Wavelets based analysis of non-uniformly sampled data for power load forecasting

被引：0
|
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-EURASIP WORKSHOP ON NONLINEAR SIGNAL AND IMAGE PROCESSING (NSIP'99) | 1999年
关键词：
wavelets; multi resolution analysis; load forecasting; power system analysis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the compactly supported orthonormal symmetrical wavelets is used to estimate non-uniformly sampled and non-gaussian noise corrupted load consumption signals for the purpose of load forecasting in a typical electrical utility network. Power load forecasting is an important function of utility management and present methods invariably rely heavily on past historical load curves which are collected from the grid via various monitors placed at several nodes. Wavelet technology is proposed in this paper to recover irregularly sampled data, for denoising, compression and subsequent extraction of evolutionary trends in the signal in various time windows. Simple algorithms are outlined for each stage in a modular load signal analysis scheme.
引用
收藏
页码：784 / 787
页数：4
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