Hourly Electric Load Forecasting Algorithm based on Echo State Neural Network

被引:0
|
作者
Song, Qingsong
Zhao, Xiangmo [1 ]
Feng, Zuren [2 ,3 ]
An, Yisheng [1 ]
Song, Baohua [4 ]
机构
[1] Changan Univ, Sch Informat Engn, Xian 710064, Shaanxi, Peoples R China
[2] Xi An Jiao Tong Univ, Syst Engn Int, Xian, Shaanxi, Peoples R China
[3] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Peoples R China
[4] Changqing Drilling Co, Qingyang Petr Machinery Co, Qingyang 745100, Peoples R China
基金
中国国家自然科学基金;
关键词
Hourly electric load prediction; Neural networks; Echo state network; linear regression;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An algorithm for hourly electric load forecasting based on echo state neural networks (ESN) is proposed in this paper. ESN is a new paradigm for using recurrent neural networks (RNNs) with a simpler training method. While the prediction, load patterns are treated as time series signals; no further information is used than the past load data records, such as weather, seasonal variations. The relation between key parameter of the ESN and the predicting performance is discussed; ESN and feedforward neural network (FNN) are compared with the same task also. Simulation experiment results demonstrate that the proposed ESN algorithm is valid and can obtain more accurate predicting results than the FNN for the short-term load prediction problem.
引用
收藏
页码:3893 / 3897
页数:5
相关论文
共 50 条
  • [31] Research on the Short-term Electric Load Forecasting Based on Wavelet Neural Network
    Liu, Tongna
    [J]. 2009 INTERNATIONAL CONFERENCE ON INFORMATION MANAGEMENT, INNOVATION MANAGEMENT AND INDUSTRIAL ENGINEERING, VOL 3, PROCEEDINGS, 2009, : 20 - 23
  • [32] Load forecasting of electric vehicle charging station based on grey theory and neural network
    Feng, Jiawei
    Yang, Junyou
    Li, Yunlu
    Wang, Haixin
    Ji, Huichao
    Yang, Wanying
    Wang, Kang
    [J]. ENERGY REPORTS, 2021, 7 : 487 - 492
  • [33] Hourly Urban Water Demand Forecasting Using the Continuous Deep Belief Echo State Network
    Xu, Yuebing
    Zhang, Jing
    Long, Zuqiang
    Tang, Hongzhong
    Zhang, Xiaogang
    [J]. WATER, 2019, 11 (02)
  • [34] Optimizing of Artificial Neural Network Based on Immune Genetic Algorithm in Power Load Forecasting
    Wang, Yongli
    [J]. NEW CHALLENGES FOR INTELLIGENT INFORMATION AND DATABASE SYSTEMS, 2011, 351 : 329 - 338
  • [35] Short Term Load Forecasting: A Dynamic Neural Network Based Genetic Algorithm Optimization
    Wang, Yan
    Ojleska, Vesna
    Jing, Yuanwei
    K.-Gugulovska, Tatjana
    Dimirovski, Georgi M.
    [J]. PROCEEDINGS OF 14TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE (EPE-PEMC 2010), 2010,
  • [36] Research on power load forecasting of wavelet neural network based on the improved genetic algorithm
    Zhang, Ruihong
    Yu, Zhichao
    [J]. INTERNATIONAL JOURNAL OF AMBIENT ENERGY, 2019, 43 (01) : 1036 - 1040
  • [37] Dynamic Neural Network Based Genetic Algorithm Optimizing for Short Term Load Forecasting
    Wang, Yan
    Jing, Yuanwei
    Zhao, Weilun
    Mao, Yan-e
    [J]. 2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5, 2010, : 2701 - +
  • [38] Object-oriented Genetic Algorithm based Artificial Neural Network for load forecasting
    Lai, LL
    Subasinghe, H
    Rajkumar, N
    Vaseekar, E
    Gwyn, BJ
    Sood, VK
    [J]. SIMULATED EVOLUTION AND LEARNING, 1999, 1585 : 462 - 469
  • [39] Short - Term electric load forecasting using neural network models
    AlRashid, Y
    Paarmann, LD
    [J]. PROCEEDINGS OF THE 39TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS I-III, 1996, : 1436 - 1439
  • [40] Proton exchange membrane fuel cell ageing forecasting algorithm based on Echo State Network
    Morando, Simon
    Jemei, Samir
    Hissel, Daniel
    Gouriveau, Rafael
    Zerhouni, Noureddine
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (02) : 1472 - 1480