Monthly Operation Optimization of Cascade Hydropower Reservoirs with Dynamic Programming and Latin Hypercube Sampling for Dimensionality Reduction

Zhong-kai Feng (), Wen-jing Niu, Zhi-qiang Jiang, Hui Qin and Zhen-guo Song
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Zhong-kai Feng: Huazhong University of Science and Technology
Wen-jing Niu: ChangJiang Water Resources Commission
Zhi-qiang Jiang: Huazhong University of Science and Technology
Hui Qin: Huazhong University of Science and Technology
Zhen-guo Song: China Ship Development and Design Center

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 6, No 11, 2029-2041

Abstract: Abstract The dimensionality problem is posing an enormous challenge for cascade hydropower reservoirs operation because the memory usage and execution time grow exponentially with the expansion of system scale. To effectively address this problem, this paper develops a novel Latin dynamic programming algorithm for dimensionality reduction in hydropower reservoir operation problem, where the Latin hypercube sampling method is firstly adopted to produce a subset of discrete state variables at each stage, and then the standard dynamic programming recursive equation is used to search for a modified trajectory around the newly-generated solutions, while the iterative search strategy is used to gradually enhance the solution quality. The results in a real-world hydropower system of China demonstrate that compared with the standard dynamic programming method, the execution efficiency of the presented method is significantly improved while the power generation is well maintained in different scenarios. Hence, the novelty of the paper is to provide an effective dimensionality reduction tool for solving the complex hydropower operation problem.

Keywords: Cascade hydropower reservoirs; Monthly operation optimization; Latin hypercube sampling; Dynamic programming; Dimensionality reduction (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11269-020-02545-0

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