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基于多种模型融合的电能计量互感器误差自动化补偿方法

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为电能精准计量提供保障,提出基于多种模型融合的电能计量互感器误差自动化补偿方法.获取影响电能计量互感器误差的关键特征数据,作为改进LSTM与SVR输入,得到对应子模型的预测输出,计算子模型的权重系数,通过平均加权法融合模型的预测结果,确定电能计量互感器运行数据预测值,利用自回归积分滑动平均模型实现电能计量互感器误差的动态补偿.实验结果表明,特征数据选择可有效降低电能计量互感器比差和角差波动幅度;误差补偿后的二次电压曲线平滑,且更加接近理想的正弦波形.
Automatic Compensation Method for Error of Electric Energy Measurement Transformers Based on Multiple Model Fusion
In order to ensure the accurate measurement of electric energy,this paper proposes an automatic compen-sation method for the error of electric energy metering transformer based on the fusion of multiple models.The key characteristic data selection that affects the error of electric energy metering transformer is obtained as the input of improved LSTM and SVR,and the predicted output of the corresponding sub-model is obtained,and the weight coeffi-cient of the sub-model is calculated.The predicted value of the operation data of electric energy metering transformer is determined by fusing the prediction results of the model by the average weighting method,and the dynamic com-pensation of the error of electric energy metering transformer is realized by using the autoregressive integral moving average model.The experimental results show that the selection of characteristic data can effectively reduce the fluc-tuation range of ratio difference and angular difference of electric energy metering transformer.The secondary voltage curve after error compensation is smooth and closer to the ideal sine wave.

transformererror compensationtransfer entropySVRLSTMautoregressive integral moving average model

杜瀚霖

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柳州市计量技术测试研究所,柳州 545000

互感器 误差补偿 传递熵 SVR LSTM 自回归积分滑动平均模型

2024

自动化与仪表
天津市工业自动化仪表研究所 天津市自动化学会

自动化与仪表

CSTPCD
影响因子:0.548
ISSN:1001-9944
年,卷(期):2024.39(9)