文章摘要
电子式电流互感器误差模型及误差状态预测方法
Research on the Error Model and Forecasting Method for Electronic Current Transformers
投稿时间:2020-03-04  修订日期:2020-04-21
DOI:
中文关键词: 电子式电流互感器  Z-score标准化  聚类  RBF神经网络  
英文关键词: Electronic current transformer, Z-score standardization, clustering, RBF neural network
基金项目:国网科技项目(52182017000J)国家重点研发计划大科学装置前沿研究专项课题(2016YFA0401703)
作者单位E-mail
胡琛 国网江西省电力有限公司电力科学研究院 306358587@qq.com 
张竹 合肥工业大学 电气与自动化工程学院 zhuzhang@hfut.edu.cn 
杨爱超 国网江西省电力有限公司电力科学研究院  
李敏 国网江西省电力有限公司电力科学研究院  
焦洋 华中科技大学 强电磁工程与新技术国家重点实验室 湖北 武汉  
李东江 国网江西省电力有限公司电力科学研究院  
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中文摘要:
      为及时发现电子式电流互感器误差状态的稳定性问题,保证电能贸易结算的公平性,有必要对电子式电流互感器的误差状态进行预测。建立了电子式电流互感器误差模型,将其误差表征为单输出变量和多输入变量的理论模型,确定了模型输入变量和输出变量。针对模型输入变量和输出变量之间无明确函数关系的问题,提出了基于聚类RBF神经网络的误差状态预测方法,针对变量单位和数量级不同的问题,采用Z-score标准化法对数据进行预处理,为了简化神经网络,采用K-Means聚类算法对输入变量进行聚类分析。算例分析结果表明比差预测误差的绝对值小于0.05%,角差预测误差的绝对值小于10’。该预测方法可提供电子式电流互感器误差状态的变化信息,防范电能贸易结算的风险。
英文摘要:
      Predicting the error of electronic current transformers is significance for tackling the long-term stability problem of elec-tronic current transformers’ error in time and ensuring the validity of electric power trade. This paper develops the error model for electronic current transformers, where the error of electronic transformers is taken as a theoretical model with one input and multiple outputs, and the input and output variables are determined. Since the relationship between the input and output variables is indistinct, a forecasting method for electronic transformers based on clustering RBF neu-ral network is proposed. The data are pre-processed using Z-score normalization method to avoid the problem of dif-ferent variable magnitude and unit. The input variables are analyzed by K-means clustering method to simplify the neural network. The numerical example suggests that the predicting error of ratio error is less than 0.05% and the pre-dicting error of phase error is less than 10’. This method could provide an effective approach to analyzing the devel-opment state of electronic current transformers in operation and to managing the instruments actively, as a result, the risk of electric energy trade can be alleviated.
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