Identification of Nonlinear Load Power using Wavelet Neural Networks

摘要：

In this paper, a Dmeyer Wavelet function is utilized to decompose the mixed load current waveforms and extract the parameter values which represent the nonlinear loads. A three layer BP neural network model is established, which is trained using Levenberg Marquardt (LM) algorithm which shows fast convergence and strong stability. The results indicate that the proposed method of the wavelet BP neural network load identification has good practicability and reliability. The scientific management of university student’s apartments is realized. This study is very important for eliminating the campuses fire hidden trouble.

作者: Meng Gao Fuchun Sun Yanhui Shi Jianhua Liu Huaping Liu

作者单位: are with Shijiazhuang Railway Institute are with Department of Computer Science and Technology,Tsinghua University

会议类型: 国际会议

会议名称: The 2nd International Symposium on Systems and Control in Aeronautics and Astronautics(第二届航空航天系统与控制国际会议 ISSCAA 2008)

会议地点: 深圳

会议语种:英文

页码: 116-120

在线出版日期: 2008-12-10（万方平台首次上网日期，不代表论文的发表时间）