基于小波特征提取的可调节负荷辨识方法  

Adjustable load identification method based on wavelet feature extraction

作　　者：许春蕾 刘文颖[1] 郭虎 刘福潮 郑伟 Xu Chunlei;Liu Wenying;Guo Hu;Liu Fuchao;Zheng Wei(State Key Laboratory of New Energy Power System ,North China Electrical Power University, Beijing 102206,China;State Grid Gansu Electric Power Company, Lanzhou 730050, China)

机构地区：[1]华北电力大学新能源电力系统国家重点实验室,北京102206 [2]国网甘肃省电力公司,甘肃兰州730050

出　　处：《可再生能源》2019年第6期845-851,共7页Renewable Energy Resources

基　　金：国家科技支撑计划项目(2015BAA01B04);国家电网公司科技项目(52272216002D);国网甘肃省电力公司科技项目(SGGSKY00JNJS1700149)

摘　　要：可调节负荷辨识方法能够区别可再生能源并网的电力系统中各类具有调节特性的负荷。文章对各类典型可调节负荷特征进行了深入分析,提取可调节负荷的最大可调节速率、调节深度、最大可调节时间等特征参量。为了提高可调节负荷的辨识精度,利用DB小波变换提取小波能量值作为新增特征参量,在此基础上,提出一种基于小波特征提取的可调节负荷辨识方法,并采用模糊C均值聚类方法(FCM)进行负荷辨识。最后,对甘肃某地区典型综合负荷点进行仿真计算,验证了所提辨识方法可有效提高可调节负荷的辨识精度,对利用可调节负荷的调节能力消纳受阻风电具有重要的现实意义。Load identification method can identify the different types of adjustable loads in power system with high proportion of renewable energy. This paper makes an in-depth analysis of various typical adjustable load characteristics,the characteristic parameters such as maximum adjustable speed,maximum adjustable time and depth of adjustment are proposed. In order to improve the identification precision of adjustable load,the Daubechies fast wavelet transform is used to extract energy value as a new feature parameter. On this basis, an adjustable load identification method based on wavelet feature extraction is proposed, and fuzzy C means clustering method(FCM) is used to identify the load. Finally,typical integrated load points in Hexi area are simulated to verify that the proposed identification method can effectively improve the identification accuracy of adjustable load. Hence, it is of great practical significance to use the adjustable load capacity to make use of the curtailed wind power.

关 键 词：可调节负荷辨识 DB小波变换 特征提取 小波能量值 FCM 

分 类 号：TK81[动力工程及工程热物理—流体机械及工程]