Power system reduced model by artificial neural networks

被引：0
|
作者：
Ramirez, JM [1 ]
机构：
[1] Univ Guadalajara, CINVESTAV, Dept Elect Engn, Guadalajara 44430, Jalisco, Mexico
来源：
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5 | 2005年
关键词：
artificial neural networks; power systems; reduced order models; power system transient stability;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper is aimed to the application of artificial neural networks (ANN) for constructing a power system reduced model, also termed dynamic equivalent. ANN are trained to help in constructing dynamic equivalents, which is considered a bard task in the context of electrical power systems. The main objective is to reproduce the complex voltage at some relevant nodes. The simulation results prove the applicability and robustness of this innovative approach.
引用
收藏
页码：2607 / 2612
页数：6
相关论文
共 50 条
  • [1] Reduced model for power system state estimation using artificial neural networks
    Onwuachumba, Amamihe
    Wu, Yunhui
    Musavi, Mohamad
    [J]. 2013 IEEE GREEN TECHNOLOGIES CONFERENCE, 2013, : 407 - 413
  • [2] Artificial neural networks in power system restoration
    Bretas, AS
    Phadke, AG
    [J]. IEEE TRANSACTIONS ON POWER DELIVERY, 2003, 18 (04) : 1181 - 1186
  • [3] New reduced model approach for power system state estimation using artificial neural networks and principal component analysis
    Onwuachumba, Amamihe
    Musavi, Mohamad
    [J]. 2014 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC), 2014, : 15 - 20
  • [4] Utilization of Artificial Neural Networks to Improve the Accuracy of a Hybrid Power System Model
    Atef, Mohamed
    Abdullah, M. F.
    Khatib, Tamer
    Romlie, M. F.
    [J]. 2019 17TH IEEE STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT (SCORED), 2019, : 284 - 288
  • [5] Power system voltage stability monitoring using artificial neural networks with a reduced set of inputs
    Bahmanyar, A. R.
    Karami, A.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 58 : 246 - 256
  • [6] Artificial neural networks in power system topology recognition
    Delimar, M
    Pavic, I
    Hebel, Z
    [J]. IEEE REGION 8 EUROCON 2003, VOL B, PROCEEDINGS: COMPUTER AS A TOOL, 2003, : 287 - 291
  • [7] Artificial Neural Networks Controller for Power System Voltage Improvement
    Messalti, Sabir
    Boudjellal, Bilal
    Said, Azouz
    [J]. 2015 6TH INTERNATIONAL RENEWABLE ENERGY CONGRESS (IREC), 2015,
  • [8] An application of Artificial Neural Networks in power system load modeling
    Yousefi, GR
    [J]. 2005 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS, 1-3, 2005, : 308 - 313
  • [9] Power system state forecasting using artificial neural networks
    Kumar, DMV
    Srivastava, SC
    [J]. ELECTRIC MACHINES AND POWER SYSTEMS, 1999, 27 (06): : 653 - 664
  • [10] Dynamic Model of a High Power PEM Fuel Cell System on the basis of Artificial Neural Networks
    Chavez, A. U.
    Duron, S. M.
    Arriaga, L. G.
    Munoz, R.
    [J]. 2009 6TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTING SCIENCE AND AUTOMATION CONTROL (CCE 2009), 2009, : 487 - +
12345