摘要
当前对于光伏微电网设备故障预警多采用相似性建模方法,但这种方法缺少对设备运行数据的流处理,导致故障预警精度较低。因此,提出基于多传感器信息融合的光伏微电网设备故障预警研究。首先,采集设备的状态参数,并利用多变量非线性函数对设备运行的历史数据与实时数据进行流处理与故障引擎分析,由此建立设备状态模型。其次,结合多传感器信息融合技术融合设备状态数据,并将其转化为后验概率输出,求取故障预警指标。最后,构建设备故障预警模型,计算故障预警区间阈值,实现设备故障预警。结果表明:所提方法得到的预警值与真实值之间的拟合优度较高,具有较高的预警精度。
Currently,the fault early warning of photovoltaic microgrid equipment often adopts similarity modeling methods.However,this approach lacks real-time processing of equipment operational data,resulting in lower fault early warning accuracy.Therefore,this paper proposes research on fault early warning of photovoltaic microgrid equipment based on multi-sensor information fusion.Firstly,collect the equipment state parameters and utilize multi-variable nonlinear functions to perform real-time data processing and fault engine analysis on the historical and collected real-time operational data of the equipment,thus establishing an equipment state model.Secondly,combined with multi-sensor information fusion technology,the equipment state data is fused and transformed into posterior probability output,so as to obtain the fault early warning index.Finally,the equipment fault early warning model is constructed,and the threshold of fault early warning interval is calculated,so as to realize the equipment fault early warning.The results show that the fitting goodness between the early warning value and the real value obtained by the proposed method is high,providing a high early warning accuracy.
作者
赵杨
ZHAO Yang(CNOOC Energy Development Co.,Ltd.Clean Energy Hainan Branch,Tianjin 300452)
出处
《能源科技》
2024年第3期64-67,共4页
Energy Science and Technology
关键词
多传感器信息融合
光伏微电网设备
故障预警
预警精度
Multisensor information fusion
photovoltaic microgrid equipment
fault early warning
early warning accuracy
