作者:\n\t周柯，王晓明，李肖博，宋益 \n
Authors:\n\tZHOU Ke,WANG Xiaoming,LI Xiaobo,SONG Yi \n
摘要:\n\t为了基于监测数据对智能变电站二次保护装置进行故障预警，提出了一种基于ARIMA-BP组合模型的智能变电站遥测数据趋势性分析预警方法。通过智能变电站继电保护故障分析，选择装置状态趋势预警遥测数据源，基于数据源特性分析建立ARIMA-BP组合预测模型，基于ARIMA-BP组合预测模型及装置历史遥测数据进行装置运行趋势预测。并以某220kV变电站中线路保护装置的遥测数据为例进行算例分析，结果表明ARIMA-BP组合模型的预测误差率比单独的ARIMA模型和BP模型分别低5%和9%，验证了ARIMA-BP组合模型在遥测趋势预测预警的优越性。\n
Abstract:\n\tIn order to perform fault early warning on the secondary protection devices of smart substations based on monitoring data, a trend analysis and early warning method of smart substation telemetry data based on the ARIMA-BP combined model is proposed.Based on the analysis of the relay protection failure of the intelligent substation, the remote measurement data source for the early warning of the device status trend is selected, and the ARIMA-BP combined forecasting model is established based on the analysis of the characteristics of the data source.Based on the ARIMA-BP combined forecasting model and the historical telemetry data of the equipment, the equipment operation trend prediction is carried out.Taking the remote measurement data of the line protection device in a 220kV substation as an example, the prediction error rate of the ARIMA-BP combined model is 5% and 9% lower than that of the ARIMA model and the BP model alone. The superiority of ARIMA-BP combined model in telemetry trend prediction and early warning is verified.\n
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基于ARIMA-BP组合模型的智能变电站遥测数据趋势性分析预警技术研究
本站小编 Free考研考试/2024-10-07
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