基于马尔可夫过程的漏电保护器服役状态及其可靠性分析

doi:10.19595/j.cnki.1000-6753.tces.221171

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Abstract

The residual current Device(RCD) is mainly used for the protection of power supply lines or electrical equipment leakage fault. During the service of the RCD, it may occur to the reject-operation or the wrong-operation. If the RCD loses its leakage protection function, the lines or equipment have safety hazards, such as personal electric shock or leakage fire. Therefore, it is necessary to study the reliability of RCD.
If the RCD fails, its fault state is exposed only when the corresponding excitation condition occurs. The higher the reliability level of RCD, the smaller reject-operation rate and wrong-operation rate. The higher the probability of normal service state is, the lower the probability of fault state will be. The reliability block diagram is shown in Figure 1.

The fault state of RCD is divided into two categories: the hidden failure state and the appearing fault state. Therefore, there are five service conditions of RCD: normal service state (state 1), the hidden reject-operation state (state 2), the hidden wrong-operation state (state 3), the appearing reject-operation state (state 4) and the appearing wrong-operation state (state 5). The current moment states corresponding to state 4 and state 5 are necessarily state 2 and state 3, not state 1 (previous state). That is to say, the state at the next moment is only related to the current state, which satisfies Markov property. Markov process can be used to describe the state transfer of RCD. There are safety hazards when RCD is in the hidden failure state, and it is necessary to eliminate the hidden fault state of RCD by periodic inspection. The state transition diagram of RCD based on periodic inspection is shown in Figure 2.

In general, if the frequency of fault leakage of power supply lines or electrical equipment is lower, the RCD in the hidden reject-operation state can be found at a lower periodic inspection frequency. However, the normal leakage of power supply lines or electrical equipment exists permanently, so the probability of the wrong-operation appearance state is still high. If RCD reliability level is lower, the self-inspection can be used to achieve a high frequency of periodic inspections in order to significantly improve the reliability and safety of the power supply system.
In different service environments, the frequency of fault leakage and the residual current are different for power supply lines or electrical equipment. So the service environment can be divided into three grades: good, general and bad. The Poisson distribution is used to describe the frequency of fault leakage, and the Normal distribution is used to describe the amplitude of normal residual current and fault leakage current. Under the same power supply reliability conditions, the higher the reliability level of RCD is, the fewer periodic inspections are required. In addition, periodic inspection can significantly reduce the frequency of replacing the leakage protector due to apparent failure, and can avoid power loss caused by RCD failure.
The simulation experiment takes leakage fault frequency, magnitude of the leakage current, reliability level of the RCD and running time as the variables, and analyzes the probability for each running status of the inspected RCD and the one without inspection. The minimum periodic inspection frequency is obtained to ensure the reliability and safety of power supply system. The simulation results not only explain the phenomenon that the wrong-operation is more than the reject-operation of RCD in actual service, but also prove that the service reliability analysis model of RCD based on Markov process can well describe the actual operation of RCD.

Key words： residual current protection reliability excitation response method Markov process periodic inspection service reliability

PACS:

TM56

	Service

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	Li Kui
	Hao Yunqian
	Zhao Chengchen
	Dai Yihua
	Guan Ruiliang

Cite this article:

Li Kui,Hao Yunqian,Zhao Chengchen等. Service States and Reliability Analysis of Residual Current Device Based on Markov Process[J]. Transactions of China Electrotechnical Society, 0, (): 37-37.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.221171 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/37

[1] 高洁馨. 常村煤矿地面供电系统中漏电断路器的应用分析[J]. 机电工程技术, 2019, 48(01): 122-124.
Gao Jiexin.Application Analysis of Leakage Circuit Breaker in Ground Power Supply System of Changcun Coal Mine[J]. M&E Engineering Technology, 2019, 48(01): 122-124.
[2] 边鑫磊. 温湿度对电子式漏电断路器性能影响的研究[D]. 天津: 河北工业大学, 2017.
[3] 李奎, 李常宇, 牛峰, 等. 电磁式漏电断路器的空间磁场抗扰分析及屏蔽结构设计[J]. 电工技术报, 2022, 37(09): 2161-2169.
Li Kui, Li Changyu, Niu Feng, et al.Anti-Magnetic Field Interference Analysis and Shielding Structure Design of Electromagnetic Residual Current Circuit Breaker[J]. Transactions of China Electrotechnical Society, 2022, 37(09): 2161-2169.
[4] 刘帼巾, 李想, 王泽, 等. 基于Wiener过程电子式漏电断路器的剩余寿命预测[J]. 电工技术学报, 2022, 37(02): 528-536.
Liu Guojin, Li Xiang, Wang Ze, et al.Remaining Life Prediction of Electronic Residual Current Circuit Breaker Based on Wiener Process[J]. Transactions of China Electrotechnical Society, 2022, 37(02): 528-536.
[5] 魏永祥, 陈建军, 马洪波, 等. 随机参数弹性连杆在平稳随机激励下的动力可靠性分析[J]. 机械工程学报, 2012, 48(02): 36-43.
Wei Yongxiang, Chen Jianjun, Ma Hongbo, et al.Dynamic Reliability Analysis of Elastic Linkage Mechanism with Stochastic Parameters under Stationary Random Excitation[J]. Journal of Mechanical Engineering, 2012, 48(02): 36-43.
[6] Joint Song, Armen Der Kiureghian.Joint First-Passage Probability and Reliability of Systems under Stochastic Excitation[J]. Journal of Engineering Mechanics, 2006, 132(01): 65-77.
[7] 彭文昊, 陆俊, 冯勇军, 等. 计及用户参与不确定性的需求响应策略优化方法[J]. 电网技术, 2018, 42(05): 1588-1594.
Peng Wenhao, Lu Jun, Feng Yongjun, et al.A Demand Response Strategy Optimization Considering User Participation Uncertainty[J]. Power System Technology, 2018, 42(05): 1588-1594.
[8] 金有刚, 姚军. 随机振动环境下电路板的疲劳寿命与可靠性研究[J]. 强度与环境, 2007(03): 58-62.
Jin Yougang, Yao Jun.The method research on fatigue life analysis and reliability of the typical circuit board in random-vibration environment[J]. Structure & Environment Engineering, 2007(03): 58-62.
[9] 张鹏, 王艺环, 秦国晋. 非随机过程的地震激励下埋地压力管道的非概率可靠性分析[J]. 中国安全生产科学技术, 2018, 14(06): 134-141.
Zhang Peng, Wang Yihuan, Qin Guojin.Non-probabilistic reliability analysis of buried pressure pipeline under non-random process earthquake excitation[J]. Journal of Safety Science and Technology, 2018, 14(06): 134-141.
[10] Hailong Zhang, Tinghui Zhang, Shuyu Shen, et al.Reliability analysis of a Novel Magneto-rheological Regenerative Suspension System under Road Excitation[C]//2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Auckland, New Zealand, 2018: 1033-1038.
[11] 杨墨缘, 欧阳森, 张真, 等. 考虑不同运行状态的多端口直流断路器可靠性模型[J]. 电网技术, 2021, 45(10): 4037-4049.
Yang Moyuan, Ou Yangsen, Zhang Zhen, et al.Reliability Model of Multi-terminal DC Circuit Breaker Considering Different Operation States[J]. Power System Technology, 2021, 45(10): 4037-4049.
[12] Prodan Ivanov Prodanov, Dobroslav Danailov Dankov.Applying Markov Analysis for Reliability Modeling of Energy Storage Devices[C]//XI National Conference with International Participation "Electronica 2020", Sofia, Bulgaria, 2020.
[13] 于明丽, 崔利荣. 两阶段有向网络马尔可夫系统维修模型与分析[J]. 北京理工大学学报, 2011, 31(06): 753-756.
Yu Mingli, Cui Lirong.Modeling and Analysis of Two-Stage Directed Network Markov Pepairable System[J]. Transactions of Beijing Institute of Technology, 2011, 31(06): 753-756.
[14] 倪伟, 吕林, 向月, 等. 基于马尔可夫过程蒙特卡洛法的综合能源系统可靠性评估[J]. 电网技术, 2020, 44(01): 150-158.
Ni Wei, Lv Lin, Xiang Yue, et al.Reliability Evaluation of Integrated Energy System Based on Markov Process Monte Carlo Method[J]. Power System Technology, 2020, 44(01): 150-158.
[15] 石文辉, 别朝红, 王锡凡. 大型电力系统可靠性评估中的马尔可夫链蒙特卡洛方法[J]. 中国电机工程学报, 2008(04): 9-15.
Si Wenhui, Bie Zhaohong, Wang Xifan.Applications of Markov Chain Monte Carlo in Large-scale System Reliability Evaluation[J]. Proceedings of the CSEE, 2008(04): 9-15.
[16] 赵志欣, 唐慧, 刘仁云. 基于马尔可夫过程的风电系统可靠性分析[J]. 吉林大学学报(工学版), 2021, 51(02): 697-703.
Zhao Zhixin, Tang Hui, Liu Rengyun.Reliability analysis of wind power generation system based on Markov process[J]. Journal of Jilin University (Engineering and Technology Edition), 2021, 51(02): 697-703.
[17] 边晓燕, 史越奇, 裴传逊, 等. 计及经济性和可靠性因素的区域综合能源系统双层协同优化配置[J]. 电工技术学报, 2021, 36(21): 4529-4543.
Bian Xiaoyan, Shi Yueqi, Pei Chuanxun, et al.Bi-Level Collaborative Configuration Optimization of Integrated Community Energy System Considering Economy and Reliability[J]. Transactions of China Electrotechnical Society, 2021, 36(21): 4529-4543.
[18] 赵书涛, 王波, 华回春, 等. 基于马尔科夫模型的直流断路器可靠性评估方法[J]. 电工技术学报, 2019, 34(S1): 126-132.
Zhao Shutao, Wang Bo, Hua Huichun, et al.Reliability Evaluation Method of DC Circuit Breaker Based on Markov Model[J]. Transactions of China Electrotechnical Society, 2019, 34(S1): 126-132.
[19] Arash Khalilnejad, Student Member, Maneli Malek Pour, et al.Long term reliability analysis of components of photovoltaic system based on Markov process[C]//SoutheastCon 2016, Norfolk, VA, USA, 2016: 1-5.
[20] Yifang Tan, Ding Feng.Reliability Evaluation for Unmanned Aerial Vehicle Components Based on Markov Degradation Process[C]//2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Xi'an, China, 2016: 1804-1807.
[21] 刘帼巾, 王泽, 李想, 等. 基于改进Bootstrap-Bayes的电子式剩余电流动作断路器可靠性评估[J]. 电工技术学报, 2022, 37(16): 4250-4258. Liu Guojin, Wang Ze, Li Xiang, et al. Reliability Evaluation of Electronic Residual Current Operated Circuit Breakers Based on Improved Bootstrap-Bayes[J]. Transactions of China Electrotechnical Society, 2022, 37(16): 4250-4258.
[22] 李谦. 计及极端天气与风电接入的系统运行风险评估[D]. 山东: 山东大学, 2015.
[23] A. Ghaderi, M. R. Haghifam, S. Mostafa Abedi.Application of Monte Carlo Simulation in Markov Process for Reliability Analysis[C]//2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, Singapore, 2010.
[24] 潘仲立. 可靠性分析的理论基础[M]. 北京: 水力电力出版社, 1988: 66-70.
[25] Omer Faruk Ugurlu, Mustafa Kumral.Reliability-based performance analysis of mining drilling operations through Markov chain Monte Carlo and mean reverting process simulations[J]. Transactions of the Society for Modeling and Simulation International, 2020, 96(7): 593-604.
[26] 郭一帆, 唐家银. 伴有衰减型随机冲击的竞争失效可靠性综合评估模型[J]. 湖北大学学报(自然科学版), 2021, 43(01): 6-15.
Guo Yifan, Tang Jiayin.Comprehensive evaluation model of competitive failure reliability with attenuated random shock[J]. Journal of Hubei University( Natural Science), 2021, 43(01): 6-15.
[27] 赵营鸽, 李颖, 王灵月, 等. 基于均值点展开的单变元降维法在EIT不确定性量化研究中的应用[J]. 电工技术学报, 2021, 36(18): 3776-3786.
Zhao Yingge, Li Ying, Wang Lingyue, et al.The Application of Univariate Dimension Reduction Method Based on Mean Point Expansion in the Research of Electrical Impedance Tomography Uncertainty Quantification[J]. Transactions of China Electrotechnical Society, 2021, 36(18): 3776-3786.