Research and application of joint optimal operation of reservoir group flood control based on improved particle swarm optimization algorithm

Minglei Ren; Qi Zhang; Shuai Guo; Gang Wang; Wei Xu; Xiaoyang Liu; Liping Zhao; Yuhan Zhou

doi:10.1117/12.3051672

18 November 2024 Research and application of joint optimal operation of reservoir group flood control based on improved particle swarm optimization algorithm

Minglei Ren, Qi Zhang, Shuai Guo, Gang Wang, Wei Xu, Xiaoyang Liu, Liping Zhao, Yuhan Zhou

Author Affiliations +

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134030E (2024) https://doi.org/10.1117/12.3051672
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

The strategic synchronization of multiple reservoir operations for flood management is a vital non-engineering strategy that enhances the flood mitigation capabilities of these reservoirs. It can enhance reservoirs' flood control ability, and play a role in regulating flood peak, saving flood, alleviating or even avoiding flood disaster. This paper takes the three large reservoirs of Chushandian, Nanwan and Suyahu above Wangjiaba in the main stream of the Huaihe River as examples, takes the floods in July 2020 as the input, changes their previous independent and regularized operation mode, and aims to minimize the sum of the maximum flood control storage capacity occupied by the three reservoirs as the target for joint optimal operation of reservoir group flood control under the premise of ensuring downstream flood control safety. The corresponding model is established and solved by improved PSO. The results show that the improved PSO algorithm has higher search efficiency and convergence accuracy. Compared with regular scheduling, optimal scheduling can ensure the safety of the reservoir and downstream control stations in the basin, and the total storage capacity occupied by the three reservoirs can be reduced by 123 million m³.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Minglei Ren, Qi Zhang, Shuai Guo, Gang Wang, Wei Xu, Xiaoyang Liu, Liping Zhao, and Yuhan Zhou "Research and application of joint optimal operation of reservoir group flood control based on improved particle swarm optimization algorithm", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134030E (18 November 2024); https://doi.org/10.1117/12.3051672

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