Optimization of Operation Strategies for an Interbasin Water Diversion System Using an Aggregation Model and Improved NSGA-II Algorithm
Publication: Journal of Irrigation and Drainage Engineering
Volume 146, Issue 5
Abstract
To maximize the benefits of an interbasin water diversion system (IBWD), an aggregation model and improved NSGA-II algorithm were constructed to establish operation strategies for water diversion and water supply. An aggregation model was constructed to aggregate multiple reservoirs into an equivalent reservoir which made the operation strategies for water diversion and supply easy to define. Then an improved nondominated sorting genetic algorithm II (NSGA-II) algorithm was developed by considering variables’ sensitivity to improve its search efficiency. Finally, the IBWD subsystem for water supply in China’s Shenzhen city was taken as a case study, and its operation strategies for different water supply scenarios were optimized by the improved algorithm. Simulation results demonstrated that the equivalent reservoir is an effective method to reduce the complexity of operational strategies, and improved NSGA-II algorithm has a higher search efficiency.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party (Xili Reservoir Authority and Shenzhen Water Planning & Design Institute) and may be provided only with restrictions (e.g., project scale, engineering structure, and partial water demand information).
Acknowledgments
This research is supported by the National Natural Science Foundation of China (Grant Nos. 51609025, 91547111, and 51709108), Open Fund Approval (SKHL1713, 2017), the Chongqing Technology Innovation and Application Demonstration Project (cstc2018jscx-msybX0274 and cstc2016shmszx30002), Xili Reservoir Authority, and Shenzhen Water Planning & Sesign Institute.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 146 • Issue 5 • May 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Apr 17, 2019
Accepted: Nov 12, 2019
Published online: Mar 14, 2020
Published in print: May 1, 2020
Discussion open until: Aug 14, 2020
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