Forecasting Electricity Consumption Using an Improved Grey Prediction Model

doi:10.3390/info9080204

CORC > 上海财经大学 > 上海财经大学

	Forecasting Electricity Consumption Using an Improved Grey Prediction Model
	Li, Kai 1; Zhang, Tao 1,2
刊名	INFORMATION
	2018-08
卷号	9 期号:8
关键词	grey forecasting model electricity consumption GM(1 1) model background value data transformation DCOGM(1 1)
ISSN号	2078-2489
DOI	10.3390/info9080204
英文摘要	Prediction of electricity consumption plays critical roles in the economy. Accurate electricity consumption forecasting is essential for policy makers to formulate electricity supply policies. However, limited data and variables generally cannot provide sufficient information to gain satisfactory prediction accuracy. To address this problem, we propose a novel improved grey forecasting model, which combines data transformation for the original data sequence and combination interpolation optimization of the background value of the GM(1,1) model, and is therefore named DCOGM(1,1). To evaluate the simulation and prediction performance of DCOGM(1,1), two case studies are carried out. In addition, the results show that DCOGM(1,1) outperforms most existing improved grey models in terms of forecasting accuracy. Finally, DCOGM(1,1) is employed to predict the total electricity consumption of Shanghai City in China from 2017 to 2021. In addition, the results suggest that DCOGM(1,1) performs well compared with the traditional GM(1,1) model and other grey modification models in this context and Shanghai's electricity consumption will increase stably in the following five years. In summary, DCOGM(1,1) proposed in our study has competent exploration and exploitation ability, and could be utilized as an effective and promising tool for short-term planning for other forecasting issues with limited source data as well.
WOS研究方向	Computer Science
语种	英语
出版者	MDPI
WOS记录号	WOS:000443255500021
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/551]
专题	上海财经大学
通讯作者	Zhang, Tao
作者单位	1.Shanghai Univ Finance & Econ, Sch Informat Management & Engn, 777 Guoding Rd, Shanghai 200433, Peoples R China; 2.Shanghai Univ Finance & Econ, Shanghai Key Lab Financial Informat Technol, 777 Guoding Rd, Shanghai 200433, Peoples R China
推荐引用方式 GB/T 7714	Li, Kai,Zhang, Tao. Forecasting Electricity Consumption Using an Improved Grey Prediction Model[J]. INFORMATION,2018,9(8).
APA	Li, Kai,&Zhang, Tao.(2018).Forecasting Electricity Consumption Using an Improved Grey Prediction Model.INFORMATION,9(8).
MLA	Li, Kai,et al."Forecasting Electricity Consumption Using an Improved Grey Prediction Model".INFORMATION 9.8(2018).