Volume 37 Issue 10
Turn off MathJax
Article Contents
Abstract
Related Articles
TIAN Shu, LIU Ying, MEI Xiao-li. Research of Influence of Grid Connection of Distributed Generation on Current Protection of Distribution Network[J]. Journal of Mine Automation, 2011, 37(10): 39-43.
Citation: TIAN Shu, LIU Ying, MEI Xiao-li. Research of Influence of Grid Connection of Distributed Generation on Current Protection of Distribution Network[J]. Journal of Mine Automation, 2011, 37(10): 39-43.
shu

Research of Influence of Grid Connection of Distributed Generation on Current Protection of Distribution Network

  • 1.

    School of Electrical Engineering and Automation of Henan Polytechnic University, Jiaozuo 454003, China. 2.The Third Department of Substation Operation of Zhengzhou Power Supply Company, Zhengzhou 45

More Information
    Graphical Abstract
    • Abstract
  • The paper analyzed influence of grid connection of distributed generation on traditional current protection of distribution network, used Matlab/Simulink simulation software to prove influence of different capacities and grid connected positions of distributed generation on each section of current protection of distribution network, and proposed an improved scheme which can meet with protection requirement of distribution network after grid connection of distributed generation. The implementing principle of the scheme is as follows: for downstream protection of distributed generation, taking power supply of power system and distributed generation as a whole, resetting set values of each section of current protection; for upstream protection of distributed generation, installing a direction relay based on fault current component on each protector, so as to ensure reliable action of protection when over-current relay and direction relay start simultaneously.
    • FullText(HTML)
    • References (0)
    • Related Articles

  • Related Articles

    [1]TIAN Jie, YIN Xiaoqi, WEN Yicheng. Method of cutting trajectory planning of roadheader based on hybrid IWO-PSO algorithm[J]. Journal of Mine Automation, 2021, 47(12): 55-61. DOI: 10.13272/j.issn.1671-251x.2021050018
    [2]CUI Lizhen, XU Fanfei, WANG Qiaoli, GAO Lili. Underground adaptive positioning algorithm based on PSO-BP neural network[J]. Journal of Mine Automation, 2018, 44(2): 74-79. DOI: 10.13272/j.issn.1671-251x.2017090028
    [3]ZHANG Yuwu, XU Huadong, WANG Yingying. Segment data fitting method for support pressure monitoring[J]. Journal of Mine Automation, 2016, 42(2): 51-54. DOI: 10.13272/j.issn.1671-251x.2016.02.013
    [4]LI Jianhong, ZHOU Lawu, XUE Zhengshan. Comprehensive energy-saving control of asynchronous motor based on penalty functio[J]. Journal of Mine Automation, 2014, 40(4): 59-62. DOI: 10.13272/j.issn.1671-251x.2014.04.014
    [5]YOU Wen-jian, LIANG Bing, LI Yin-jun. Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network[J]. Journal of Mine Automation, 2013, 39(2): 47-50.
    [6]PAN Lei, LI Li-juan, DING Ting-ting, LIU Dui. Forecasting of Short-term Power Load Based on Improved PSO Algorithm and LS-SVM[J]. Journal of Mine Automation, 2012, 38(9): 55-59.
    [7]WANG Jian-jun, WANG Shi-ying, LEI Meng. Application of Particle Swarm Optimization Algorithm in Prediction of Coal Calorific Value[J]. Journal of Mine Automation, 2012, 38(5): 50-53.
    [8]GONG Wen, LI Long-qing, XU Yong-gang. Evaluation of Coal Mine Informatization Level Based on Entropy Weight Method and Grey Correlation Degree Method[J]. Journal of Mine Automation, 2012, 38(3): 23-25.
    [9]SUN Jie, HAN Yan, DUAN Yong, CUI Bao-xia. PID Neural Network Control System of Ball Mill Based on Modified PSO Algorithm[J]. Journal of Mine Automation, 2011, 37(5): 59-62.
    [10]AN Feng-shua, . Optimization of PID Controller Parameters Based on Modified Particle Swarm Optimization Algorithm[J]. Journal of Mine Automation, 2010, 36(5): 54-57.

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (40) PDF downloads (8) Cited by()
    Related

    苏ICP备 05016349号-2

    Supported by: Beijing Renhe Information Technology Co., Ltd. Visits：1164426    Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return