Artificial neural network modeling technique for voltage stability assessment of radial distribution systems

被引:2
|
作者
Hamada, Mohamed M.
Wahab, Mohamed A. A.
Hemdan, Nasser G. A.
机构
关键词
D O I
10.1109/UPEC.2006.367632
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 an Artificial Neural Network (ANN) based modeling technique for predicting the voltage stability of radial distribution systems. The modeling technique is based on a new voltage stability index for assessment of radial distribution systems L(v). The index is implemented to investigate a 33-bus distribution system. An ANN model which has an input layer with two input vectors (P, Q), one hidden layer, and an output layer, which gives the predicted value for the voltage stability. index I, is suggested to predict the value of this index. The performance of the ANN model is tested by using the results of the 33-bus distribution system. Then the ANN model is checked by two model evaluation indices namely mean absolute percentage error and actual percentage error. Plotting of the Simulated results with the ANN output is used to evaluate visually the accuracy Of Simulation. Extensive testing of the proposed ANN based technique have indicated its viability for voltage stability assessment.
引用
收藏
页码:1011 / 1015
页数:5
相关论文
共 50 条
  • [21] Assessment of Voltage Security in a Multi bus Power System Using Artificial Neural Network and Voltage Stability Indicators
    Chakraborty, Kabir
    De, Abhinandan
    Chakrabarti, Abhijit
    JOURNAL OF ELECTRICAL SYSTEMS, 2010, 6 (04) : 517 - 529
  • [22] Artificial neural network and support vector machine approach for locating faults in radial distribution systems
    Thukaram, D
    Khincha, HP
    Vijaynarasimha, HP
    IEEE TRANSACTIONS ON POWER DELIVERY, 2005, 20 (02) : 710 - 721
  • [23] Modeling pollutant concentrations with artificial neural network technique
    College of Transport and Logistics, Dalian Maritime University, Dalian 116026, China
    不详
    Jilin Daxue Xuebao (Gongxueban), 2007, 3 (705-708): : 705 - 708
  • [24] Simple and efficient method for steady-state voltage stability assessment of radial distribution systems
    Hamada, Mohamed M.
    Wahab, Mohamed. A. A.
    Hemdan, Nasser G. A.
    ELECTRIC POWER SYSTEMS RESEARCH, 2010, 80 (02) : 152 - 160
  • [25] A linear static voltage stability margin for radial distribution systems
    Haque, M. H.
    2006 POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-9, 2006, : 917 - 922
  • [26] Artificial neural network to power system voltage stability improvement
    Bansilal
    Thukaram, D
    Kashyap, KH
    IEEE TENCON 2003: CONFERENCE ON CONVERGENT TECHNOLOGIES FOR THE ASIA-PACIFIC REGION, VOLS 1-4, 2003, : 53 - 57
  • [27] Online voltage stability monitoring using Artificial Neural Network
    Nakawiro, Worawat
    Erlich, Istvan
    2008 THIRD INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION AND RESTRUCTURING AND POWER TECHNOLOGIES, VOLS 1-6, 2008, : 941 - 947
  • [28] Voltage Stability Assessment Based on BP Neural Network
    Han, Xiaoqing
    Zheng, Zhijing
    Tian, Nannan
    Hou, Yuanyuan
    2009 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), VOLS 1-7, 2009, : 1032 - +
  • [29] Towards a neural network based voltage stability assessment
    Cory, B.J.
    Knight, U.G.
    Gabellone, L.
    Trovato, M.
    International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, 1996, 4 (01): : 25 - 31
  • [30] Towards a neural network based voltage stability assessment
    Cory, BJ
    Knight, UG
    Gabellone, L
    Trovato, M
    ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 1996, 4 (01): : 25 - 31