摘要
针对现有风电机组数据采集与监视控制系统(Supervisory Control And Data Acquisition,SCADA)采用固定阈值法进行参数异常检测效率低下、智能化缺乏的不足,提出了一种结合专家知识与数据分析的风力发电机组参数异常检测方法。首先,依据风电机组运行原理,将其划分为变桨系统、机舱系统、传动系统、发电机系统等子系统;然后,针对设备数据不变、数据跳变、数据一致性异常等典型故障,分系统构建基于专家知识与数据分析的异常预警方法;最后,采用多台风电机组真实运行数据,验证所提方法的准确性与有效性。
Aiming at the disadvantages of low efficiency and lack of intelligentization in parameter anomaly detection by using fixed threshold method in the existing Supervisory Control and Data Acquisition(SCADA)system of wind turbines,this paper presents a method of wind turbine parameter anomaly detection which combines expert knowledge and data analysis.Firstly,according to the operating principle of wind turbine,it is divided into subsystems such as variable pitch system,engine room system,transmission system and generator system.Then,aimed at the typical faults such as equipment data invariance,data jump and data consistency anomaly,an anomaly warning method based on expert knowledge and data analysis is constructed according to each subsystem.Finally,the accuracy and effectiveness of the proposed method are verified by using the real operation data of multiple wind turbine generators.
作者
张明红
张琛
ZHANG Minghong;ZHANG chen(China Harzone Industry Co.,Ltd.,Wuhan Hubei 4302223,China;School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan Hubei 430068,China)
出处
《湖北电力》
2024年第5期51-58,共8页
Hubei Electric Power
基金
国家重点研发计划项目(项目编号:2022YFB4100400)。
关键词
新能源
风力发电
太阳能发电
可再生能源
碳排放
风电场
碳达峰
碳中和
new energy
wind power generation
solar power generation
renewable energy
carbon emission
wind farm
carbon peak,carbon neutrality
