Applications of Symlets for denoising and load forecasting

被引:13
作者
Swee, EG [1 ]
Elangovan, S [1 ]
机构
[1] Natl Univ Singapore, Dept Elect Engn, Singapore 119260, Singapore
来源
PROCEEDINGS OF THE IEEE SIGNAL PROCESSING WORKSHOP ON HIGHER-ORDER STATISTICS | 1999年
关键词
load forecasting; denoising; wavelet transforms; power systems analysis;
D O I
10.1109/HOST.1999.778717
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The Symmetrical Wavelet (Symlet) is proposed as a basis function in a Multi-Resolution Analysis (MRA) using the Discrete Wavelet Transform (DWT) to analyze power load consumption signals. Load forecasting is an important function in a utility as it supports maintenance, marketing, investment and production planning. Present load forecasting techniques rely heavily on past load patterns. These load consumption signals however are by nature corrupted by non-stationary and non-gaussian noise processes of which no models exists. Wavelet analysis is proposed in this case to denoise and isolate load trends in the consumption patterns. A one-week sample data is analysed to demonstrate the potential and benefits of such a scheme.
引用
收藏
页码:165 / 169
页数:3
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