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
  • [41] A New Hybrid Model for Short-Term Electricity Load Forecasting
    Haq, Md Rashedul
    Ni, Zhen
    IEEE ACCESS, 2019, 7 : 125413 - 125423
  • [42] A Hybrid Stacking Model for Enhanced Short-Term Load Forecasting
    Guo, Fusen
    Mo, Huadong
    Wu, Jianzhang
    Pan, Lei
    Zhou, Hailing
    Zhang, Zhibo
    Li, Lin
    Huang, Fengling
    ELECTRONICS, 2024, 13 (14)
  • [43] An Effective Short-Term Load Forecasting Methodology Using Convolutional Long Short Term Memory Network
    Rafi, Shafiul Hasan
    Nahid-Al Masood
    Deeba, Shohana Rahman
    PROCEEDINGS OF 2020 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), 2020, : 278 - 281
  • [44] Short-term load forecasting using fuzzy logic and ANFIS
    Hasan Hüseyin Çevik
    Mehmet Çunkaş
    Neural Computing and Applications, 2015, 26 : 1355 - 1367
  • [45] Short-term load forecasting using dynamic neural networks
    Chogumaira, Evans N.
    Hiyama, Takashi
    Elbaset, Adel A.
    2010 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2010,
  • [46] Short-term load forecasting using artificial immune network
    You, Y
    Wang, SA
    Sheng, WX
    POWERCON 2002: INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY, VOLS 1-4, PROCEEDINGS, 2002, : 2322 - 2325
  • [47] Multi-objective LSTM ensemble model for household short-term load forecasting
    Chaodong Fan
    Yunfan Li
    Lingzhi Yi
    Leyi Xiao
    Xilong Qu
    Zhaoyang Ai
    Memetic Computing, 2022, 14 : 115 - 132
  • [48] Short-term load forecasting using Fuzzy Neural Network
    Shao, S
    Sun, YM
    FOURTH INTERNATIONAL CONFERENCE ON ADVANCES IN POWER SYSTEM CONTROL, OPERATION & MANAGEMENT, VOLS 1 AND 2, 1997, : 131 - 134
  • [49] Short-term load forecasting using informative vector machine
    Dept. of Electronics and Bioinformatics, Meiji University, 1-1-1, Higashimita, Tama-ku, Kawasaki 214-8571, Japan
    不详
    IEEJ Trans. Power Energy, 2007, 4 (566-572+2): : 566 - 572+2
  • [50] Short-Term Load Forecasting Using Informative Vector Machine
    Kurata, Eitaro
    Mori, Hiroyuki
    ELECTRICAL ENGINEERING IN JAPAN, 2009, 166 (02) : 23 - 31