DocumentCode :
2975399
Title :
Applications of symlets for denoising and load forecasting
Author :
Swee, E.G.T. ; Elangovan, M.S.
Author_Institution :
Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore
fYear :
1999
fDate :
1999
Firstpage :
165
Lastpage :
169
Abstract :
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. One week of sample data is analysed to demonstrate the potential and benefits of such a scheme
Keywords :
discrete wavelet transforms; load forecasting; noise; power system analysis computing; signal processing; signal resolution; DWT; MRA; basis function; denoising; discrete wavelet transform; investment; load forecasting; maintenance; marketing; multi-resolution analysis; non-Gaussian noise processes; non-stationary noise processes; power load consumption signals; power systems analysis; production planning; symlets; symmetrical wavelet; Discrete wavelet transforms; Investments; Load forecasting; Multiresolution analysis; Noise reduction; Pattern analysis; Production planning; Signal analysis; Signal processing; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Caesarea
Print_ISBN :
0-7695-0140-0
Type :
conf
DOI :
10.1109/HOST.1999.778717
Filename :
778717
Link To Document :
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