Neural network based very short term load prediction

被引:0
|
作者
Chen, Dingguo [1 ]
York, Mike [1 ]
机构
[1] Siemens Power Transmiss & Distribut Inc, 10900 Wayzata Blvd, Minnetonka, MN 55305 USA
来源
2008 IEEE/PES TRANSMISSION & DISTRIBUTION CONFERENCE & EXPOSITION, VOLS 1-3 | 2008年
关键词
very short term load prediction (VSTLP); Short Term Load Forecast (STLF); neural network (NN); load dynamics; hierarchical neural network; Automatic Generation Control (AGC);
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents novel neural network based very short term load prediction (VSTLP) schemes. The VSTLP has developed and implemented as part of Siemens' CPS based Automatic Generation Control (AGC) Scheme. The load prediction is formulated mathematically to form a basis for the neural network based VSTLP The neural network based VSTLP is different from conventional neural network based Short Term Load Forecast (STLF) in that: (1) VSTLP provides predictions of minutely load for the very near future while STLF forecasts load with a much longer lead time of one hour up to seven days; and (2) The minutely forecasted load values by VSTLP are intended for use in dispatching generation in a predictive manner in real time. The neural network based VSTLP takes into consideration the load dynamics in the immediate past, the variations in load dynamics during the course of a day, and the weather factors as well. Mathematical formulation of the problem and the architecture of the neural network based load prediction schemes are studied. Experimental experiences in this study are also discussed.
引用
收藏
页码:423 / +
页数:2
相关论文
共 50 条
  • [21] Short-Term Load Forecasting Based on RBF Neural Network
    Zhao, Bing
    Liang, Yue
    Gao, Xin
    Liu, Xin
    3RD ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2018), 2018, 1069
  • [22] Neural Network Based Approach for Short-Term Load Forecasting
    Osman, Zainab H.
    Awad, Mohamed L.
    Mahmoud, Tawfik K.
    2009 IEEE/PES POWER SYSTEMS CONFERENCE AND EXPOSITION, VOLS 1-3, 2009, : 1162 - +
  • [23] Artificial neural network based short-term load forecasting
    Munkhjargal, S
    Manusov, VZ
    KORUS 2004, VOL 1, PROCEEDINGS, 2004, : 262 - 264
  • [24] Short-term load forecasting based on fuzzy neural network
    Wang, Cuiru
    Cui, Zhikun
    Chen, Qi
    IITA 2007: WORKSHOP ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, PROCEEDINGS, 2007, : 335 - 338
  • [25] Short-term Load Forecasting Based on BP Neural Network
    Li Yan-bin
    Li Peng
    Li Guan-hong
    ICPOM2008: PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE OF PRODUCTION AND OPERATION MANAGEMENT, VOLUMES 1-3, 2008, : 1182 - 1186
  • [26] Short-term load forecasting based on fuzzy neural network
    DONG Liang
    MU Zhichun (Information Engineering School
    Journal of University of Science and Technology Beijing(English Edition), 1997, (03) : 46 - 48
  • [27] Short Term Load Forecasting based on Improved RBF Neural Network
    Zhang, Hong
    Lei, Zhiguo
    Guo, Jian
    Pian, Zhaoyu
    ENERGY DEVELOPMENT, PTS 1-4, 2014, 860-863 : 2610 - +
  • [28] Study of Artificial Neural Network Based Short Term Load Forecasting
    Webberley, Ashton
    Gao, David Wenzhong
    2013 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PES), 2013,
  • [29] Synergism of Deep Neural Network and ELM for Smart Very-Short-Term Load Forecasting
    Alamaniotis, Miltiadis
    PROCEEDINGS OF 2019 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE (ISGT-EUROPE), 2019,
  • [30] Very Short Term Load Forecasting Based On Meteorological With Modelling k-NN-Feed Forward Neural Network
    Kartini, Unit Three
    Ardianto, Dwi
    Wardani, Laili
    JOURNAL OF ELECTRICAL SYSTEMS, 2019, 15 (01) : 1 - 16