FAST VOLTAGE ESTIMATION USING AN ARTIFICIAL NEURAL-NETWORK

被引:10
|
作者
HSU, YY
YANG, CC
机构
[1] Department of Electrical Engineering, National Taiwan University, Taipei
关键词
SECURITY ASSESSMENT; CONTINGENCY ANALYSIS; BUS VOLTAGE ESTIMATION; ARTIFICIAL NEURAL NETWORK;
D O I
10.1016/0378-7796(93)90054-I
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fast estimation of bus voltages is important for contingency analysis and security assessment of a power system. In this paper, an approach based on artificial neural networks (ANNs) is presented to estimate bus voltages in a very efficient manner. In the design of the ANN, a set of system variables which affect bus voltages most are first selected as the inputs to the ANN using an entropy function. A number of training patterns are then created to train the ANN. The resultant ANN is applied to estimate bus voltages following an outage event in a 30-bus system and in the Taiwan power system. Since accurate bus voltage predictions can be achieved very quickly by the proposed method, it is expected that the developed ANN can provide valuable information for operators in real-time system operation.
引用
收藏
页码:1 / 9
页数:9
相关论文
共 50 条
  • [21] Rainfall estimation using an artificial neural network
    Hsu, K
    Sorooshian, S
    Gao, XG
    Gupta, HV
    FIRST CONFERENCE ON ARTIFICIAL INTELLIGENCE, 1998, : 28 - 32
  • [22] ANALYSIS OF MASTICATORY MUSCLE BURST PATTERNS USING ARTIFICIAL NEURAL-NETWORK
    KIMURA, H
    SATO, T
    YAMADA, Y
    JOURNAL OF DENTAL RESEARCH, 1995, 74 : 513 - 513
  • [23] PREDICTION OF BREAST-CANCER MALIGNANCY USING AN ARTIFICIAL NEURAL-NETWORK
    FLOYD, CE
    LO, JY
    YUN, AJ
    SULLIVAN, DC
    KORNGUTH, PJ
    CANCER, 1994, 74 (11) : 2944 - 2948
  • [24] FORECASTING MONTHLY ELECTRIC-LOAD AND ENERGY FOR A FAST-GROWING UTILITY USING AN ARTIFICIAL NEURAL-NETWORK
    ISLAM, SM
    ALALAWI, SM
    ELLITHY, KA
    ELECTRIC POWER SYSTEMS RESEARCH, 1995, 34 (01) : 1 - 9
  • [25] FAST APPROACH TO ARTIFICIAL NEURAL-NETWORK TRAINING AND ITS APPLICATION TO ECONOMIC LOAD DISPATCH
    SINGH, G
    SRIVASTAVA, SC
    KALRA, PK
    KUMAR, DMV
    ELECTRIC MACHINES AND POWER SYSTEMS, 1995, 23 (01): : 13 - 24
  • [26] DAILY ELECTRIC-LOAD FORECASTING USING ARTIFICIAL NEURAL-NETWORK
    ISHIDA, T
    TAMURA, S
    ELECTRICAL ENGINEERING IN JAPAN, 1995, 115 (06) : 52 - 61
  • [27] NOVEL CLUSTERING METHOD FOR COHERENCY IDENTIFICATION USING AN ARTIFICIAL NEURAL-NETWORK
    WANG, MH
    CHANG, HC
    IEEE TRANSACTIONS ON POWER SYSTEMS, 1994, 9 (04) : 2056 - 2062
  • [28] IN-VIVO LIVER DIFFERENTIATION BY ULTRASOUND USING AN ARTIFICIAL NEURAL-NETWORK
    ZATARI, D
    BOTROS, N
    DUNN, F
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 1994, 96 (01): : 376 - 381
  • [29] FLOW OF INFORMATION THROUGH AN ARTIFICIAL NEURAL-NETWORK
    GUIMARAES, PRB
    MCGREAVY, C
    COMPUTERS & CHEMICAL ENGINEERING, 1995, 19 : S741 - S746
  • [30] INTERPRETATION OF NONSTRESS TESTS BY AN ARTIFICIAL NEURAL-NETWORK
    KOL, S
    THALER, I
    PAZ, N
    SHMUELI, O
    AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 1995, 172 (05) : 1372 - 1379