刘本希 (副教授)

副教授   硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:水利工程系

学科:水文学及水资源. 水利水电工程

办公地点:大连理工大学西部校区能源与动力学院928室

电子邮箱:benxiliu@dlut.edu.cn

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Parallel chance-constrained dynamic programming for cascade hydropower system operation

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论文类型:期刊论文

发表时间:2018-12-15

发表刊物:ENERGY

收录刊物:SCIE、Scopus

卷号:165

页面范围:752-767

ISSN号:0360-5442

关键字:Chance-constrained dynamic programming; Parallel programming; Reliability; Extreme system failure; Cascade hydropower system

摘要:With continuing development of hydropower in China, cascade hydropower system will account for more in the power grid, and may increase power grid operation risk under global climate change. This paper presents a parallel chance-constrained dynamic programming model to derive optimal operating policies for a cascade hydropower system in China. The innovation work of this paper is mainly embodied in two aspects. First, the reliabilities of meeting the firm power requirements of the cascade hydropower system and avoiding extreme system failure under extreme events are explicitly embedded in the model using Lagrangian duality theory and a penalty function. Multiple operating policies are generated by updating the values of Lagrangian multiplier and penalty coefficient for system disruption, then best operating rules are selected based on system performance and evaluated according to simulated reliability, extreme system failure, and maximum benefit. Second, the Fork/Join parallel framework is deployed to parallelize the chance-constrained dynamic programming in a multi-core environment for improving computational efficiency. Two computing platforms with contrasting configurations are employed to illustrate the parallelization performance. Results from a cascade hydropower system operation demonstrate that the proposed method is computationally efficient and can obtain satisfying operating policies, especially for extreme drought events. (C) 2018 Elsevier Ltd. All rights reserved.

发表时间:2018-12-15

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