Using a Combined Method to Forecasting Electricity Demand

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

	Using a Combined Method to Forecasting Electricity Demand
	Gui, Xiangquan; Li, Li; Xie, Pengshou; Cao, Jie
	2014
关键词	Electricity demand forecasting Wavelet transform Seasonal Adjustment Elman Neural Network
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.
会议录	ADVANCES IN MECHATRONICS AND CONTROL ENGINEERING III
会议录出版者	TRANS TECH PUBLICATIONS LTD
会议录出版地	LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND
语种	英语
WOS研究方向	Engineering ; Materials Science ; Mechanics
WOS记录号	WOS:000348108500025
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36605]
专题	计算机与通信学院
通讯作者	Gui, Xiangquan
作者单位	Lanzhou Univ Technol, Coll Comp & Commun, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Gui, Xiangquan,Li, Li,Xie, Pengshou,et al. Using a Combined Method to Forecasting Electricity Demand[C]. 见:.