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

Abstract
Figure/Table
References (27)
Related Citation (1)

Download: PDF (1642 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

The residual current Device (RCD) is mainly used to protect power supply lines or electrical equipment leakage faults. 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 lower the reject-operation rate and wrong-operation rate. The higher the probability of a normal service state, the lower the probability of a fault state. The reliability block diagram is shown in Fig.A1.

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). The state at the next moment only relates to the current state, which satisfies the 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 Fig.A2.

In general, if the frequency of fault leakage of power supply lines or electrical equipment is low, 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 the RCD reliability level is low, self-inspection can be used to achieve a high frequency of periodic inspections, thereby significantly improving 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 describes the frequency of fault leakage, and the Normal distribution describes 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, a 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, the magnitude of the leakage current, the reliability level of the RCD, and running time as the variables. The probabilities for each running status with and without the inspected RCD are analyzed. The minimum periodic inspection frequency is obtained to ensure the reliability and safety of the power supply system. The simulation results not only explain 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 the Markov process can describe the actual operation of RCD.

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

Received: 20 June 2022

PACS:

TM56

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	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, 2023, 38(18): 5061-5076.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.221171 OR https://dgjsxb.ces-transaction.com/EN/Y2023/V38/I18/5061

[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(1): 122-124.
Gao Jiexin.Application analysis of leakage circuit breaker in ground power supply system of Changcun coal mine[J]. Mechanical & Electrical Engineering Technology, 2019, 48(1): 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]. 电工技术学报, 2022, 37(9): 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(9): 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(2): 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(2): 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(2): 36-43.
Wei Yongxiang, Chen Jianjun, Ma Hongbo, et al.Dynamic reliability analysis of elastic linkage mech-anism with stochastic parameters under stationary random excitation[J]. Journal of Mechanical Engin-eering, 2012, 48(2): 36-43.
[6] Song J, Der Kiureghian A.Joint first-passage pro-bability and reliability of systems under stochastic excitation[J]. Journal of Engineering Mechanics, 2006, 132(1): 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(5): 1588-1594.
Peng Wenhao, Lu Jun, Feng Yongjun, et al.Optimization method of demand response strategy considering user participation uncertainty[J]. Power System Technology, 2018, 42(5): 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, 34(3): 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, 34(3): 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(6): 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 Tech-nology, 2018, 14(6): 134-141.
[10] Zhang Hailong, Zhang Tinghui, Shen Shuyu, et al.Reliability analysis of a novel magneto-rheological regenerative suspension system under road excita-tion[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): 4037-4046.
Yang Moyuan, Ouyang Sen, Zhang Zhen, et al.Reliability model of multi-port DC circuit breaker considering different operating states[J]. Power System Technology, 2021, 45(10): 4037-4046.
[12] Prodanov P I, Dankov D D.Applying Markov analysis for reliability modeling of energy storage devices[C]//2020 XI National Conference with International Participation (ELECTRONICA), Sofia, Bulgaria, 2021: 1-4.
[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(6): 753-756.
Yu Mingli, Cui Lirong.Modeling and analysis of two-stage directed network Markov repairable system[J]. Transactions of Beijing Institute of Technology, 2011, 31(6): 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(1): 150-158.
Ni Wei, Lü Lin, Xiang Yue, et al.Reliability evaluation of comprehensive energy system based on Markov process Monte Carlo method[J]. Power System Technology, 2020, 44(1): 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, 28(4): 9-15.
Shi Wenhui, Bie Zhaohong, Wang Xifan.Appli-cations of Markov chain Monte Carlo in large-scale system reliability evaluation[J]. Proceedings of the CSEE, 2008, 28(4): 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(2): 697-703.
Zhao Zhixin, Tang Hui, Liu Renyun.Reliability analysis of wind power system based on Markov process[J]. Journal of Jilin University (Engineering and Technology Edition), 2021, 51(2): 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(增刊1): 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] Khalilnejad A, Pour M M, Zarafshan E, et al.Long term reliability analysis of components of photo-voltaic system based on Markov process[C]//SoutheastCon, Norfolk, VA, USA, 2016: 1-5.
[20] Tan Yifang, Feng Ding.Reliability evaluation for unmanned aerial vehicle components based on Markov degradation process[C]//IEEE Advanced Infor-mation Management, Communicates, Electronic and Automation Control Conference (IMCEC), Xi'an, China, 2017: 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 breaker 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]. 济南: 山东大学, 2015.
[23] Ghaderi A, Haghifam M R, Mostafa Abedi S.Application of Monte Carlo simulation in Markov process for reliability analysis[C]//IEEE 11th Inter-national Conference on Probabilistic Methods Applied to Power Systems, Singapore, 2010: 293-298.
[24] 潘仲立. 可靠性分析的理论基础[M]. 北京: 水利电力出版社, 1988.
[25] Ugurlu O F, Kumral M.Reliability-based perfor-mance analysis of mining drilling operations through Markov chain Monte Carlo and mean reverting process simulations[J]. Simulation, 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(1): 6-15.
Guo Yifan, Tang Jiayin.Comprehensive evaluation model of competitive failure reliability with atten-uated random shock[J]. Journal of Hubei University (Natural Science Edition), 2021, 43(1): 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 quanti-fication[J]. Transactions of China Electrotechnical Society, 2021, 36(18): 3776-3786.