DocumentCode :
3230610
Title :
Application of particle swarm optimization in flood optimal control of reservoir group
Author :
Jian-qun, Wang ; Xu-Yang, Guo
Author_Institution :
Coll. of Hydrol. & Water Resources, Hohai Univ., Nanjing, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
856
Lastpage :
859
Abstract :
The reservoir group along the middle and lower reaches of Yellow River is composed of the Luhun reservoir, Guxian reservoir and Xiaolangdi reservoir, in addition to Huanyuankou hydrological station as the common flood control point, with each reservoir having its own flood control objective respectively. The flood protection priority of the reservoir group along the middle and lower reaches of Yellow River is to regulate flood scientifically and reduce peak discharge at the flood control points of every reservoir and Huanyuankou hydrological station in the most efficient way. A flood optimal control model is established to optimize flood control of the reservoir group along the middle and lower reaches of Yellow River, based on the maximum flood peak clipping criterion. The combination of particle swarm optimization with reservoir cycling method is proposed to solve the model, whose effectiveness is validated through an expirical study.
Keywords :
floods; nonlinear programming; optimal control; particle swarm optimisation; reservoirs; Guxian reservoir; Huanyuankou hydrological station; Luhun reservoir; Xiaolangdi reservoir; Yellow River; flood optimal control; maximum flood peak clipping criterion; nonlinear optimization; particle swarm optimization; reservoir cycling method; reservoir group; Integrated optics; Reservoirs; flood regulation; nonlinear optimization; optimal operation; particle swarm optimization; swarm intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645237
Filename :
5645237
Link To Document :
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