A novel two-stage seasonal grey model for residential electricity consumption forecasting

doi:10.1016/j.energy.2022.124664

CSpace

	A novel two-stage seasonal grey model for residential electricity consumption forecasting
	Du, Pei 1; Guo, Ju'e 1; Sun, Shaolong 1; Wang, Shouyang 2; Wu, Jing 1
	2022-11-01
发表期刊	ENERGY
ISSN	0360-5442
卷号	258 页码:18
摘要	Accurate electricity consumption forecasting plays a significant role in power production and supply and power dispatching. Thus, a new hybrid model combing a grey model with fractional order accumulation, called FGM (1, 1), with seasonal factors, sine cosine algorithm (SCA), and an error correction strategy is proposed in this research. To accurately predict the seasonal fluctuations, seasonal factors are used in this model; Then, with the aim of improving the prediction performance, a SFGM (1,1) model optimized by SCA rather than least square method, namely SCA-SFGM (1, 1), is establish to forecast electricity con-sumption; Moreover, considering forecasting error sequence may contain useful information, an error correction strategy is introduced to model forecasting error time series to adjust the preliminary fore-casts of SCA-SFGM (1, 1). Fourth, four comparison models, three measurement criteria and a statistical hypothesis testing method using monthly residential electricity consumption dataset from 2015 to 2020 are designed to verify the prediction performance of models; Lastly, experimental results show that the mean absolute percentage error (MAPE) of the proposed model is 4.1698%, which is much lower than 14.5642%, 6.5108%, 5.9472%, 5.7060% and 4.9219% of GM (1, 1), SARIMA, SGM (1, 1), SFGM (1,1) and SCA-SFGM (1, 1) models, respectively, showing that the proposed model can not only effectively capture seasonal fluctuations, it also adds an operational candidate forecasting benchmark model in electricity markets. (c) 2022 Published by Elsevier Ltd.
关键词	Electricity consumption forecasting Grey model Seasonal factor Error correction strategy
DOI	10.1016/j.energy.2022.124664
收录类别	SCI
语种	英语
资助项目	Soft science project of Shaanxi Province[2022KRM093] ; Fundamental Research Funds for the Central Universities[SK2022040] ; China Postdoctoral Science Foundation[2021M702579]
WOS研究方向	Thermodynamics ; Energy & Fuels
WOS类目	Thermodynamics ; Energy & Fuels
WOS记录号	WOS:000854020000001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/61032
专题	中国科学院数学与系统科学研究院
通讯作者	Wu, Jing
作者单位	1.Xi An Jiao Tong Univ, Sch Management, Xian 710049, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Du, Pei,Guo, Ju'e,Sun, Shaolong,et al. A novel two-stage seasonal grey model for residential electricity consumption forecasting[J]. ENERGY,2022,258:18.
APA	Du, Pei,Guo, Ju'e,Sun, Shaolong,Wang, Shouyang,&Wu, Jing.(2022).A novel two-stage seasonal grey model for residential electricity consumption forecasting.ENERGY,258,18.
MLA	Du, Pei,et al."A novel two-stage seasonal grey model for residential electricity consumption forecasting".ENERGY 258(2022):18.