| 水库排沙调度优化模型 |
| |
| 引用本文： | 甘富万,李义天,邓金运,陈建.水库排沙调度优化模型[J].水科学进展,2009,20(6):863-868. |
| |
| 作者姓名： | 甘富万 李义天 邓金运 陈建 |
| |
| 作者单位： | 1.武汉大学水资源与水电工程科学国家重点实验室, 湖北, 武汉, 430072; |
| |
| 基金项目： | 国家自然科学基金资助项目，水资源与水电工程科学国家重点实验室(武汉大学)开放基金资助项目 |
| |
| 摘 要： | 在分析水库排沙调度机理的基础上建立了水库排沙调度优化模型,以遗传算法作为寻优算法,并用BP神经网络拟合一维水沙数学模型计算成果的方法简化了泥沙淤积计算,使得所建模型得以有效求解。以三峡水库为例进行优化,结果表明,利用所建立的模型和求解方法可以有效优化三峡水库的排沙调度,在保证淤积不增多的基础上大大增加了发电效益。
|
| 关 键 词： | 水库排沙调度 优化 遗传算法 神经网络 |
| 收稿时间： | 2008-09-16 |
Optimization model for reservoir sediment regulation |
| |
| Affiliation: | 1.State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;2.Guangxi Water and Power Design Institute, Nanning 530023, China;3.North China University of Water Conservancy and Hydroelectric Power, Zhengzhou 450011, China |
| |
| Abstract: | The optimizing sediment regulation will safeguard long-term reservoir operations and maximize the reservoir effectiveness. In this study, an optimization model for reservoir sediment regulation is developed based on the principle of efficiently removing sediment. The reservoir sedimentation is calculated using a one-dimensional water-sediment transport model, the back-propagation neural network is adopted in the model training processes, and a genetic algorithm is used to ensure the high performance in the model calibration. The model is applied to the Three Gorges Reservoir. The result shows that the model is capable of finding the balanced optimized solution for the reservoir sediment regulation and maximizing the reservoir power generation. |
| |
| Keywords: | reservoir sediment regulation optimization genetic algorithms neural network |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《水科学进展》浏览原始摘要信息 |
|
点击此处可从《水科学进展》下载全文 |
|
