DocumentCode
2826817
Title
The Minimum Abandoned Water Optimization Model of Reservoir and Its Application
Author
Sun, Xiu-ling ; Dong, Sheng-Nan ; Xu, Xiao-Ru
Author_Institution
Sch. of Civil Eng., Shandong Univ., Jinan, China
Volume
6
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
131
Lastpage
135
Abstract
The traditional control way of reservoir results in a large number of ¿abandoned water¿ during annual flood season, and it is possible that there is not always enough water for reservoir storing to maximal beneficial cubage after flood season. Responding to this case, this paper established the minimum abandoned water optimization model of reservoir based on risk analysis. There are two characters in this model: system has more relevancies and nonlinear. As the optimization model has aforementioned characters, this paper use particle swarm optimization method (PSO) to solve the model. In order to improve the convergence problem of PSO, combines PSO with simulating anneal arithmetic (SAA), that is, using particle swarm-simulating anneal arithmetic (P-S) to deal with the constraints in the model. Apply the model to the North Xing Jia reservoir in Yantai City, Shandong Province as an example. The result shows that it can increase markedly the use of water resources of this reservoir, which is of great use for improving the utilization of surface water resources in the north area of China.
Keywords
convergence; particle swarm optimisation; reservoirs; risk analysis; simulated annealing; convergence problem; flood season; minimum abandoned water optimization model; particle swarm optimization method; reservoir; risk analysis; simulating anneal arithmetic; Arithmetic; Convergence; Floods; Optimization methods; Particle swarm optimization; Reservoirs; Risk analysis; Simulated annealing; Water resources; Water storage; Application; Minimum Abandoned Water; Optimization Model; Reservoir;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.209
Filename
5363897
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