考虑激励特性的汽轮机做功模型辨识数据优选方法  

Selection method for identification data of steam turbine work model considering excitation characteristics

作　　者：郝晓光 王辉 金飞 王腾辉 HAO Xiaoguang;WANG Hui;JIN Fei;WANG Tenghui(State Grid Hebei Energy Technology Service Co.,Ltd.,Shijiazhuang 050021,China;School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China)

机构地区：[1]国网河北能源技术服务有限公司,河北石家庄050021 [2]华北电力大学控制与计算机工程学院,北京102206

出　　处：《热力发电》2024年第11期130-138,共9页Thermal Power Generation

基　　金：国网河北省电力有限公司科技项目(TSS2023-03)。

摘　　要：针对历史运行数据中难以选择合适样本辨识汽轮机做功模型问题,提出一种考虑激励特性的辨识数据优选方法。首先,采用费歇尔(Fisher)信息矩阵条件数提取历史运行数据的激励特性,与数据的趋势特性和参数间相关性共同构成特征变量集。其次,以特征变量作为输入,基于标准汽轮机做功模型生成的标识结果作为输出,采用随机森林分类算法生成辨识数据分类规则模型,实现辨识数据的在线选择。最后,对模型分类结果的准确性与所选数据的辨识效果进行验证。结果表明,分类规则模型的准确度为97.561%,可准确选出历史运行数据中含有充分激励的样本段,其汽轮机做功模型辨识结果与标准模型具有较高的一致性。A method of identifying data by considering the excitation characteristics is proposed to solve the problem that it is difficult to select suitable samples from the historical operation data to identify the turbine work model.Firstly,Fisher’s information matrix condition number is applied to extract the excitation characteristics of the historical operating data,which together with the trend characteristics and the correlation between parameters constitute the set of feature variables.Secondly,by using the feature variables as inputs and the identification results generated based on the standard turbine work model as outputs,the Random Forest classification algorithm is used to generate a classification rule model for the identification data to realize the online selection of identification data.Finally,the accuracy of the model classification results and the identification effect of the selected data are verified.The result proves that the accuracy of the classification rule model is 97.561%,which can accurately select the sample segments containing sufficient incentives in the historical operation data,and the identification results of the turbine work model are in high consistency with that of the the standard model.

关 键 词：辨识数据 数据激励特性 汽轮机 随机森林 

分 类 号：TM621[电气工程—电力系统及自动化]