基于Markov模型的继电保护风险评估体系研究
[Abstract]:With the rapid development of social economy and industry in our country, the power system has the characteristics of high efficiency, new science and technology, large capacity, high voltage, long distance, intelligence and so on. The power consumption scale of the power system is increasing at a high speed. But at the same time, the complexity of power system automation control also brings many unstable factors and risks to its safe and reliable power supply process. Relay protection is the most important link in the whole power supply system, whether it can be normal or not. Stable work is the main basis for ensuring the reliability of electricity. Aiming at the shortcomings of traditional risk assessment and reliability analysis, this paper proposes a 10-state Markov model-based relay protection risk assessment system to evaluate the reliability and risk. The methods of theoretical analysis, system simulation and feedback verification are adopted to carry out in-depth research on the design, installation, debugging, operation and management of relay protection, so as to obtain the first-hand basic data, including the original data, in-depth research on the design, installation, debugging, operation and management of relay protection. Operation condition, maintenance data, management data, etc., and by using big data calculation method based on time series LS-SVM, a model of time varying failure rate of relay protection device based on three parameter Weibull distribution is constructed to calculate the failure rate function of each device. Finally, the risk assessment of the existing relay protection system in Huainan City is carried out, and the results are tested and corrected. In this paper, while analyzing the failure rate of relay protection, the calculation method of failure rate function is given. The calculation of failure rate of relay protection, the assessment of risk and the reliability of relay protection are discussed. The methods to evaluate the system risk and improve the reliability are discussed. According to the experimental results, the potential hidden dangers are discovered in time and the loss is reduced to the maximum extent, so that the management level of the power grid can be improved and the safe and stable operation of the power network can be realized.
【学位授予单位】:安徽理工大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TM77
【相似文献】
相关期刊论文 前6条
1 顾辉;宋笔锋;李晓;;基于Markov模型的地空导弹武器系统可信性评估[J];火力与指挥控制;2008年08期
2 覃庆努;魏学业;韩磊;吴小进;;电子系统的Markov模型和云可靠性评价方法[J];西安交通大学学报;2012年08期
3 岳奎志;侯志强;韩维;贾忠湖;;机群出动能力的Markov模型[J];系统仿真学报;2008年22期
4 韩维;李成;商兴华;;基于Markov模型的机群完好率研究[J];飞机设计;2011年04期
5 王慧锋;张亨;汤陈怀;罗晓明;;SIS中基于Markov模型的诊断模块失效率分析[J];化工自动化及仪表;2013年02期
6 李寿安;郭风;张恒喜;李曙林;李登科;;战伤抢修对飞机战斗力作用的Markov模型[J];战术导弹技术;2006年01期
相关会议论文 前1条
1 汤洪秀;徐利华;林曦晨;汪宏晶;张庆;蔡伟斌;尹平;;多状态Markov模型及其在艾滋病发展过程中的应用[A];2011年中国卫生统计学年会会议论文集[C];2011年
相关硕士学位论文 前7条
1 刘素叶;认知无线电中基于Markov模型的频谱预测算法研究[D];西安电子科技大学;2014年
2 杨迪;基于混合多步Markov模型的位置预测方法研究[D];东北大学;2014年
3 罗倩;基于Markov模型的继电保护风险评估体系研究[D];安徽理工大学;2017年
4 王强;基于Markov模型对益气活血中药干预不稳定性心绞痛支架术后疗效的评价研究[D];中国中医科学院;2012年
5 周宇;基于改进Markov模型的预测推荐系统研究[D];昆明理工大学;2013年
6 鲍俊颖;Markov模型下的融资融券投资策略研究[D];重庆大学;2014年
7 苏玉杰;无线衰落信道的Markov模型[D];北京交通大学;2011年
,本文编号:2435717
本文链接:https://www.wllwen.com/kejilunwen/dianlidianqilunwen/2435717.html