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 inWater resources management Vol. 38; no. 14; pp. 5463 - 5483
Main Authors Sun, Jiahui, Wang, Chao, Wang, Hao, Xiao, Yunke, Lei, Xiaohui, He, Zhongzheng, Song, Peibing, Jin, Pengyu
Format Journal Article
LanguageEnglish
Published 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.
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
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  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
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  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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Progressive optimal algorithm
Large-scale reservoirs
Aggregation-decomposition
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Snippet With the increased construction reservoirs, hydropower systems are becoming larger and more complex, which brings challenges of optimal operation of...
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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
URI https://link.springer.com/article/10.1007/s11269-024-03863-3
https://www.proquest.com/docview/3126246427
https://www.proquest.com/docview/3154176209
Volume 38
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