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SIMULATION OPERATION METHOD FOR LARGE-SCALE RESERVOIR GROUP IN MAIN STREAM AND TRIBUTARIES OF RIVER BASIN

机译：河流河流域主流和支流大型储层组仿真运行方法

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摘要

The present invention relates to the field of optimal operation of a hydropower system, and provides a simulation operation method for a large-scale reservoir group in a main stream and tributaries of a river basin. The method comprises: (1) constructing a reservoir operation function, analyzing relevant factors affecting a reservoir outflow, performing correlation analysis, and determining input factors of each reservoir operation function; (2) constructing a neural network model according to the input factors of the operation function, optimizing neural network parameters using an adaptive moment estimation algorithm, training the constructed neural network by using historical operation data of the reservoir, and taking the trained neural network as a fitting function of the reservoir operation function; and (3) establishing a simulation operation model of the reservoir group according to the fitting function of the reservoir operation function, a spatial topological structure and the constraints of the reservoir operation, to simulate the operation process of the reservoir group of the river basin step by step. According to the present invention, the fitting accuracy is improved significantly, and the operation plan of the large-scale reservoir group in the main stream and tributaries of the river basin can be more accurately described in the case of the unknown operation pattern.

机译：本发明涉及水电系统的最佳运行领域，为大型储存器组提供了一种河流盆地主流和支流的模拟操作方法。该方法包括：（1）构建储层操作功能，分析影响储层流出的相关因素，执行相关分析和确定每个储层操作功能的输入因子; （2）根据操作功能的输入因素构建神经网络模型，使用自适应力矩估计算法优化神经网络参数，通过使用储存器的历史操作数据训练构建的神经网络，并将培训的神经网络拍摄为储层运行功能的拟合功能; （3）根据储层运行功能的装配函数，空间拓扑结构和储层操作的约束建立储层组的仿真操作模型，模拟河流域储层储存器组的运行过程逐步。根据本发明，在未知操作模式的情况下，可以显着提高了拟合精度，并且在河流盆中的主流和支流中的大规模储存器组的操作平面可以更准确地描述。

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公开/公告号WO2021120787A1

专利类型
公开/公告日2021-06-24

原文格式PDF
申请/专利权人 HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY;
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申请/专利号WO2020CN119821
发明设计人 ZHOU JIANZHONG;QIU HONGYA;LUO GUANGLEI;DAI LING;LU CHENGWEI;FENG ZHONGKAI;JIANG ZHIQIANG;ZHA GANG;ZENG YU;ZHU SIPENG;
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申请日2020-10-06
分类号E02B1/02;G06N3/04;G06N3/08;G06F30/20;G06F111/04;
国家 CN
入库时间 2022-08-24 19:37:37

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