风电机组试运行期间停机时间建模分析

doi:10.11930/j.issn.1004-9649.2013.11.109.3

摘要/Abstract

摘要： 并网风电机组作为大型户外单体机电设备,其平均停机时间（mean downtime,MDT）是反映机组可靠性的重要指标之一。针对试运行期间的MDT估计问题,提出一种基于Weibull分布的MDT建模估计方法。以山东青岛某风电场投入试运行的14台1.5 MW永磁直驱风电机组的停机时间为研究对象,通过箱线图检验法,剔除疑似异常数据,再对修正后的数据进行概率纸检验,建立基于Weibull分布的机组停机时间模型。截取2012年12月—2013年3月14台机组停机时间数据,利用模型的数学性质,进行平均停机时间的点、双侧区间和单侧区间上限估计。基于计算结果,分析影响停机时间的原因,并提出降低试运行期间机组停机时间的建议。

关键词: 风电机组, 平均停机时间, 概率纸检验, Weibull分布

Abstract: Grid-connected wind turbines are of large single outdoor mechanical and electric equipment, and the mean downtime(MDT) is an important indicator reflecting the reliability of the unit. For estimating the MDT during the trial operation period, a Weibull distribution- based method was proposed. By taking a wind farm in Qingdao city of Shandong province for downtime case study, which has 14 direct drive permanent magnet wind turbines of 1.5 MW, a Weibull distribution-based downtime model was established through excluding the suspected abnormal-data by Boxplots test and testing the revised data by Weibull probability paper. By intercepting the downtime data of 14 units in trial operation from December 2012 to March 2013, the upper MDT bound of point, bilateral interval and unilateral interval was estimated by the model. Based on the calculation results, the causes of the downtime were analyzed and some advises were proposed for reducing the unit downtime during the trial operation period.

Key words: wind turbines, mean downtime (MDT), probability paper test, Weibull distribution

中图分类号:

TM614

张穆勇, 芮晓明, 霍娟. 风电机组试运行期间停机时间建模分析[J]. 中国电力, 2013, 46(11): 109-112.

ZHANG Mu-yong, RUI Xiao-ming, HUO Juan. Modeling Analysis of the Downtime of Wind Turbines During Trial Operation Period[J]. Electric Power, 2013, 46(11): 109-112.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.2013.11.109.3

https://www.electricpower.com.cn/CN/Y2013/V46/I11/109

参考文献

[1] 吴义纯,丁明. 风电场可靠性评估[J]. 中国电力,2004,37（5）： 81-84.
WU Yi-Chun, DING Ming. Reliability assessment of wind farm[J]. Electric Power, 2004, 37(5): 81-84.
[2] 孔屹刚,王志新. 风电机组可靠性建模和动态过程分析[J]. 太阳能学报,2008,29（6）：652-656.
KONG Yi-gang, WANG Zhi-xin. Reliability modeling and dynamic process analysis for wind turbine[J]. Acta Engeriae Solaris Sinica, 2008, 29(6): 652-656.
[3] SPINATO F, TAVNER P J, Van BUSSEL G J W, et al. Reliability of wind turbines subassemblies [J]. IET Renewable Power Generator, 2009, 3(4): 1-15.
[4] HERBERT G M J, INIYAN S, SREEVALSAN E, et al. A review of wind energy technologies[J]. Renewable and Sustainable Energy Reviews, 2007, 11(6): 1117-1145.
[5] PéREZ J M P, MáRQUEZ F P G, TOBIAS A, et al. Wind turbine reliability analysis [J]. Renewable and Sustainable Energy Reviews, 2013, 23(7): 463-472.
[6] SPINATO F, TAVNER P, Van BUSSEL G, et al. Reliability of wind turbine subassemblies [J]. IET Renewable Power Generation,2009, 3(4): 387-401.
[7] TAVNER P, XIANG J, SPINATO F. Reliability analysis for wind turbines [J]. Wind Energy, 2007, 10(1): 1-18.
[8] WANG Wen-bin. An overview of recent advances in delay-time based maintenance modeling [J]. Reliability Engineering & System Safety, 2012, 106(10): 165-178
[9] MENSAH A F, LEONARDO D O. A closed-form technique for the reliability and risk assessment of wind turbine systems[J].Energies, 2012, 5(6): 1734-1750.
[10] 辛卫东,马志勇,滕伟,等. 振动监测技术在风电齿轮箱故障诊断中的应用[J]. 中国电力,2012,45（5）：77-80.
XIN Wei-dong, MA Zhi-yong, TENG Wei, et al . Application of vibration monitoring technology on fault diagnosis of gearbox in wind power unit [J]. Electric Power, 2012, 45(5): 77-80.
[11] 李大字,冯圆圆,刘展,等. 风力发电机组可靠性建模与维修策略优化[J]. 电网技术,2011,35（9）：122-127.
LI Da-zi, FENG Yuan-yuan, LIU Zhan, et al . Reliability modeling and maintenance strategy optimization for wind power generation sets [J]. Power System Technology, 2011, 35(9): 122-127.
[12] 孙永全,郭建英,陈洪科,等. 兆瓦级直驱风电机组可靠性增长预测[J]. 中国电机工程学报,2010,30（18）：67-71.
SUN Yong-quan, GUO Jian-ying, CHEN Hong-ke, et al . MW level direct-driven wind turbine reliability growth prediction[J]. Proceeding of the CSEE, 2010, 30(18): 67-71.
[13] 敖长林,李一军,闫相斌,等. 基于非齐次泊松过程的拖拉机发动机使用可靠性[J]. 机械工程学报,2007,43（10）：206-210.
AO Chang-lin, LI Yi-jun, YAN Xiang-bin, et al . Operational reliability of tractor engines based on non-homogeneous Poisson process[J]. Chinese Journal of Mechanical Engineering, 2007, 43(10): 206-211.
[14] 陈雪峰,李继猛,程航,等. 风力发电机状态监测和故障诊断技术的研究与进展[J]. 机械工程学报,2011,47（9）：45-52.
CHEN Xue-feng, LI Ji-meng, CHENG Hang, et al . Research and application of condition monitoring and fault diagnosis technology in wind turbines [J]. Journal of Mechanical Engineering, 2011, 47(9): 45-52.
[15] 郭鹏,徐明,白楠,等. 基于SCADA运行数据的风电机组塔架振动建模与监测[J]. 中国电机工程学报,2013,33（5）：128-135.
GUO Peng, XU Ming, BAI Nan, et al . Wind turbine tower vibration modeling and monitoring driven by SCADA data[J]. Proceeding of the CSEE, 2013, 33(5): 128-135.
[16] 盛骤,谢式千,潘承毅. 概率论与数理统计[M]. 北京：高等教育出版社,2008：130-135.
[17] 刘天华,张志华,李庆民,等. 威布尔型多不可修部件备件需求确定方法[J]. 系统工程理论与实践,2012,32（9）：2010-2015.
LIU Tian-hua, ZHANG Zhi-hua, LI Qing-min, et al . Determination method of the spare demand for multiple components with Weibull distribution[J]. Systems Engineering-Theory & Practice, 2012, 32(9): 2010-2015.
[18] RAUSAUD M. 系统可靠性性理论：模型、统计方法及应用[M]. 2版. 郭强,王秋芳,刘树林,译. 北京：国防工业出版社,2011：13-31.