基于PCA-FSEM方法的风力发电机可靠性研究

兰州理工大学学报 ›› 2024, Vol. 50 ›› Issue (1): 35-40.

基于PCA-FSEM方法的风力发电机可靠性研究

郑玉巧^*, 郎启发, 施成龙, 刘宇航, 刘燕杰

兰州理工大学机电工程学院, 甘肃兰州 730050

收稿日期:2022-02-27 出版日期:2024-02-28 发布日期:2024-03-04
通讯作者: 郑玉巧(1977-),女,甘肃庄浪人,博士,教授,博导. Email:zhengyuqiaolut@163.com
基金资助:
国家自然科学基金(51965034)

Reliability research of wind turbine based on PAC-FSEM method

ZHENG Yu-qiao, LANG Qi-fa, SHI Cheng-long, LIU Yu-hang, LIU Yan-jie

School of Mechanical and Electronical Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China

Received:2022-02-27 Online:2024-02-28 Published:2024-03-04

摘要/Abstract

摘要： 针对西北某风电场相关运行数据,对风力发电机进行可靠性研究.考虑运行数据之间相关性和冗余度,采用主成分分析(PCA)法进行降维,选取部分关键可靠性指标且根据关键指标运行数据,结合模糊理论建立可靠性评价模型,并选取部分风力发电机运行数据进行模型验证.结果表明,PCA法提取主成分累积方差贡献率为87.585%,可综合表述风力发电机的可靠性信息.单一可靠性指标评价时,虽然B02单机可利用率高达98%,但总发电量最低,虽然A04单机可利用率最低,但发电量较高,说明单一可靠性指标评价时存在误差.A05、B03单机各项指标均高,实际运行状态良好,发电量高,说明综合可靠性更高,与研究结果一致.因此,基于PCA模糊理论建立的风力发电机可靠性模糊理论评价模型(FSEM)符合实际运行状态,对定量评估机组可靠性具有指导意义.

关键词: 风力发电机, PCA, 可靠性, FESM

Abstract: Based on the relevant operating data from a wind farm in Northwest China, the reliability of wind turbines is studied. Considering the correlation and redundancy among operating data, Principal Component Analysis (PCA) method was used to reduce dimensionality, and some key reliability indicators were selected. Subsequently, a reliability evaluation model is constructed utilizing fuzzy theory in conjunction with the selected key indicators from operational data. A subset of wind turbine operating data is selected for model verification. The research results show that the PCA method extracts the principal component with a cumulative variance contribution rate of 87.585%, which can comprehensively express the reliability information of wind turbines. In the evaluation of a single reliability index, the availability of B02 is as high as 98%, but its total power generation is the lowest. Conversely, the availability of A04 is the lowest in the available area yet relatively higher power generation, indicating potential discrepancies when assessing reliability based on single reliability index. All indicators of A05 and B03 are high, the actual operation state of which is good, and the power generation is high, indicating that their comprehensive reliability is higher, which is consistent with the research results. Therefore, the fuzzy theoretical evaluation model (FSEM) of wind turbine reliability established based on PCA and fuzzy theory is in line with the actual operating state and has guiding significance for quantitatively evaluating the reliability of wind turbines.

Key words: wind turbine, PCA, reliability, FESM

中图分类号:

TK83

郑玉巧, 郎启发, 施成龙, 刘宇航, 刘燕杰. 基于PCA-FSEM方法的风力发电机可靠性研究[J]. 兰州理工大学学报, 2024, 50(1): 35-40.

ZHENG Yu-qiao, LANG Qi-fa, SHI Cheng-long, LIU Yu-hang, LIU Yan-jie. Reliability research of wind turbine based on PAC-FSEM method[J]. Journal of Lanzhou University of Technology, 2024, 50(1): 35-40.

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