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Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin
Study region: Reservoir system on the Upper Yellow River Basin (UYRB), China. Study focus: A multipurpose reservoir system with multi-year regulation capacity calls for new optimization with high efficiency owing to the curse of dimensionality. This paper presents a state-of-the-art large-scale multi-objective evolutionary algorithm (LSMOEA), called the weight optimization framework (WOF) with Non-dominated Sorting Genetic Algorithm II (NSGAII) optimizer, to alleviate the problem, and improve its performance by determining applicable grouping mechanism based on inflow features. A novel constrains handle method named dual progressive repair is used to ensure search progress in feasible decision space. New hydrological insights for the region: Compared to classic NSGA2, WOF with NSGA2 optimizer (WOF-NSGA2 herein) shows better performance on diversity, convergence, and convergence rate. The tuning method, along with the repair method, makes WOF-NSGA2 outperform in all parameter combinations, and produces satisfying operation schedule in the case of multi-objective reservoir operation in the UYRB. The tuning and repair method could be used widely for the large-scale multi-objective reservoir system operation.
Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin
Study region: Reservoir system on the Upper Yellow River Basin (UYRB), China. Study focus: A multipurpose reservoir system with multi-year regulation capacity calls for new optimization with high efficiency owing to the curse of dimensionality. This paper presents a state-of-the-art large-scale multi-objective evolutionary algorithm (LSMOEA), called the weight optimization framework (WOF) with Non-dominated Sorting Genetic Algorithm II (NSGAII) optimizer, to alleviate the problem, and improve its performance by determining applicable grouping mechanism based on inflow features. A novel constrains handle method named dual progressive repair is used to ensure search progress in feasible decision space. New hydrological insights for the region: Compared to classic NSGA2, WOF with NSGA2 optimizer (WOF-NSGA2 herein) shows better performance on diversity, convergence, and convergence rate. The tuning method, along with the repair method, makes WOF-NSGA2 outperform in all parameter combinations, and produces satisfying operation schedule in the case of multi-objective reservoir operation in the UYRB. The tuning and repair method could be used widely for the large-scale multi-objective reservoir system operation.
Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin
Hongyi Yao (author) / Zengchuan Dong (author) / Dayong Li (author) / Xiaokuan Ni (author) / Tian Chen (author) / Mufeng Chen (author) / Wenhao Jia (author) / Xin Huang (author)
2022
Article (Journal)
Electronic Resource
Unknown
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Multi-Objective Synergetic Operation for Cascade Reservoirs in the Upper Yellow River
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