A novel two-stage seasonal grey model for residential electricity consumption forecasting
文献类型：期刊论文
| 作者 | Du, Pei1; Guo, Ju'e1; Sun, Shaolong1; Wang, Shouyang2; Wu, Jing1 |
| 刊名 | ENERGY
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 258页码:18 |
| ISSN号 | 0360-5442 |
| 关键词 | Electricity consumption forecasting Grey model Seasonal factor Error correction strategy |
| DOI | 10.1016/j.energy.2022.124664 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:000854020000001 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/61031]  |
| 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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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