基于比例强度模型的风电机组优化检修策略研究
|
摘要
本文首先介绍了风电机组优化检修实施的背景和重要意义。然后介绍了与电力系统设备优化检修相关的一些基本的理论知识。叙述了可靠性理论中的可靠性、失效、分布的定义及内涵;介绍了几个常用的可靠性指标,包括失效率,可靠度以及平均寿命;简要介绍了威布尔分布的概念以及极大似然估计法的基本步骤。
研究了比例失效模型的概念及模型的建立过程,提出了利用该模型对风电机组制定优化检修决策的方法。详细分析了不同类型的比例失效模型的参数估计方法,并在MATLAB平台上编程实现了模型的极大似然参数估计。阐述了如何利用最小成本法或最大可用度法计算最优预防维修间隔,进而可算出最优维修阈值,并在维修决策图中绘制出最优维修阈值曲线,利用状态监测数据在维修决策图中描点,得到最优维修策略。利用风电机组主轴、主轴承的故障数据和状态监测数据,给出了具体的制定优化检修策略的过程。
介绍了比例强度模型的概念及模型的建立过程,阐述了利用该模型对风电机组制定优化检修决策的步骤。对比例强度模型的参数估计方法进行了详细分析,并对模型编程实现了参数估计。阐述了最小成本法和最大可用度法,并利用最小成本法计算最优预防维修间隔,算出最优维修阈值,在维修决策图中绘制最优维修阈值曲线,利用状态监测数据在维修决策图中描点,进而得到最优维修策略。利用风电机组齿轮箱、发电机的故障数据和状态监测数据,实现了制定优化检修策略的具体过程。
This thesis firstly introduced the background and significance of the implementation of maintenance optimization about wind turbine-generator system. Then it introduced some basic theoretical knowledge which are related to optimization maintenance of power system equipment, described some parts of the theory of reliability, such as the definitions and connotations of reliability ,failure, distribution, introduced several common reliability indexes, including the failure rate, reliability and life expectancy, briefly introduced the concept of the weibull distribution and the basic steps of maximum likelihood estimation method.
The paper studied the concept of proportional hazards model and the process of the model established , put forward optimization maintenance decision based on the model for the wind generator , detailed analysised the parameter estimation methods of different types of proportional hazards model, and realized the maximum likelihood parameter estimation of the model in MATLAB, expounded how to calculate the optimum preventive maintenance interval by the minimum cost method or maximum availability method, then calculated the optimal maintenance threshold, mapped out the optimal maintenance threshold curve in maintenance decision diagram, traced points by using state monitoring datas in maintenance decision diagram, gettd the optimal strategy of maintenance. It realized the specific process of formulating optimization maintenance strategies by using the failure datas and condition monitoring datas of the shaft and the main bearings of the wind generator.
The thesis introduced the concept of proportional intensity model and the process of the model established, described the optimization maintenance decision steps using the model for the wind generator, analyzed the parameter estimation method of proportional intensity model in detail, realized the parameter estimation by programming for the model. It expounded the minimum cost method and maximum availability method, calculated the optimum preventive maintenance intervals by using minimum cost method, then can calculate the optimal maintenance threshold, painted the optimal maintenance threshold curve in maintenance decision figure, traced points by using state monitoring data in maintenance decision diagram, and then got the optimal strategy of maintenance.The paper achieved the concrete process of optimized maintenance strategy by using the fault data and condition monitoring data of wind generator gearing box and generator.
研究了比例失效模型的概念及模型的建立过程,提出了利用该模型对风电机组制定优化检修决策的方法。详细分析了不同类型的比例失效模型的参数估计方法,并在MATLAB平台上编程实现了模型的极大似然参数估计。阐述了如何利用最小成本法或最大可用度法计算最优预防维修间隔,进而可算出最优维修阈值,并在维修决策图中绘制出最优维修阈值曲线,利用状态监测数据在维修决策图中描点,得到最优维修策略。利用风电机组主轴、主轴承的故障数据和状态监测数据,给出了具体的制定优化检修策略的过程。
介绍了比例强度模型的概念及模型的建立过程,阐述了利用该模型对风电机组制定优化检修决策的步骤。对比例强度模型的参数估计方法进行了详细分析,并对模型编程实现了参数估计。阐述了最小成本法和最大可用度法,并利用最小成本法计算最优预防维修间隔,算出最优维修阈值,在维修决策图中绘制最优维修阈值曲线,利用状态监测数据在维修决策图中描点,进而得到最优维修策略。利用风电机组齿轮箱、发电机的故障数据和状态监测数据,实现了制定优化检修策略的具体过程。
This thesis firstly introduced the background and significance of the implementation of maintenance optimization about wind turbine-generator system. Then it introduced some basic theoretical knowledge which are related to optimization maintenance of power system equipment, described some parts of the theory of reliability, such as the definitions and connotations of reliability ,failure, distribution, introduced several common reliability indexes, including the failure rate, reliability and life expectancy, briefly introduced the concept of the weibull distribution and the basic steps of maximum likelihood estimation method.
The paper studied the concept of proportional hazards model and the process of the model established , put forward optimization maintenance decision based on the model for the wind generator , detailed analysised the parameter estimation methods of different types of proportional hazards model, and realized the maximum likelihood parameter estimation of the model in MATLAB, expounded how to calculate the optimum preventive maintenance interval by the minimum cost method or maximum availability method, then calculated the optimal maintenance threshold, mapped out the optimal maintenance threshold curve in maintenance decision diagram, traced points by using state monitoring datas in maintenance decision diagram, gettd the optimal strategy of maintenance. It realized the specific process of formulating optimization maintenance strategies by using the failure datas and condition monitoring datas of the shaft and the main bearings of the wind generator.
The thesis introduced the concept of proportional intensity model and the process of the model established, described the optimization maintenance decision steps using the model for the wind generator, analyzed the parameter estimation method of proportional intensity model in detail, realized the parameter estimation by programming for the model. It expounded the minimum cost method and maximum availability method, calculated the optimum preventive maintenance intervals by using minimum cost method, then can calculate the optimal maintenance threshold, painted the optimal maintenance threshold curve in maintenance decision figure, traced points by using state monitoring data in maintenance decision diagram, and then got the optimal strategy of maintenance.The paper achieved the concrete process of optimized maintenance strategy by using the fault data and condition monitoring data of wind generator gearing box and generator.
引文
[1]魏林君,迟永宁,赵建国等.双馈变速风电机组低电压穿越控制[J].电网与清洁能源,2009,25(2):41-45.
[2]舒进,郝志国,张宝会等.孙建远.改善接入系统同步稳定性的变速风电机组控制[J].电力系统自动化,2009,33(7):65-70.
[3]朴海国,王志新.风电机组偏航Fuzzy-PID合成控制系统仿真[J].电工技术学报,2009,24(3):183-202.
[4]林今,李国杰,孙元章等.双馈风电机组的小信号分析及其控制系统的参数优化[J].电力系统自动化.2009, 33(5):86-95.
[5]秦世耀,李庆,王伟等.基于PC测量仪器的风电机组电能质量测试系统[J].电网与清洁能源,2009,25(1):36-39.
[6]黄弦超,舒隽,张粒子等.免疫禁忌混合智能优化算法在配电网检修优化中的应用,中国电机工程学报,2004,24(11):96-100.
[7]将献伟,黄民翔,许诺等.供电设备检修计划优化,电力系统及其自动化学报,2007,19(4):116-120.
[8]张道乾,王思印.供电企业状态检修现状与展望,高电压技术,2006,32(1)114-118.
[9]李明华,研璋,薛随敬等.我国电力系统状态检修开展状况统计,中国电力,2005,38(12):33-36.
[10]赵振宇,郑浦水,徐元载.火电厂实施状态检修的意义与方法,华北电力技术,2003,3:46-49.
[11]程志华,章剑光.状态检修技术及其辅助分析系统的应用,电网技术,2007,27(7):16-24.
[12]余杰,周浩,黄春光.以可靠性为中心的检修策略,高电压技术,2005,31(6):27-28.
[13]郭云鹏,黄民翔,许旭锋.输变电设备的检修策略,华东电力技术,2006,34(12):36-40.
[14] R.Eshraghnia, MH.Modir Shanechi, H.Rajabi Mashhadi. A new approach for maintenance scheduling of generating units in power market[C]. 9th international conference on Probabilistic methods applied to power systems, Sweden, 2006,11-15.
[15] Neil Montgomery, Tommie Lindquist, Marie-Agnes Garnero, et al. Reliability functions and optimal decisions using condition data for EDF primary pumps[C].9th International Conference on Probabilistic Methods to Power Systems.2006,33-36.
[16] Huamin Liu. Reliability of a Load-Sharing k-out-of-n:G System:Non-iid Components with Arbitrary Distributions[J]. IEEE TRANSACTIONS ON RELIABILITY.1998,47(3):279-284.
[17] N.Hou. The infrared thermography diagnostic technique for high-voltage electric equipment with internal fault[C]. In Pro. of IEEE powercon, 1988,110-115.
[18] C.Sweetser, W.J.Bergman, G.Montillet, et al. Strategies for selecting monitoring of circuit breakers[J]. IEEE Transaction on power delivery, 2002, 17(3):742-746.
[19] G.C.Montanari, L.Simoni. Aging phenomenology and modeling[J]. IEEE transaction on Electric Insulation, 1993, 28(5):755-776.
[20] Dhananjay Kumar, Ulf Westberg. Proportional Hazards Modeling of Time-Dependent Covariates Using Linear Regression: A Case Study[J].IEEE TRANSACTIONS ON RELIABILITY.1996,45(3):386-392.
[21] P.Hilber, V.Mirando, M.matos, et al. Multiobjective optimization applied to maintenance policy for electrical networks[J]. IEEE transaction on power systems, 2007, 22(4):1675-1682.
[22] G.Cliteur. Maintenance as a strategic tool for asset management[S]. IEEE tutorial on asset management-maintenance and replacement strategies. 2007.
[23] L.Bertling. RCM and its extension into a quantitative approach RCAM[S]. IEEE tutorial on asset management-maintenance and replacement strategies.2007.
[24] G.J.Anders. Computer program for decision support in the management of equipment maintenance[S]. IEEE tutorial on asset management-maintenance and replacement strategies. 2007.
[25] R.miler. The present status of maintenance strategies and the impact of maintenance on reliability [J]. IEEE transaction on power systems, 2001, 16(4):638-646.
[26] Thomas L. Landers,Homa E. Soroudi. Robustness of a Semi-Parametric Proportional Intensity Model[J]. IEEE Transactions on Reliability. 1991, 40(2): 161-164.
[27] Shwu-Tzy Jiang,Thomas L.Landers,and Teri Reed Rhoads. Assessment of Repairable–System Reliability Using Proportional Intensity Models: A Review[J]. IEEE Transactions on Reliability, 2006,55(2):328-336.
[28] Diederik Lugtigheid, Dragan Banjuevic, Andrew K.S. Jardine. Component repairs: when to perform and what to do?[C].Relaiability and Maintainability Symposium,2005,398-403.
[29] Min Luo, Tongmin Jiang. Step Stress Accelerated Life Testing data analysis for repairable system using proportional intensity model[C]. Reliability and Maintainability Symposium,2009, 360-364.
[30] Huairrui Guo, Wenbiao Zhao, Adamantios Mettas. Practical methods for modeling repairable systems with time trends and repair effects[C]. Reliability and Maintainability Symposium.Jan.2006, 182-188.
[31] Kumar.D. Westberg.U. Proportional hazards modeling of time-dependent covariates using linear regression :a case study[mine power cable reliability][J]. IEEE Transactions on Reliability.1996, 45(3):386-392.
[32] Shibata. k,Rinsaka,k, Dohi,T. Metrics-Based Software Reliability Models Using Non-homogeneous Poisson Processes[C].17th International Symposium on Software Reliability Enginneering.2006,52-61.
[33] Prasad.P.V.N, Rao.K.R.M. Failure analysis and replacement strategies of distribution transformers using proportional hazard modeling[C]. Reliability and Maintainability Symposium.2003, 523-527.
[34] Tsujitani.M, Sakon.M. Analysis of Survival Data Having Time-Dependent Covariates[J].IEEE Transaction on Neural Networds.2009,20(3):389-394.
[35] Hougaard.P. Fitting a multivariate failure time distribution[J]. IEEE Transactions on Reliability.1989, 38(4):444-448.
[36] Chan.C.K. A proportional hazards approach to correlate SiO2-breakdown voltage and time distributions[J].IEEE Transactions on Reliability.1990,39(2):147-150.
[37] Elsayed.E.A.,Chan.C.K. Estimation of thin-oxide reliability using proportional hazards models[J]. IEEE Transactions on Reliability.1990, 39(3):329-335.
[38] Huamin Liu. Reliability of a load-sharing k-out-of-n:G system: non-iid components witharbitray distributions[J].IEEE Transactions on Reliability.1998,47(3):279-284.
[39] Xiao-lan Deng, Ting Wang. Stock Market Factors and Risk of Financial Distress: An Empirical Analysis Using Cox proportional Hazard Model[C].4th international Conference on Wireless Communications, Networking and Mobile Computing.2008, 1-4.
[40] Mazzuchi.T.A, Soyer.R, Spring.R.V. The proportional hazards model in reliability[C]. Reliability and Maintianability Symposium.1989, 252-256.
[41] Makis V, Jardine A K S. Optimal replacement in the proportional hazards model[J]. INFOR, 1991, 30(3): 172-83.
[2]舒进,郝志国,张宝会等.孙建远.改善接入系统同步稳定性的变速风电机组控制[J].电力系统自动化,2009,33(7):65-70.
[3]朴海国,王志新.风电机组偏航Fuzzy-PID合成控制系统仿真[J].电工技术学报,2009,24(3):183-202.
[4]林今,李国杰,孙元章等.双馈风电机组的小信号分析及其控制系统的参数优化[J].电力系统自动化.2009, 33(5):86-95.
[5]秦世耀,李庆,王伟等.基于PC测量仪器的风电机组电能质量测试系统[J].电网与清洁能源,2009,25(1):36-39.
[6]黄弦超,舒隽,张粒子等.免疫禁忌混合智能优化算法在配电网检修优化中的应用,中国电机工程学报,2004,24(11):96-100.
[7]将献伟,黄民翔,许诺等.供电设备检修计划优化,电力系统及其自动化学报,2007,19(4):116-120.
[8]张道乾,王思印.供电企业状态检修现状与展望,高电压技术,2006,32(1)114-118.
[9]李明华,研璋,薛随敬等.我国电力系统状态检修开展状况统计,中国电力,2005,38(12):33-36.
[10]赵振宇,郑浦水,徐元载.火电厂实施状态检修的意义与方法,华北电力技术,2003,3:46-49.
[11]程志华,章剑光.状态检修技术及其辅助分析系统的应用,电网技术,2007,27(7):16-24.
[12]余杰,周浩,黄春光.以可靠性为中心的检修策略,高电压技术,2005,31(6):27-28.
[13]郭云鹏,黄民翔,许旭锋.输变电设备的检修策略,华东电力技术,2006,34(12):36-40.
[14] R.Eshraghnia, MH.Modir Shanechi, H.Rajabi Mashhadi. A new approach for maintenance scheduling of generating units in power market[C]. 9th international conference on Probabilistic methods applied to power systems, Sweden, 2006,11-15.
[15] Neil Montgomery, Tommie Lindquist, Marie-Agnes Garnero, et al. Reliability functions and optimal decisions using condition data for EDF primary pumps[C].9th International Conference on Probabilistic Methods to Power Systems.2006,33-36.
[16] Huamin Liu. Reliability of a Load-Sharing k-out-of-n:G System:Non-iid Components with Arbitrary Distributions[J]. IEEE TRANSACTIONS ON RELIABILITY.1998,47(3):279-284.
[17] N.Hou. The infrared thermography diagnostic technique for high-voltage electric equipment with internal fault[C]. In Pro. of IEEE powercon, 1988,110-115.
[18] C.Sweetser, W.J.Bergman, G.Montillet, et al. Strategies for selecting monitoring of circuit breakers[J]. IEEE Transaction on power delivery, 2002, 17(3):742-746.
[19] G.C.Montanari, L.Simoni. Aging phenomenology and modeling[J]. IEEE transaction on Electric Insulation, 1993, 28(5):755-776.
[20] Dhananjay Kumar, Ulf Westberg. Proportional Hazards Modeling of Time-Dependent Covariates Using Linear Regression: A Case Study[J].IEEE TRANSACTIONS ON RELIABILITY.1996,45(3):386-392.
[21] P.Hilber, V.Mirando, M.matos, et al. Multiobjective optimization applied to maintenance policy for electrical networks[J]. IEEE transaction on power systems, 2007, 22(4):1675-1682.
[22] G.Cliteur. Maintenance as a strategic tool for asset management[S]. IEEE tutorial on asset management-maintenance and replacement strategies. 2007.
[23] L.Bertling. RCM and its extension into a quantitative approach RCAM[S]. IEEE tutorial on asset management-maintenance and replacement strategies.2007.
[24] G.J.Anders. Computer program for decision support in the management of equipment maintenance[S]. IEEE tutorial on asset management-maintenance and replacement strategies. 2007.
[25] R.miler. The present status of maintenance strategies and the impact of maintenance on reliability [J]. IEEE transaction on power systems, 2001, 16(4):638-646.
[26] Thomas L. Landers,Homa E. Soroudi. Robustness of a Semi-Parametric Proportional Intensity Model[J]. IEEE Transactions on Reliability. 1991, 40(2): 161-164.
[27] Shwu-Tzy Jiang,Thomas L.Landers,and Teri Reed Rhoads. Assessment of Repairable–System Reliability Using Proportional Intensity Models: A Review[J]. IEEE Transactions on Reliability, 2006,55(2):328-336.
[28] Diederik Lugtigheid, Dragan Banjuevic, Andrew K.S. Jardine. Component repairs: when to perform and what to do?[C].Relaiability and Maintainability Symposium,2005,398-403.
[29] Min Luo, Tongmin Jiang. Step Stress Accelerated Life Testing data analysis for repairable system using proportional intensity model[C]. Reliability and Maintainability Symposium,2009, 360-364.
[30] Huairrui Guo, Wenbiao Zhao, Adamantios Mettas. Practical methods for modeling repairable systems with time trends and repair effects[C]. Reliability and Maintainability Symposium.Jan.2006, 182-188.
[31] Kumar.D. Westberg.U. Proportional hazards modeling of time-dependent covariates using linear regression :a case study[mine power cable reliability][J]. IEEE Transactions on Reliability.1996, 45(3):386-392.
[32] Shibata. k,Rinsaka,k, Dohi,T. Metrics-Based Software Reliability Models Using Non-homogeneous Poisson Processes[C].17th International Symposium on Software Reliability Enginneering.2006,52-61.
[33] Prasad.P.V.N, Rao.K.R.M. Failure analysis and replacement strategies of distribution transformers using proportional hazard modeling[C]. Reliability and Maintainability Symposium.2003, 523-527.
[34] Tsujitani.M, Sakon.M. Analysis of Survival Data Having Time-Dependent Covariates[J].IEEE Transaction on Neural Networds.2009,20(3):389-394.
[35] Hougaard.P. Fitting a multivariate failure time distribution[J]. IEEE Transactions on Reliability.1989, 38(4):444-448.
[36] Chan.C.K. A proportional hazards approach to correlate SiO2-breakdown voltage and time distributions[J].IEEE Transactions on Reliability.1990,39(2):147-150.
[37] Elsayed.E.A.,Chan.C.K. Estimation of thin-oxide reliability using proportional hazards models[J]. IEEE Transactions on Reliability.1990, 39(3):329-335.
[38] Huamin Liu. Reliability of a load-sharing k-out-of-n:G system: non-iid components witharbitray distributions[J].IEEE Transactions on Reliability.1998,47(3):279-284.
[39] Xiao-lan Deng, Ting Wang. Stock Market Factors and Risk of Financial Distress: An Empirical Analysis Using Cox proportional Hazard Model[C].4th international Conference on Wireless Communications, Networking and Mobile Computing.2008, 1-4.
[40] Mazzuchi.T.A, Soyer.R, Spring.R.V. The proportional hazards model in reliability[C]. Reliability and Maintianability Symposium.1989, 252-256.
[41] Makis V, Jardine A K S. Optimal replacement in the proportional hazards model[J]. INFOR, 1991, 30(3): 172-83.