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 mult...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-04-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581822000131 |
| _version_ | 1819003194240401408 |
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| author | Hongyi Yao Zengchuan Dong Dayong Li Xiaokuan Ni Tian Chen Mufeng Chen Wenhao Jia Xin Huang |
| author_facet | Hongyi Yao Zengchuan Dong Dayong Li Xiaokuan Ni Tian Chen Mufeng Chen Wenhao Jia Xin Huang |
| author_sort | Hongyi Yao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T23:17:07Z |
| format | Article |
| id | doaj.art-b462a858cc824e6a8b8baf41e6229cb0 |
| institution | Directory Open Access Journal |
| issn | 2214-5818 |
| language | English |
| last_indexed | 2024-12-20T23:17:07Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj.art-b462a858cc824e6a8b8baf41e6229cb02022-12-21T19:23:37ZengElsevierJournal of Hydrology: Regional Studies2214-58182022-04-0140101000Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River BasinHongyi Yao0Zengchuan Dong1Dayong Li2Xiaokuan Ni3Tian Chen4Mufeng Chen5Wenhao Jia6Xin Huang7College of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, ChinaCollege of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, China; Corresponding author.College of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, ChinaCollege of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, ChinaYellow River Institute of Hydraulic Research, No.45 Shunhe Road, Zhengzhou 450003, ChinaCollege of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, ChinaCollege of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, ChinaCollege of Hydrology and Water Resources, Hohai University, No.1, Xikang Road, Nanjing 210098, ChinaStudy 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.http://www.sciencedirect.com/science/article/pii/S2214581822000131Weight optimization frameworkGrouping mechanismConstraints handling methodLarge-scale multi-objective evolutionary algorithmUpper Yellow River Basin |
| spellingShingle | Hongyi Yao Zengchuan Dong Dayong Li Xiaokuan Ni Tian Chen Mufeng Chen Wenhao Jia Xin Huang Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin Journal of Hydrology: Regional Studies Weight optimization framework Grouping mechanism Constraints handling method Large-scale multi-objective evolutionary algorithm Upper Yellow River Basin |
| title | Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin |
| title_full | Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin |
| title_fullStr | Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin |
| title_full_unstemmed | Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin |
| title_short | Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: Case study of cascade reservoirs in the Upper Yellow River Basin |
| title_sort | long term optimal reservoir operation with tuning on large scale multi objective optimization case study of cascade reservoirs in the upper yellow river basin |
| topic | Weight optimization framework Grouping mechanism Constraints handling method Large-scale multi-objective evolutionary algorithm Upper Yellow River Basin |
| url | http://www.sciencedirect.com/science/article/pii/S2214581822000131 |
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