Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7685
Title: Parallel discrete differential dynamic programming for multireservoir
Authors: Cheng, C
Wang, S
Chau, KW 
Wu, X
Keywords: Hydropower systems
Discrete differential dynamic programming
Parallel
Long-term operation
Optimization
Issue Date: Jul-2014
Publisher: Elsevier
Source: Environmental modelling & software, July 2014, v. 57, p. 152-164 How to cite?
Journal: Environmental modelling & software 
Abstract: The curse of dimensionality and computational time cost are a great challenge to operation of large-scale hydropower systems (LSHSs) in China because computer memory and computational time increase exponentially with increasing number of reservoirs. Discrete differential dynamic programming (DDDP) is one of the most classical algorithms for alleviating the dimensionality problem for operation of LSHSs. However, the computational time performed on DDDP still increases exponentially with increasing number of reservoirs. Therefore, a fine-grained parallel DDDP (PDDDP) algorithm, which is based on Fork/Join parallel framework in multi-core environment, is proposed to improve the computing efficiency for long-term operation of multireservoir hydropower systems. The proposed algorithm is tested using a huge cascaded hydropower system located on the Lancang River in China. The results demonstrate that the PDDDP algorithm enhances the computing efficiency significantly and takes full advantage of multi-core resources, showing its potential practicability and validity for operation of LSHSs in future.
URI: http://hdl.handle.net/10397/7685
ISSN: 1364-8152
DOI: 10.1016/j.envsoft.2014.02.018
Rights: Environmental Modelling & Software © 2014 Elsevier Ltd. The journal web site is located at http://www.elsevier.com/locate/envsoft.
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