利用人工神经网络生成双涡轮山图

A. R. G. Filho, Filipe de S. L. Ribeiro, R. Carvalho, C. Coelho
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引用次数: 2

摘要

山图是研究水轮机性能、发电、管理和水电控制的重要工具。提出了一种基于前馈人工神经网络(ANN-FF)的双山图生成模型。用于训练ANN-FF模型的数据集来自安装在巴西朗多尼亚州马德拉河上的水力涡轮机的小规模测试模型。应用所提出的ANN-FF模型对各参数的预测值与水轮机小试模型的实测值相近。所提出的ANN-FF模型的训练误差从小数点后第三位开始具有显著值。结果表明,ANN-FF算法是水轮机效率山图生成的一种较好的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generation of Two Turbine Hill Chart Using Artificial Neural Networks
The hill chart is an important tool for the study of the turbine performance, the energy production as well as management and hydropower control. This paper propose a model to generate two hill chart based on feed-forward Artificial Neural Network (ANN-FF). The dataset used for training the ANN-FF model is obtained from a small-scale test model of hydroelectric turbine, installed on the Madeira River in the state of Rondonia, Brazil. Predicted values obtained by applying the proposed ANN-FF model for each parameter is similar to the values measured from the small-scale test model of the turbine. The training errors of the proposed ANN-FF model have significant values from the third decimal point. It is concluded that ANN-FF is a good strategy for the generation of hill charts for the study of hydroelectric turbine efficiency.
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