• HOME
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • Chinese
Site search        
文章摘要
高压输电线路故障测距综合优化方法研究
Research on the comprehensive optimization method?of the fault location of the high-voltage transmission line
Received:August 02, 2016  Revised:August 02, 2016
DOI:
中文关键词: 神经网络  故障测距  优化评估  输电线路  
英文关键词: Neural network  Fault location  Optimized evaluation  Transmission line  
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
Author NameAffiliationE-mail
SHEN Yuan* Electric?Power?Research?Institute of Yun Nan Power Grid lej01@mails.tsinghua.edu.cn 
JIANGZhi-bo Wuhan NARI Limited Company of NARI Group Corporation 2234861084@qq.com 
HUANG Xiu-qian Yun Nan Power Grid 1540641364@qq.com 
SONG Wen-bo Yun Nan Power Grid 823796962@qq.com 
WANG Ke Electric?Power?Research?Institute of Yun Nan Power Grid 18672838112@qq.com 
HEI Ying-dun Electric?Power?Research?Institute of Yun Nan Power Grid 467634341@qq.com 
Hits: 2016
Download times: 450
中文摘要:
      提高高压输电线路故障定位精度有助于及时排查故障并修复供电,对于提高系统供电可靠性,保证电网安全稳定运行能力具有重要现实意义。本文采用BP神经网络对现有各种测距手段提供的测距结果信息进行综合,对故障测距结果进行优化评估,提高故障测距精度。分别给出了以故障实际距离和故障测距误差为输出的两种综合模型,以仿真计算和实际系统测距数据作为训练样本对神经网络进行训练,进行了两种模型适用性的分析。实际应用结果表明,所提出故障测距综合优化方法可充分综合利用各测距方法的优点,有效提高了故障定位精度。
英文摘要:
      Improving the fault location accuracy of high voltage transmission line is helpful to find the fault location and repair it in time, and is of great significance to improve the power supply reliability, and guarantee a safe and stable operation of power grid. In this paper, the BP neural network is adopt to comprehensively integrate the fault location information of different ranging method, and then evaluate the fault distance optimally to improve the accuracy of fault location. Two integrated models that take fault distance and fault location error as the output respectively, are built, and the simulation calculation and the actual ranging data are utilized as training samples to train the neural network, and the applicability of these two models are analyzed. The results of practical application show that the proposed fault location comprehensive optimization method can make full use of the advantage of various ranging method, and can effectively improve the accuracy of fault location.
View Full Text   View/Add Comment  Download reader
Close
  • Home
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • 中文页面
Address: No.2000, Chuangxin Road, Songbei District, Harbin, China    Zip code: 150028
E-mail: dcyb@vip.163.com    Telephone: 0451-86611021
© 2012 Electrical Measurement & Instrumentation
黑ICP备11006624号-1
Support:Beijing Qinyun Technology Development Co., Ltd