摘要
台风极端天气会诱发强风、暴雨、风暴潮等灾害链,传统海上风电运维策略仅考虑台风风速,难以全面地刻画台风对风机可靠度的影响,为此该文提出一种考虑台风灾害链的海上风电预测性维护策略。首先,针对台风及其灾害链对海上风机各部件冲击机理与载荷特性不同导致可靠度建模困难的问题,构建一种基于3-D Vine Copula的多灾害联合模型,对部件故障率增量进行差异化建模;其次,为解决台风等复杂海况下数据采集与监视控制系统(supervisory control and data acquisition,SCADA)关联数据隐含时空关系复杂难以准确描述态势的问题,将信息熵和循环神经网络引入时序卷积网络中,提出一种机组态势感知模型并修正台风灾害链下基于态势感知的可靠度;最后,针对态势变化和台风灾害链耦合影响下风机可靠度下降引发的不同时间尺度维护策略协调问题,构建海上风电机组多时间粒度分层预测性维护策略。通过算例仿真验证所提模型和方法的有效性。
Offshore wind turbine units are susceptible to typhoon attacks,and extreme typhoon weather can trigger a disaster chain of strong winds,heavy rain,storm surges,etc.Traditional operation and maintenance strategies only consider typhoon wind speeds,making it difficult to systematically characterize the impact of typhoons on turbine reliability and formulate corresponding maintenance strategies.To address this,the predictive maintenance strategy for offshore wind power,considering the typhoon disaster chain,is proposed in this article.Firstly,to address the difficulty in modeling reliability stemming from the varying impact mechanisms and load characteristics of typhoons and their disaster chains on different components of offshore wind turbines,a joint multi-disaster model based on 3-D Vine Copula is constructed to differentially model the incremental failure rates of components.Secondly,to tackle complex implicit spatio-temporal relationships in supervisory control and data acquisition(SCADA)correlation data under complex sea conditions such as typhoons,which hamper accurate situation description,Information Entropy and Recurrent Neural Network are introduced into Temporal Convolutional Network,and a unit situational awareness model is proposed to correct the reliability under the typhoon disaster chain.Finally,aiming at the coordination of maintenance strategies across different time scales,considering the decline in turbine reliability under the coupled influence of situational changes and typhoon disaster chains,a multi-time-granularity hierarchical predictive maintenance strategy for offshore wind turbine units is established.The superiority and effectiveness of the proposed model are verified through case simulations.
作者
葛晓琳
潘彬宇
符杨
刘璐洁
黄逸伟
GE Xiaolin;PAN Binyu;FU Yang;LIU Lujie;HUANG Yiwei(Engineering Research Center of Offshore Wind Technology Ministry of Education(Shanghai University of Electric Power),Yangpu District,Shanghai 200090,China;Faculty of Electrical Engineering,Shanghai Electric Power University,Yangpu District,Shanghai 200090,China)
出处
《中国电机工程学报》
北大核心
2026年第2期582-594,I0011,共14页
PROCEEDINGS OF THE CHINESE SOCIETY FOR ELECTRICAL ENGINEERING
基金
国家自然科学基金项目(52077130)
上海市教育发展基金会和上海市教育委员会“曙光计划”(23SG49)
上海绿色能源并网工程技术研究中心(13DZ2251900)。
关键词
台风灾害链
海上风电
可靠度
预测性维护
typhoon disaster chain
offshore wind power
component reliability
predictive maintenance
