基于小波去噪的电力系统日负荷分析  

Analysis on Daily Load of Power System Based on Wavelet De-noising

作　　者：杨耀[1,2] 魏宾[3] 李晶晶[1,4] 高飞[5] 

机构地区：[1]华北电力大学,河北保定071000 [2]三门峡供电公司,河南三门峡472000 [3]西安供电局,陕西西安710032 [4]华仿科技有限公司,河北保定071000 [5]中国电力科学研究院,北京100192

出　　处：《陕西电力》2011年第12期14-17,共4页Shanxi Electric Power

基　　金：国家自然科学基金资助项目(70901025)

摘　　要：介绍了小波去噪的基本原理及方法,简要说明了其消噪的步骤。进一步说明了小波包去噪的原理和步骤,并给出了1个给定含噪信号去噪的实例。由于影响日负荷因素的复杂性,本文采用4个气象指数来量化温度、湿度和风速等气象因子对负荷的综合影响。首先介绍了小波去噪原理,然后通过小波去噪消除负荷和气象数据中的伪数据和噪声。结果表明,去噪以后从关联性上看效果显著,为最终进行负荷预测工作提供指导依据。Due to the complexity of the factors that affecting daily load, four meteorological indices are applied to quantify the combined effects on daily load caused by temperature, humidity, wind speed and other meteorological factors. This paper describes the basic principles and methods of wavelet de-noising, and briefly explains the wavelet de-noising steps. To further demonstrate this technique, one practical example of wavelet de-noising with given noisy-containing signal is illustrated. The results show a significant correlation after the pseudo-data and noise from load and meteorological data is eliminated. This study provides a guidance for eventual load forecasting.

关 键 词：日负荷 气象指数 小波去噪 伪数据 噪声 

分 类 号：TM715[电气工程—电力系统及自动化]