Aggregation-Decomposition Coupling Drawdown Rule and Progressive Optimal Algorithm for Optimization of Large-Scale Reservoirs
With the increased construction reservoirs, hydropower systems are becoming larger and more complex, which brings challenges of optimal operation of large-scale reservoirs to improve the power generation. To address this efficiently, we propose an aggregation-decomposition method based on cascade re...
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Published in | Water resources management Vol. 38; no. 14; pp. 5463 - 5483 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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Dordrecht
Springer Netherlands
01.11.2024
Springer Nature B.V |
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Abstract | With the increased construction reservoirs, hydropower systems are becoming larger and more complex, which brings challenges of optimal operation of large-scale reservoirs to improve the power generation. To address this efficiently, we propose an aggregation-decomposition method based on cascade reservoir drawdown rule. Based on a two-stage method, we analyze the monotonicity of power generation increment of cascade reservoirs and propose the drawdown rule, which we used to guide the drawdown order of cascade reservoirs. On this basis, we propose an aggregation-decomposition coupling drawdown rule and progressive optimal algorithm (ADDR-POA) method of large-scale reservoirs. To confirm the viability of the proposed approach, we selected 29 series–parallel-mixed reservoirs in the upper Yangtze River Basin in China as the study subjects and optimized them with the goal of maximizing the total power generation. Results show that compared to conventional mathematical optimization method and heuristic algorithm, ADDR-POA can effectively express the compensation effect between reservoirs and has a good performance in improving the total power generation of the basin and reducing iteration times, which presents a novel approach for solving the problem of drawdown operation of large-scale reservoirs. |
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AbstractList | With the increased construction reservoirs, hydropower systems are becoming larger and more complex, which brings challenges of optimal operation of large-scale reservoirs to improve the power generation. To address this efficiently, we propose an aggregation-decomposition method based on cascade reservoir drawdown rule. Based on a two-stage method, we analyze the monotonicity of power generation increment of cascade reservoirs and propose the drawdown rule, which we used to guide the drawdown order of cascade reservoirs. On this basis, we propose an aggregation-decomposition coupling drawdown rule and progressive optimal algorithm (ADDR-POA) method of large-scale reservoirs. To confirm the viability of the proposed approach, we selected 29 series–parallel-mixed reservoirs in the upper Yangtze River Basin in China as the study subjects and optimized them with the goal of maximizing the total power generation. Results show that compared to conventional mathematical optimization method and heuristic algorithm, ADDR-POA can effectively express the compensation effect between reservoirs and has a good performance in improving the total power generation of the basin and reducing iteration times, which presents a novel approach for solving the problem of drawdown operation of large-scale reservoirs. |
Author | Lei, Xiaohui Wang, Chao Song, Peibing Jin, Pengyu He, Zhongzheng Xiao, Yunke Sun, Jiahui Wang, Hao |
Author_xml | – sequence: 1 givenname: Jiahui surname: Sun fullname: Sun, Jiahui organization: Geotechnical and Structural Engineering Research Center, Shandong University – sequence: 2 givenname: Chao surname: Wang fullname: Wang, Chao email: wangchao@iwrh.com organization: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research – sequence: 3 givenname: Hao surname: Wang fullname: Wang, Hao organization: Geotechnical and Structural Engineering Research Center, Shandong University, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research – sequence: 4 givenname: Yunke surname: Xiao fullname: Xiao, Yunke organization: Water resource department, Changjiang River Scientiffic Research Institute – sequence: 5 givenname: Xiaohui surname: Lei fullname: Lei, Xiaohui organization: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research – sequence: 6 givenname: Zhongzheng surname: He fullname: He, Zhongzheng organization: School of Infrastructure, Nanchang University – sequence: 7 givenname: Peibing surname: Song fullname: Song, Peibing organization: China Renewable Energy Engineering Institute – sequence: 8 givenname: Pengyu surname: Jin fullname: Jin, Pengyu organization: Collge of Water Resources and Hydrology, Hohai University |
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SubjectTerms | Aggregation Algorithms Atmospheric Sciences basins China Civil Engineering Coupling Decomposition Drawdown Earth and Environmental Science Earth Sciences Electric power generation Environment Geotechnical Engineering & Applied Earth Sciences Heuristic methods Hydroelectric power Hydrogeology Hydrology/Water Resources Mathematical analysis Optimization power generation Reservoirs River basins system optimization viability water Water drawdown water power watersheds Yangtze River |
Title | Aggregation-Decomposition Coupling Drawdown Rule and Progressive Optimal Algorithm for Optimization of Large-Scale Reservoirs |
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