电网技术
電網技術
전망기술
Power System Technology
2015年
11期
3202-3207
,共6页
张秋雁%程含渺%李红斌%魏伟
張鞦雁%程含渺%李紅斌%魏偉
장추안%정함묘%리홍빈%위위
数字化电能计量%误差评估%多参量退化模型%大数据处理%差分归一化%前馈神经网络
數字化電能計量%誤差評估%多參量退化模型%大數據處理%差分歸一化%前饋神經網絡
수자화전능계량%오차평고%다삼량퇴화모형%대수거처리%차분귀일화%전궤신경망락
digital electrical energy metering%error evaluation%multi-parameter degradation model%big data processing%differential normalization%feed-forward neural network
为评估数字电能计量系统的运行误差,提出了基于多参量退化模型的误差评估方法。数字化电能计量系统等效为多输入单输出系统,确定系统退化参量及参量退化作用量,从而建立多参量退化模型,并给出误差评估约束条件。在求解退化网络过程中,引入了大数据处理方法。针对数据种类繁多且变化速率不一的特点,采用差分归一化数据预处理方法。针对退化网络不能用初等函数描述的问题,采用前馈神经网络逼近退化特性。实现了在已知参量退化影响量的条件下,根据误差评估约束评估数字化电能计量系统误差。实例分析结果显示,所提方法的评估结果与实际运行状态在短时间内相符合,绝对误差小于0.2%,表明该方法能有效地动态评估数字化电能计量系统的误差。
為評估數字電能計量繫統的運行誤差,提齣瞭基于多參量退化模型的誤差評估方法。數字化電能計量繫統等效為多輸入單輸齣繫統,確定繫統退化參量及參量退化作用量,從而建立多參量退化模型,併給齣誤差評估約束條件。在求解退化網絡過程中,引入瞭大數據處理方法。針對數據種類繁多且變化速率不一的特點,採用差分歸一化數據預處理方法。針對退化網絡不能用初等函數描述的問題,採用前饋神經網絡逼近退化特性。實現瞭在已知參量退化影響量的條件下,根據誤差評估約束評估數字化電能計量繫統誤差。實例分析結果顯示,所提方法的評估結果與實際運行狀態在短時間內相符閤,絕對誤差小于0.2%,錶明該方法能有效地動態評估數字化電能計量繫統的誤差。
위평고수자전능계량계통적운행오차,제출료기우다삼량퇴화모형적오차평고방법。수자화전능계량계통등효위다수입단수출계통,학정계통퇴화삼량급삼량퇴화작용량,종이건립다삼량퇴화모형,병급출오차평고약속조건。재구해퇴화망락과정중,인입료대수거처리방법。침대수거충류번다차변화속솔불일적특점,채용차분귀일화수거예처리방법。침대퇴화망락불능용초등함수묘술적문제,채용전궤신경망락핍근퇴화특성。실현료재이지삼량퇴화영향량적조건하,근거오차평고약속평고수자화전능계량계통오차。실례분석결과현시,소제방법적평고결과여실제운행상태재단시간내상부합,절대오차소우0.2%,표명해방법능유효지동태평고수자화전능계량계통적오차。
To evaluate operating error of digital electrical energy metering system, an evaluation method based on multi-parameter degradation model is proposed. Digital electrical energy metering system is equivalent to a multi-input single-output system where system degradation parameters and degradation acting parameters are determined, aiming at building multi-parameter degradation model and putting forward error evaluation constraint. Big data analysis methods are introduced in process of solving degradation network. As the data are of multiple categories and data changing rates are variable, pre-processing method of differential normalized data is employed. Additionally, feed-forward neural network is adopted to approximate degradation characteristics, because elementary function is incapable of describing degradation network. Therefore, error of digital electrical energy metering system can be evaluated according to error evaluation constraint, assuming degradation acting parameters pre-determined. Example analysis results show that evaluation results using the proposed method is in accordance with operating state in short time, and absolute error is less than 0.2%, demonstrating that the method can evaluate error of digital electrical energy metering system effectively and dynamically.