24 hour load forecasting using combined very-short-term and short-term multi-variable time-series model

被引：1
|
作者：
Lee W. [1 ]
Lee M. [2 ]
Kang B.-O. [3 ]
Jung J. [1 ]
机构：
[1] Dept. of Energy System Research, Ajou University
[2] Dept. of Energy Science, Sungkyunkwan University
[3] Dept. of Electric Engineering, Dong-a University
来源：
Jung, Jaesung (jjung@ajou.ac.kr) | 1600年 / Korean Institute of Electrical Engineers卷 / 66期
关键词：
24 hour load forecasting; Combined multi-variate time-series model; Multi-variate time-series model; Short-term load forecasting; Very-short-term load forecasting;
D O I：
10.5370/KIEE.2017.66.3.493
中图分类号：
学科分类号：
摘要：
This paper proposes a combined very-short-term and short-term multi-variate time-series model for 24 hour load forecasting. First, the best model for very-short-term and short-term load forecasting is selected by considering the least error value, and then they are combined by the optimal forecasting time. The actual load data of industry complex is used to show the effectiveness of the proposed model. As a result the load forecasting accuracy of the combined model has increased more than a single model for 24 hour load forecasting. Copyright © The Korean Institute of Electrical Engineers.
引用
收藏
页码：493 / 499
页数：6
相关论文
共 50 条
  • [31] Short-Term Load Forecasting of UPPCL using ANN
    Pandey, Anil K.
    Sahay, Kishan Bhushan
    Tripathi, M. M.
    Chandra, D.
    2014 6TH IEEE POWER INDIA INTERNATIONAL CONFERENCE (PIICON), 2014,
  • [32] Using deep learning for short-term load forecasting
    Nadjib Mohamed Mehdi Bendaoud
    Nadir Farah
    Neural Computing and Applications, 2020, 32 : 15029 - 15041
  • [33] Short-Term Load Forecasting Model Based on Multi-label and BPNN
    Sun, Xiaokui
    Ouyang, Zhiyou
    Yue, Dong
    ADVANCED COMPUTATIONAL METHODS IN LIFE SYSTEM MODELING AND SIMULATION, LSMS 2017, PT I, 2017, 761 : 263 - 272
  • [34] A dynamic multi-model transfer based short-term load forecasting
    Xiao, Ling
    Bai, Qinyi
    Wang, Binglin
    APPLIED SOFT COMPUTING, 2024, 159
  • [35] Short-term Load Forecasting With Clustered Hybrid Models Based On Hour Granularity
    Kouloumpris, Eleftherios
    Konstantinou, Athina
    Karlos, Stamatis
    Tsoumakas, Grigorios
    Vlahavas, Ioannis
    PROCEEDINGS OF THE 12TH HELLENIC CONFERENCE ON ARTIFICIAL INTELLIGENCE, SETN 2022, 2022,
  • [36] Using the hierarchical temporal memory spatial pooler for short-term forecasting of electrical load time series
    Osegi, E. N.
    APPLIED COMPUTING AND INFORMATICS, 2021, 17 (02) : 264 - 278
  • [37] On the use of reactive power as an endogenous variable in short-term load forecasting
    Santos, PJ
    Martins, AG
    Pires, AJ
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2003, 27 (05) : 513 - 529
  • [38] A New Model for Short-Term Load Forecasting in an Industrial Park
    Hernandez-Callejo, Luis
    Garcia-Pedrero, Angel
    Alonso Gomez, Victor
    SMART CITIES, 2019, 978 : 29 - 37
  • [39] Short-term load forecasting based on deep learning model
    Kim D.
    Jin-Jo H.
    Park J.-B.
    Roh J.H.
    Kim M.S.
    Transactions of the Korean Institute of Electrical Engineers, 2019, 68 (09) : 1094 - 1099
  • [40] Optimization of the kernel regression model to short-term load forecasting
    Dudek, Grzegorz
    PRZEGLAD ELEKTROTECHNICZNY, 2011, 87 (9A): : 222 - 225
12345