A Parallel Solution to Large Scale Hydropower Scheduling - By reducing the number of synchronization points in the Stochastic Dual Dynamic Programming (SDDP) Algorithm
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Stochastic dual dynamic programming (SDDP) has become a popular algorithm usedin practical long-term scheduling of hydro power systems. The SDDP algorithm issignificantly more computationally demanding than most heuristic-basedscheduling methods, but can be designed to take advantage of parallelprocessing. This thesis presents a novel parallel scheme for the SDDP algorithm,where the stage-wise synchronization point traditionally used in the backwarditeration of the SDDP algorithm is either partially or fully relaxed. Theproposed scheme was tested on a realistic model of a Norwegian water course,proving that the partial synchronization point relaxation significantly improvesparallel efficiency.