| 基于动态贝叶斯网络的智能变电站监控系统可靠性分析 |
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| 引用本文： | 戴志辉,谢军,陈曦,王增平.基于动态贝叶斯网络的智能变电站监控系统可靠性分析[J].电力系统保护与控制,2018,46(23):68-76. |
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| 作者姓名： | 戴志辉 谢军 陈曦 王增平 |
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| 作者单位： | 河北省分布式储能与微网重点实验室华北电力大学，河北 保定 071003,河北省分布式储能与微网重点实验室华北电力大学，河北 保定 071003,国网保定供电公司，河北 保定 071000,河北省分布式储能与微网重点实验室华北电力大学，河北 保定 071003 |
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| 基金项目： | 国家自然科学基金项目资助(51877084);河北省自然科学基金项目资助(E2018502063);国家重点研发计划专项课题资助(2016YFB0900203);中央高校基本科研业务费资助(2017MS096) |
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| 摘 要： | 通过分析智能变电站监控系统的工作机制,提出运用动态贝叶斯网络评估其可靠性。首先,将监控系统的功能划分为三类,并建立了相应的功能可靠性框图。其次,在建立的功能可靠性框图的基础上,构建了监控系统动态贝叶斯网络模型及其求解方法。最后,以算例验证了所提方法的有效性。结果表明,该方法能较好地描述监控系统的动态特性,为系统的优化配置、故障诊断提供参考。
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| 关 键 词： | 智能变电站 监控系统 动态贝叶斯网络 动态特性 可靠性评估 |
| 收稿时间： | 2017/11/15 0:00:00 |
| 修稿时间： | 2018/2/26 0:00:00 |
Dynamic Bayesian network based reliability evaluation of supervision and control system in smart substations |
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| DAI Zhihui,XIE Jun,CHEN Xi and WANG Zengping.Dynamic Bayesian network based reliability evaluation of supervision and control system in smart substations[J].Power System Protection and Control,2018,46(23):68-76. |
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| Authors: | DAI Zhihui XIE Jun CHEN Xi and WANG Zengping |
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| Affiliation: | Hebei Key Laboratory of Distributed Energy Storage and Microgrid North China Electric Power University, Baoding 071003, China,Hebei Key Laboratory of Distributed Energy Storage and Microgrid North China Electric Power University, Baoding 071003, China,State Grid Baoding Power Supply Company, Baoding 071000, China and Hebei Key Laboratory of Distributed Energy Storage and Microgrid North China Electric Power University, Baoding 071003, China |
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| Abstract: | Based on analysis of operating mechanism of smart Substation Supervision and Control System (SSCS), Dynamic Bayesian Network (DBN) is introduced to evaluate the reliability of SSCS. First, the function of SSCS is divided to three types and the corresponding functional Reliability Block Diagrams (RBD) are established. Secondly, the DBN model and its solution of SSCS are implemented based on the functional RBD. Finally, a study case is presented to demonstrate the effectiveness of the proposed method. The results show that dynamic characteristics of SSCS could be well described by DBN and hence provide reference for the system configuration optimization and fault diagnosis. This work is supported by National Natural Science Foundation of China (No. 51877084), Natural Science Foundation of Hebei Province (No. E2018502063), National Key Research and Development Program of China (No. 2016YFB0900203), and Fundamental Research Funds for the Central Universities (No. 2017MS096). |
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| Keywords: | smart substation supervision and control system dynamic Bayesian network dynamic characteristics reliability evaluation |
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