基于数据挖掘的煤电机组能效特征指标及其基准值的研究

发布时间：2018-05-28 07:39

本文选题：煤电机组 + 优化运行　；参考：《中国电机工程学报》2017年07期

【摘要】：煤电机组的优化运行对于节能降耗有重要的意义,如何合理地选择能效特征指标并确定其基准值是机组优化运行的关键。基于数据挖掘算法,对机组历史运行数据分析:利用灰色关联度分析法,选取对供电煤耗产生主要影响的能效特征指标;采用K均值算法对多特征参数进行聚类划分并确定其基准值;结合广义回归神经网络,预测供电煤耗在基准工况下的目标值;对离散基准值样本点进行样条插值,建立机组全工况下的动态基准值工况库。最后,选取某超超临界百万湿冷机组运行数据分析与验证,分析结果表明提出的能效指标基准值研究方法,可以为煤电机组的优化运行提供调整方向。
[Abstract]:The optimal operation of coal generating units is of great significance for energy saving and consumption reduction. How to reasonably select the energy efficiency characteristic index and determine its reference value is the key to the optimal operation of the units. Based on the data mining algorithm, the paper analyzes the historical operation data of the unit. By using the grey correlation analysis method, it selects the energy efficiency characteristic index which has the main influence on the power supply coal consumption. K-means algorithm is used to cluster the multi-characteristic parameters and determine the reference value; combined with the generalized regression neural network, the target value of power supply coal consumption in the reference condition is predicted; the sample points of discrete datum value are interpolated by spline. The dynamic datum working condition library of the unit is established under all working conditions. Finally, the operation data of a ultra supercritical million wet cooling unit is analyzed and verified. The analysis results show that the proposed research method of energy efficiency index reference value can provide the adjustment direction for the optimization operation of coal power unit.
【作者单位】：华北电力大学国家火力发电工程技术研究中心;
【分类号】：TK01

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