Reservoir-system simulation and optimization techniques

被引:84
作者
Fayaed, Sabah S. [1 ]
El-Shafie, Ahmed [1 ]
Jaafar, Othman [1 ]
机构
[1] Univ Kebangsaan Malaysia, Fac Engn & Built Environm, Dept Civil & Struct Engn, Ukm Bangi 43600, Malaysia
关键词
Reservoir system management; Optimization technique; Reservoir uncertainty; Dynamic programming; Artificial neural network; REAL-TIME OPERATION; DYNAMIC-PROGRAMMING MODELS; COMBINED GENETIC ALGORITHM; ARTIFICIAL NEURAL-NETWORK; WATER-RESOURCES; CLIMATE-CHANGE; MULTIOBJECTIVE OPTIMIZATION; MULTIRESERVOIR SYSTEMS; TURBIDITY CURRENTS; CONJUNCTIVE USE;
D O I
10.1007/s00477-013-0711-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Reservoir operation is one of the challenging problems for water resources planners and managers. In developing countries the end users are represented by the water sectors in most parts and conflict over water is resolved at the agency level. This paper discusses an overview of simulation and optimization modeling methods utilized in resolving critical issues with regard to reservoir systems. In designing a highly efficient as well as effective dam and reservoir operational system, reservoir simulation constitutes one of the most important steps to be considered. Reservoirs with well-functional and reliable optimization models require very accurate simulations. However, the nonlinearity of natural physical processes causes a major problem in determining the simulation of the reservoir's parameters (elevation, surface-area, storage). Optimization techniques have shown high efficiency when used with simulation modeling and the combination of the two methods had given the best results in the reservoir management. The principal concern of this review study is to critically evaluate and analyze simulation, optimization and combined simulation-optimization modeling approach and present an overview of their utility in previous studies. Inferences and suggestions which may assist in improving quality of this overview in the future are provided. These will also enable future researchers, system analysts and managers to achieve more precise optimal operational system.
引用
收藏
页码:1751 / 1772
页数:22
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