.date.created | 2014-10-15 | |
dc.date.issued | 2014 | |
dc.identifier | ntnudaim:12189 | |
dc.identifier.uri | http://hdl.handle.net/11250/2352604 | |
dc.description.abstract | Stochastic dual dynamic programming (SDDP) has become a popular algorithm used
in practical long-term scheduling of hydro power systems. The SDDP algorithm is
significantly more computationally demanding than most heuristic-based
scheduling methods, but can be designed to take advantage of parallel
processing. This thesis 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 either partially or fully relaxed. The
proposed scheme was tested on a realistic model of a Norwegian water course,
proving that the partial synchronization point relaxation significantly improves
parallel efficiency. | |
dc.language | eng | |
dc.publisher | NTNU | |
dc.subject | Fysikk og matematikk, Industriell matematikk | |
dc.title | A Parallel Solution to Large Scale Hydropower Scheduling - By reducing the number of synchronization points in the Stochastic Dual Dynamic Programming (SDDP) Algorithm | |
dc.type | Master thesis | |
dc.source.pagenumber | 72 | |