Contrastive analysis of three parallel modes in multi-dimensional dynamic programming and its application in cascade reservoirs operation

被引:54
作者
Zhang, Yanke [1 ]
Jiang, Zhiqiang [1 ]
Ji, Changming [1 ]
Sun, Ping [1 ]
机构
[1] North China Elect Power Univ, Coll Renewable Energy, Beijing 102206, Peoples R China
关键词
Cascade reservoirs; Reservoir operation; Multi-dimensional dynamic programming; Curse of dimensionality; Parallel algorithm; Parallel mode; COMBINED GENETIC ALGORITHM; FUZZY NEURAL-NETWORK; ECONOMIC-DISPATCH; OPTIMIZATION; SYSTEMS; TIME; RIVER; CONVERGENCE; MANAGEMENT; EVOLUTION;
D O I
10.1016/j.jhydrol.2015.07.017
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The "curse of dimensionality" of dynamic programming (DP) has always been a great challenge to the cascade reservoirs operation optimization (CROO) because computer memory and computational time increase exponentially with the increasing number of reservoirs. It is an effective measure to combine DP with the parallel processing technology to improve the performance. This paper proposes three parallel modes for multi-dimensional dynamic programming (MDP) based on .NET4 Parallel Extensions, i.e., the stages parallel mode, state combinations parallel mode and hybrid parallel mode. A cascade reservoirs of Li Xiangjiang River in China is used as the study instance in this paper, and a detailed contrastive analysis of the three parallel modes on run-time, parallel acceleration ratio, parallel efficiency and memory usage has been implemented based on the parallel computing results. Results show that all the three parallel modes can effectively shorten the run-time so that to alleviate the "curse of dimensionality" of MDP, but relatively, the state combinations parallel mode is the optimal, the hybrid parallel is suboptimal and the stages parallel mode is poor. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:22 / 34
页数:13
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