Study and Application of Dynamic Collocation of Variable Weights Combination Forecasting Model

被引:1
|
作者
Cao Ning [1 ]
Huang Jian-jun [1 ]
Xie Xiao-min [1 ]
机构
[1] Chongqing Elect Power Co, Chongqing, Peoples R China
来源
2013 IEEE 11TH INTERNATIONAL CONFERENCE ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING (DASC) | 2013年
关键词
Short-term load forecasting; Weight; Dynamic collocation; Combination forecasting model; Automatic screening;
D O I
10.1109/DASC.2013.97
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Short-term load forecasting plays a very important role in operating, controlling, and planning of power system. As the load forecasting is vulnerable to various environmental factors, the short-term load forecasting is uncertain and variable. The traditional single forecasting model used to forecast the load of power grid can't comply with the requirements of the power grid management. Combination forecasting model can largely make up for the one-sidedness of the single forecasting methods. In the implementation of combination model, the fixed load forecasting methods also make forecasting results inaccurate, and have a series of problems such as low credibility. In this paper, the thought of dynamic combination is applied in the orderly power consumption management platform, and a combined optimal forecasting model is constructed through automatic screening of the forecasting methods and dynamic collocation of weights. Practice has proved that the combined forecasting method has higher forecasting accuracy than the single forecasting method and it is not only has high forecasting accuracy, but also has good extendibility, quick speed of data processing, simplicity of operation and diversity of display mode.
引用
收藏
页码:404 / 409
页数:6
相关论文
共 50 条
  • [1] COMBINATION FORECASTING MODEL FOR WATER QUALITY BASED ON OPTIMAL WEIGHTS
    Liu Dongjun
    Zou Zhihong
    ICIM2012: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT, 2012, : 358 - 362
  • [2] Nonlinear Combination Forecasting Model and Its Application
    ZHOU Chuanshi\ LIU Yongqing (Ins.of System Engineer
    Journal of Systems Science and Systems Engineering, 1998, (02) : 124 - 128
  • [3] Wind speed forecasting based on variable weight combination forecasting model of neural network and grey model
    Zhang, Jian
    Tan, Lunnong
    ADVANCED MATERIALS AND PROCESS TECHNOLOGY, PTS 1-3, 2012, 217-219 : 2654 - 2657
  • [4] Study on nonlinear combination forecasting model for grain yield
    Ran, Liu
    Hui, Bu
    Ran, L., 2013, Asian Network for Scientific Information (12) : 4666 - 4672
  • [5] Adaptive logistics combination forecasting model
    Lu Yujin
    Chen Hongming
    Proceeding of the 2006 International Conference on Management of Logistics and Supply Chain, 2006, : 50 - 55
  • [6] The research on Combination forecasting model of the automobile sales forecasting system
    Liu Gaojun
    Long Boxue
    2009 INTERNATIONAL FORUM ON COMPUTER SCIENCE-TECHNOLOGY AND APPLICATIONS, VOL 3, PROCEEDINGS, 2009, : 82 - 85
  • [7] A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method
    Shengzhi Huang
    Bo Ming
    Qiang Huang
    Guoyong Leng
    Beibei Hou
    Water Resources Management, 2017, 31 : 3667 - 3681
  • [8] A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method
    Huang, Shengzhi
    Ming, Bo
    Huang, Qiang
    Leng, Guoyong
    Hou, Beibei
    WATER RESOURCES MANAGEMENT, 2017, 31 (11) : 3667 - 3681
  • [9] Research of Neural Network Ensemble Forecasting Based on Genetic Algorithm to Optimize the Combination Weights Dynamically
    Wang Le
    2018 CHINA INTERNATIONAL CONFERENCE ON ELECTRICITY DISTRIBUTION (CICED), 2018, : 1462 - 1466
  • [10] Combination Forecasting Model of Project Cost Based on SPSS
    Liu Rui
    Zhang Yuqing
    2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 7641 - 7644