内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司,呼和浩特 010020;内蒙古自治区新型电力系统智能化电网企业重点实验室,呼和浩特 010020
分析了风电机组可靠性研究现状, 指出已有研究存在的不足; 开展了风电机组关键部件的可靠性影响因素剖析, 梳理了风电机组故障类型, 探究了故障发生原因; 从风电机组设计方案、可靠性测试水平、监测系统先进性及维修方式合理性等方面提出了提升风电机组可靠性的方法,并指出可进一步开展的工作。
85 | 0 | 113 |
下载次数 | 被引频次 | 阅读次数 |
[1] 张秀琦,曹斌,王立强,等.基于改进K-means++聚类的多类型可调节资源层级评估[J].内蒙古电力技术,2023,41(6):62-67. ZHANG Xiuqi, CAO Bin, WANG Liqiang, et al. Multi-type adjustable resources level evaluation based on improved K-means++clustering[J]. Inner Mongolia Electric Power, 2023, 41(6):62-67.
[2] 周黎明.基于反馈轴承寿命的动调轴流风机液压缸运行可靠性研究与应用[J].东北电力技术,2022,43(8):24-25. ZHOU Liming. Research and Application of Dynamic Adjustable Axial Fan Hydraulic Cylinder Operation Reliability Based on Feedback Rod Bearing Life[J]. Northeast Electric Power Technology, 2022, 43(8):24-25.
[3] 王中行,周元贵,张学广.基于人工智能算法的风电机组状态监测和故障诊断技术研究综述[J].东北电力大学学报,2024,44(1):42-51. WANG Zhongxing, ZHOU Yuangui, ZHANG Xueguang. Review of artificial intelligence algorithms-based wind turbine condition monitoring and fault diagnosis techniques[J]. Journal of Northeast Electric Power University, 2024, 44(1):42-51.
[4] 尹子康,林忠伟,吕广华,等.基于数据驱动的风电机组变桨系统故障诊断与健康状态预测研究[J].东北电力大学学报,2023,43(5):1-11,17. YIN Zikang, LIN Zhongwei, LYU Guanghua, et al. Research on Fault Diagnosis and Health State Prediction of Wind Turbine Variable Pitch System Based on Data Drive[J]. Journal of Northeast Electric Power University, 2023, 43(5):1-11, 17.
[5] 程亮亮,沈伟强,韦舒天,等.双馈风电机组变流器功率管开路故障诊断方法[J].可再生能源,2019,37(11):1691-1696. CHENG Liangliang, SHEN Weiqiang, WEI Shutian, et al. Open switch fault diagnostic method of converters for doubly fed wind turbine[J]. Renewable Energy Resources, 2019, 37(11):1691-1696.
[6] 李宣.基于EWT和最优参数精细复合多尺度散布熵的风电机组齿轮箱故障诊断[D].西安:西安理工大学,2021.
[7] 赵洪山,张健平,高夺,等.风机齿轮箱轴承状态评估与剩余寿命预测[J].中国电力,2017,50(4):141-145. ZHAO Hongshan, ZHANG Jianping, GAO Duo, et al. Condition assessment and residual life prediction for gearbox bearing of wind turbine[J]. Electric Power, 2017, 50(4):141-145.
[8] 赵琴,袁逸萍,孙文磊,等.基于竞争失效的风电机组齿轮箱轴承剩余寿命分析[J].太阳能学报,2021,42(4):438-444. ZHAO Qin, YUAN Yiping, SUN Wenlei, et al. Remaining useful life analysis of gearbox bearing of wind turbine based on competition failure[J]. Acta Energiae Solaris Sinica, 2021, 42(4):438-444.
[9] PARENT O, ILINCA A. Anti-icing and deicing techniques for wind turbines:critical review[J]. Cold Regions Science&Technology, 2011, 65(1):88-96.
[10] 黎楚阳,朱孟兆,焦健,等.基于大数据分析的风机叶片结冰故障诊断[J].自动化与仪器仪表,2020(3):12-16. LI Chuyang, ZHU Mengzhao, JIAO Jian, et al. Fault diagnosis of wind turbine blade ice based on large data analysis[J]. Automation and Instrumentation, 2020(3):12-16.
[11] 沈学利,杨莹,秦鑫宇,等.基于残差神经网络的风机叶片结冰故障诊断[J].噪声与振动控制,2022,42(1):79-87. SHEN Xueli, YANG Ying, QIN Xinyu, et al. Icing fault diagnosis of wind turbine blades based on residual neural network[J]. Noise and Vibration Control, 2022, 42(1):79-87.
[12] 王宇鹏,王致杰,刘琦,等.基于动态柯西蜂群算法优化支持向量机的风机叶片故障诊断[J].电气工程学报,2018,13(1):16-22. WANG Yupeng, WANG Zhijie, LIU Qi, et al. Fault diagnosis of wind turbine blade based on cauchy artificial bee colony algorithm optimized support vector machine[J]. Journal of Electrical Engineering, 2018, 13(1):16-22.
[13] 罗勇.基于IPSO神经网络的风电机组主轴状态监测[J].应用能源技术,2018(1):38-40. LUO Yong. Wind turbine spindle condition monitoring based on operational data[J]. Applied Energy Technology, 2018(1):38-40.
[14] 安学利,蒋东翔,李少华.基于决策融合的直驱风力发电机组轴承故障诊断[J].电网技术,2011,35(7):36-41. AN Xueli, JIANG Dongxiang, LI Shaohua. Fault diagnosis of spherical roller bearing of direct-drive wind turbine based on decision fusion[J]. Power System Technology, 2011, 35(7):36-41.
[15] 李志刚.风力发电机轴电流抑制探讨[J].机电工程技术,2020,49(1):200-202. LI Zhigang. Discussion on the suppression of wind turbine shaft current[J]. Mechanical&Electrical Engineering Technology, 2020, 49(1):200-202.
[16] 钟绍辉,解京晶.双馈风力发电机滑环、碳刷故障分析及解决措施探讨[J].风能,2018(8):98-100. ZHONG Shaohui, XIE Jingjing. Fault analysis and solution of slip ring and carbon brush of doubly-fed wind turbine[J]. Wind Energy, 2018(8):98-100.
[17] Matthews P, Godwi n J L. Classification and detection of wind turbine pitch faults through SCADA data analysis[J]. International Journal of Prognostics and Health Management, 2013(4):90-100.
[18] LIANG Y, AN Z W, LIU B, et al. Fatigue life prediction for wind turbine main shaft bearings[C]//International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, Sichuan:IEEE, 2013:930-935.
[19] AZEVEDO H, ARAUJO A M, BOUCHONNEAU N. A review of wind turbine bearing condition monitoring:state of the art and challenges[J]. Renewable&Sustainable Energy Reviews, 2016(56):368-379.
[20] 李辉,季海婷,秦星,等.考虑运行功率变化影响的风电变流器可靠性评估[J].电力自动化设备,2015,35(5):1-8. LI Hui, JI Haiting, QIN Xing, et al. Reliability evaluation of wind power converter considering the influence of operating power change[J]. Electric Power Automation Equipment, 2015, 35(5):1-8.
[21] 王达梦.以可靠性为中心的风电机组机会维修策略研究[D].北京:华北电力大学,2020.
基本信息:
DOI:10.19929/j.cnki.nmgdljs.2024.0034
中图分类号:
引用信息:
[1]张秀琦1,2,胡学超1,2,李勇1,2.风电机组设备可靠性分析及提升方法研究[J].内蒙古电力技术,2024,42(03):8-12.DOI:10.19929/j.cnki.nmgdljs.2024.0034.
基金信息:
内蒙古自治区科技重大专项研究项目“适应高比例新能源消纳的储能电站协调运行控制关键技术研究与示范应用”(2021ZD0026)