Application of An Artificial Neural Network to Study The Transient Stability of An Alternator Connected to Infinite Bus

被引：0
|
作者：
Mandal, Priyaranjan [1 ]
机构：
[1] Univ Calcutta, Dept Appl Phys, Kolkata, India
来源：
PROCEEDINGS OF 2014 1ST INTERNATIONAL CONFERENCE ON NON CONVENTIONAL ENERGY (ICONCE 2014) | 2014年
关键词：
power system stability; transient stability; neural network; training of neural network;
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 uses the neural network theory to study the transient stability. The MATLAB simulink model of an alternator is considered to be connected to an infinite bus. The transient stability of this alternator is studied after a phase fault. The relative rotor angle is taken as the measuring parameter. A neural network based approach is applied to study the transient stability of the same system. This approach gives expected results.
引用
收藏
页码：224 / 227
页数：4
相关论文
共 50 条
  • [21] SIMPLIFIED APPROACH FOR THE STABILITY STUDY, APPLICATION TO THE DAMPED ALTERNATOR
    TOUMI, A
    KAMOUN, MBA
    POLOUJADOFF, M
    JOURNAL DE PHYSIQUE III, 1995, 5 (10): : 1671 - 1688
  • [22] Artificial Neural Network's Application in Intelligent Slop Stability Analysis
    Chen Haiming
    Zhou Shengquan
    Yu Jun
    Chen Haiming
    Yu Jun
    ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL I, PROCEEDINGS, 2009, : 306 - 309
  • [23] Application of artificial neural network expert system to the transient electromagnetic method inversion
    Li, Shi
    Yan, Shu
    Li, Chuang-She
    Zhang, Li-Xin
    Chen, Ming-Sheng
    Meitiandizhi Yu Kantan/Coal Geology & Exploration, 2001, 29 (06):
  • [24] Transient stability evaluation with artificial neural networks
    Celli, G.
    Pilo, F.
    Usai, M.
    Proceedings of the Universities Power Engineering Conference, 1999, 1 : 58 - 61
  • [25] Single machine infinite bus power system transient stability: Software implementation
    Khan, AZ
    ELECTRIC MACHINES AND POWER SYSTEMS, 1998, 26 (07): : 699 - 707
  • [26] Neural network modelling of an artificial boundary for infinite domains
    Ziemianski, L
    COMPUTATIONAL MECHANICS, VOLS 1 AND 2, PROCEEDINGS: NEW FRONTIERS FOR THE NEW MILLENNIUM, 2001, : 1327 - 1332
  • [27] Stability Analysis for a Grid-Forming Converter with Inverse Droop Connected to an Infinite Bus
    Garces, Alejandro
    Gil-Gonzalez, Walter
    2021 IEEE 5TH COLOMBIAN CONFERENCE ON AUTOMATIC CONTROL (CCAC): TECHNOLOGICAL ADVANCES FOR A SUSTAINABLE REGIONAL DEVELOPMENT, 2021, : 286 - 290
  • [28] Application of Artificial Neural Networks in Determining Critical Clearing Time in Transient Stability Studies
    Krishna, D. Rama
    Murthy, K. V. S. Ramachandra
    Rao, G. Govinda
    2008 JOINT INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON) AND IEEE POWER INDIA CONFERENCE, VOLS 1 AND 2, 2008, : 216 - 221
  • [29] The application of neural network controller to power system with SMES for transient stability enhancement
    Demiroren, A.
    Zeynelgil, H. L.
    Sengor, S. N.
    EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, 2006, 16 (06): : 629 - 646
  • [30] A Comparative Study of a Fully-Connected Artificial Neural Network and a Convolutional Neural Network in Predicting Bridge Maintenance Costs
    Wang, Chongjiao
    Yao, Changrong
    Zhao, Siguang
    Zhao, Shida
    Li, Yadong
    APPLIED SCIENCES-BASEL, 2022, 12 (07):
12345