A Short-Term Forecasting Approach for Regional Electricity Power Consumption by Considering Its Co-movement with Economic Indices

被引:0
|
作者
Li, Kai [1 ]
Yang, Zan [2 ]
Li, Dan [2 ]
Xing, Yidan Yedda [1 ]
Nai, Wei [1 ]
机构
[1] Tongji Zhejiang Coll, Dept Elect & Informat Engn, Jiaxing 314051, Zhejiang, Peoples R China
[2] Tongji Zhejiang Coll, Dept Sci, Jiaxing 314051, Zhejiang, Peoples R China
关键词
regional electricity consumption; short-term forecasting; economic indices; Grey Theory; Random Forest co-movement;
D O I
10.1109/itoec49072.2020.9141928
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Electricity power consumption of a certain city or even a region always has a close relationship with the economic development of the corresponding area. Thus, interpreting the characteristics of previous regional electricity power consumption data as well as past economic data, and finding out the interrelation between them, would be of great reference value in doing the short-term forecasting work together for both. The combined forecasting work will undoubtedly be more rational and accurate in giving future electricity power consumption tendency, by comparing with the work merely based on electricity power consumption data itself. Till now, most related research have focused on analyzing the mutual relationship between electricity power consumption and economic development, forecasting work based on both aspects can still hardly be found. In this paper, a short-term forecasting approach for regional electricity power consumption by considering its co-movement with economic indices has been proposed, it has fully considered the interaction between electricity power consumption and the economic indices, and has let the forecasting result of latter make the "secondary correction" to the result of former. By setting a certain region in central western China as an example, the effectiveness of proposed approach has been proved.
引用
收藏
页码:551 / 555
页数:5
相关论文
共 50 条
  • [1] Short-term Forecasting of Electricity Consumption in Maputo
    Sotomane, Constantino
    Asker, Lars
    Bostrom, Henrik
    Massingue, Venancio
    2013 INTERNATIONAL CONFERENCE ON ADVANCES IN ICT FOR EMERGING REGIONS (ICTER), 2013, : 132 - 136
  • [2] A Short-Term Hybrid Forecasting Approach for Regional Electricity Consumption Based on Grey Theory and Random Forest
    Li, Kai
    Xing, Yidan
    Zhu, Haijia
    Nai, Wei
    2020 5TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA 2020), 2020, : 194 - 198
  • [3] Short-term forecasting of industrial electricity consumption in Brazil
    Sadownik, R
    Barbosa, EP
    JOURNAL OF FORECASTING, 1999, 18 (03) : 215 - 224
  • [4] CONSUMER CONFIDENCE INDICES AND SHORT-TERM FORECASTING OF CONSUMPTION
    Al-Eyd, Ali
    Barrell, Ray
    Davis, E. Philip
    MANCHESTER SCHOOL, 2009, 77 (01): : 96 - 111
  • [5] A global probabilistic approach for short-term forecasting of individual households electricity consumption
    Botman, Lola
    Lago, Jesus
    Becker, Thijs
    Vanthournout, Koen
    De Moor, Bart
    APPLIED ENERGY, 2025, 382
  • [6] Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting
    Divina, Federico
    Gilson, Aude
    Gomez-Vela, Francisco
    Torres, Miguel Garcia
    Torres, Jose E.
    ENERGIES, 2018, 11 (04)
  • [7] COMPARISON OF SHORT-TERM FORECASTING METHODS OF ELECTRICITY CONSUMPTION IN MICROGRIDS
    Parfenenko, Yu. V.
    Shendryk, V. V.
    Kholiavka, Ye. P.
    Pavlenko, P. M.
    RADIO ELECTRONICS COMPUTER SCIENCE CONTROL, 2023, (01) : 14 - 23
  • [8] A short-term electricity consumption forecasting approach based on feature processing and hybrid modelling
    Wei, Minjie
    Wen, Mi
    Luo, Junran
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2022, 16 (10) : 2003 - 2015
  • [9] Short-term Relationship Between Electricity Consumption and Economic Growth
    Liyu, Xia
    Wan, He
    Qian, Zhang
    2020 5TH INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE, ENERGY TECHNOLOGY AND ENVIRONMENTAL ENGINEERING, 2020, 571
  • [10] Short-term Electric Power Demand Forecasting Based on Economic-electricity Transmission Model
    Li, Wenfeng
    Bai, Hongkun
    Liu, Wei
    Liu, Yongmin
    Wang, Yubin Mao
    Wang, Jiangbo
    He, Dandan
    ADVANCES IN MATERIALS, MACHINERY, ELECTRONICS II, 2018, 1955