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计量在线监测联合智能诊断的日电量拟合分析

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针对现有数据采集系统常见的数据缺失与异常问题,通过计量在线监测与智能诊断技术,提高日电量数据的拟合精确度和可靠性.采用基于计量在线监测技术的日冻结电能示值异常甄别规则和日电量拟合模型准确标识数据问题,并结合当日负荷估值法与参考日电量加权均值法,针对不同情况进行日电量拟合计算.实验结果显示,所提方法能有效处理日电量数据缺失与异常,确保拟合结果与实际用电趋势保持一致.在处理因通信故障或设备故障导致的数据缺失时,提出的模型与算法表现出较高的准确性和可靠性.
Fitting Analysis of Daily Electricity Combining Metering Online Monitoring and Intelligent Diagnosis
Aiming at addressing data loss and abnormality in existing data acquisition systems,the fitting accuracy and re-liability of the daily power data are improved through metering online monitoring and intelligent diagnosis technology.The abnormal screening rule of daily frozen electricity value and daily electricity fitting model based on metering online monito-ring technology are adopted.The abnormal screening rules are designed to accurately identify the data problems,and the daily load valuation method and the reference daily power weighted average method are calculated for different situations.The experimental results show that the proposed method can effectively deal with the missing and abnormal daily electrici-ty data,and ensure that the fitting results are consistent with the actual electricity consumption trend.It is concluded that the proposed model and algorithm show high accuracy and reliability when handling the missing data caused by communi-cation failure or equipment failure.

online monitoringintelligent diagnosisdaily electricity fitting

伍晨豪、黄涛、黄一航

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台州宏达电力建设有限公司台州经济开发区运检分公司,浙江 台州 318000

在线监测 智能诊断 日电量拟合

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(18)