Risk assessment model of relay protection system based on multi-state Bayesian networks

被引:0
|
作者
Xu Changbao [1 ]
Zhao Lijin [1 ]
Wang Yu [1 ]
Huang Liang [1 ]
Jia Yongtian [2 ]
Ying Liming [2 ]
机构
[1] Guizhou Power Grid Corp, Elect Power Res Inst, Guiyang 550000, Guizhou, Peoples R China
[2] Wuhan Univ, Sch Elect Engn, Wuhan 430072, Hubei, Peoples R China
关键词
relay protection system; multiple-state Bayesian networks; failure probability; risk assessment;
D O I
暂无
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
Relay protection is important for power system's stable operation. However, logic state of traditional Bayesian network is simplex. To adapt to the relay protection system operation environment with increasing complexity in current years, a risk assessment model of relay protection system based on multiple-state Bayesian networks is established with dynamic and static indexes. Taking advantages of figurative expression of Bayesian network, the model can express multiple states of system and probability clearly, and also can calculate the risk grade by using qualitative and quantitative analysis of multi-state Bayesian networks.
引用
收藏
页码:1563 / 1567
页数:5
相关论文
共 50 条
  • [1] Probabilistic Risk Assessment of Multi-State Systems Based on Bayesian Networks
    Cao, Jie
    Yin, Baoqun
    Lu, Xiaonong
    [J]. 2016 18TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATIONS TECHNOLOGY (ICACT) - INFORMATION AND COMMUNICATIONS FOR SAFE AND SECURE LIFE, 2016, : 773 - 778
  • [2] Multi-state reliability assessment for hydraulic lifting system based on the theory of dynamic Bayesian networks
    Su, Chun
    Lin, Ning
    Fu, Yequn
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY, 2016, 230 (06) : 533 - 544
  • [3] Risk Assessment of Multi-State Bayesian Network in an Oil Gathering and Transferring System
    Qiu, G. Q.
    Huang, S.
    Zhu, L. L.
    Su, X. H.
    Chen, Y.
    [J]. PRESSURE VESSEL TECHNOLOGY: PREPARING FOR THE FUTURE, 2015, 130 : 1514 - 1523
  • [4] Braking System Multi-state analysis of maglev train based on Bayesian Networks
    Long, Zhiqiang
    Wang, Xinwei
    Fan, Chengxin
    [J]. 2017 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-HARBIN), 2017, : 26 - 33
  • [5] RELIABILITY ANALYSIS OF MULTI-STATE SYSTEM WITH COMMON CAUSE FAILURE BASED ON BAYESIAN NETWORKS
    Mi, Jinhua
    Li, Yanfeng
    Huang, Hong-Zhong
    Liu, Yu
    Zhang, Xiao-Ling
    [J]. EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2013, 15 (02): : 169 - 175
  • [6] Assessment of a multi-state system under a shock model
    Eryilmaz, Serkan
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2015, 269 : 1 - 8
  • [7] RELIABILITY ANALYSIS FOR MULTI-STATE SYSTEM BASED ON TRIANGULAR FUZZY VARIETY SUBSET BAYESIAN NETWORKS
    He, Qin
    Zha, Yabing
    Zhang, Ruijun
    Liu, Tianyu
    Sun, Quan
    [J]. EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2017, 19 (02): : 158 - 165
  • [8] A Bayesian Estimation of Confidence Limits for Multi-state System Vulnerability Assessment With IEMI
    Liu, Yu
    Du, Peibing
    Han, Feng
    Cai, Libing
    Qi, Hongxin
    Xia, Hongfu
    Wang, Jianguo
    [J]. IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, 2022, 64 (04) : 1219 - 1229
  • [9] Bayesian Reliability and Performance Assessment for Multi-State Systems
    Liu, Yu
    Lin, Peng
    Li, Yan-Feng
    Huang, Hong-Zhong
    [J]. IEEE TRANSACTIONS ON RELIABILITY, 2015, 64 (01) : 394 - 409
  • [10] Reliability analysis of monotone coherent multi-state systems based on Bayesian networks
    Song, Binghua
    Zhou, Zhongbao
    Ma, Chaoqun
    Zhou, Jinglun
    Geng, Shaofeng
    [J]. JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2016, 27 (06) : 1326 - 1335