Research on the trend forecasting model of power communication network operation

被引:0
|
作者
Jian, Shi [1 ]
Wu Hai-yang [2 ]
机构
[1] State Grid Elect Power Res Inst, Nanjing 210003, Jiangsu, Peoples R China
[2] Jiangsu Prov Power Co, Nanjing 210024, Jiangsu, Peoples R China
关键词
Power transmission network; trend forecast; Performance characteristic;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper deeply studied the performance data of the power transmission network, selected indicators parameter in the characterization of the running state of the network. By analyzing the factors that affect the time series, a trend forecasting algorithm of network performance based on time series decomposition is constructed. It can make quantitative estimation for the future development trend of communication network. The model and algorithm of the paper are verified by the actual performance data. The results show that the forecast value is in good agreement with the actual monitoring data, and it has good practicability, which can provide technical support and judgment basis for the pre-warning of power communication network.
引用
收藏
页码:358 / 363
页数:6
相关论文
共 50 条
  • [41] A research on power load forecasting model based on data mining
    Sun, Fuyu
    Yang, Yunshi
    [J]. RESEARCH AND PRACTICAL ISSUES OF ENTERPRISE INFORMATION SYSTEMS II, VOL 2, 2008, 255 : 1369 - +
  • [42] Research on Power Load Forecasting Method Based on LSTM Model
    Cui, Can
    He, Ming
    Di, Fangchun
    Lu, Yi
    Dai, Yuhan
    Lv, Fengyi
    [J]. PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020), 2020, : 1657 - 1660
  • [43] Research of Power Wireless Private Network Technology in the Terminal Communication Access Network
    Wang, Feng
    Ding, Yixin
    Li, Ming
    Ma, Junwei
    Shi, Xincong
    Yan, Lei
    [J]. PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON COMPUTER MODELING, SIMULATION AND ALGORITHM (CMSA 2018), 2018, 151 : 354 - 356
  • [44] Neural network forecasting for seasonal and trend time series
    Zhang, GP
    Qi, M
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2005, 160 (02) : 501 - 514
  • [45] Research on Reconfigurable Key Management in Electric Power Communication Network
    Li, Huan
    Lu, Shengyang
    Li, Wei
    Geng, Hongbi
    [J]. PROCEEDINGS OF THE 2016 5TH INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENTAL PROTECTION (ICEEP 2016), 2016, 98 : 469 - 473
  • [46] Research on Short-term Power Load Time Series Forecasting model Based on BP Neural Network
    Niu Dongxiao
    Shi Hui
    Li Jianqing
    Wei Yanan
    [J]. 2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 4, 2010, : 509 - 512
  • [47] Research on Simulation Technology of Communication Network for Power System Protection
    Jin, GuangXiang
    Li, JiangSheng
    Liu, YaoXian
    Sun, Yi
    Li, Bin
    [J]. PROCEEDINGS OF 2017 8TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2017), 2017, : 600 - 603
  • [48] Research on A Forecasting Model of Wind Power based on Recurrent Neural Network with Long Short-term Memory
    Li, Anying
    Cheng, Lei
    [J]. 2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019), 2019, : 1776 - 1779
  • [49] Research on Cyber Attacks and Defensive Measures of Power Communication Network
    Wu, Yingjun
    Ru, Yingtao
    Lin, Zhiwei
    Liu, Chengjun
    Xue, Tao
    Zhao, Xiang
    Chen, Jinfan
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (09) : 7613 - 7635
  • [50] Operation Quality Evaluation of Power Communication Network Based on Business QOS Indicators
    Zhang, Geng
    Wang, Ke
    Wang, Yang
    Wang, Yanan
    Chen Xiangzhou
    [J]. 2018 INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS AND CONTROL ENGINEERING (ISPECE 2018), 2019, 1187