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

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 algorit...

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Bibliographic Details
Published inWater resources management Vol. 34; no. 6; pp. 2029 - 2041
Main Authors Feng, Zhong-kai, Niu, Wen-jing, Jiang, Zhi-qiang, Qin, Hui, Song, Zhen-guo
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.04.2020
Springer Nature B.V
Subjects
Algorithms
Atmospheric Sciences
Civil Engineering
Dynamic programming
Earth and Environmental Science
Earth Sciences
Electric power generation
Environment
Geotechnical Engineering & Applied Earth Sciences
Hydroelectric power
Hydrogeology
Hydrology/Water Resources
Hypercubes
Latin hypercube sampling
Optimization
Reduction
Reservoir operation
Sampling
Sampling methods
State variable
Dimensionality reduction
Latin hypercube sampling
Dynamic programming
Cascade hydropower reservoirs
Monthly operation optimization
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Summary: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.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-020-02545-0