Using a combined method to forecasting electricity demand

doi:10.4028/www.scientific.net/AMM.678.120

CORC > 兰州理工大学 > 兰州理工大学

	Using a combined method to forecasting electricity demand
	Gui, Xiang Quan 1; Gui, Xiang Quan 2; Li, Li 1; Xie, Peng Shou 1; Cao, Jie 1
	2014
会议日期	August 27, 2014 - August 28, 2014
会议地点	Zhuhai, China
关键词	Commerce Forecasting Wavelet transforms Demand forecasting Electric markets Electricity demand forecasting Electricity demands Elman neural network Elman neural networks (ENN) Forecasting electricity Seasonal adjustments
卷号	678
DOI	10.4028/www.scientific.net/AMM.678.120
页码	120-125
英文摘要	In electric market, accurate electricity demand forecasting is often needed. Because electricity demand forecasting has become needful for creators and purchasers in the electric markets at present. But in electricity demand forecasting, noise signals, caused by various unstable factors, often corrupt demand series. In order to seek accurate demand forecasting methods, this article proposed a new combined electric load forecasting method (WSENN) which based on Wavelet Transform (WT), Seasonal Adjustment (SA) and Elman Neural Network (ENN) to forecast electricity demand. The effectiveness of WSENN is tested by applying the data from New South Wales (NSW) of Australia. Experimental results demonstrate that the WSENN model can offer more precise results than other methods that had mentioned in other literatures. © (2014) Trans Tech Publications, Switzerland.
会议录	Applied Mechanics and Materials
会议录出版者	Trans Tech Publications Ltd
语种	英语
ISSN号	16609336
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117673]
专题	兰州理工大学
作者单位	1.College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China; 2.School of Mathematics and Statistics, Lanzhou University, Lanzhou, China
推荐引用方式 GB/T 7714	Gui, Xiang Quan,Gui, Xiang Quan,Li, Li,et al. Using a combined method to forecasting electricity demand[C]. 见:. Zhuhai, China. August 27, 2014 - August 28, 2014.