Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm

With the rapid construction of smart grid, many applications of the new generation and the large power dynamic loads are revolutionizing the electrical energy measurement of electricity meters. The dynamic measurement errors produced by electricity meters are intolerable. In order to solve the dynam...

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Main Authors: Wang Xuewei, Wang Jing
Format: Article
Language:English
Published: Sciendo 2018-10-01
Series:Measurement Science Review
Subjects:
Online Access:https://doi.org/10.1515/msr-2018-0029
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spelling doaj-72b85ce8b4ae468da8024a3480cf26ff2021-09-06T19:20:28ZengSciendoMeasurement Science Review1335-88712018-10-0118520721710.1515/msr-2018-0029msr-2018-0029Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement AlgorithmWang Xuewei0Wang Jing1Institute of Information Science and Technology, Beijing University of Chemical Technology, North Third Ring Road,Beijing, ChinaInstitute of Information Science and Technology, Beijing University of Chemical Technology, North Third Ring Road,Beijing, ChinaWith the rapid construction of smart grid, many applications of the new generation and the large power dynamic loads are revolutionizing the electrical energy measurement of electricity meters. The dynamic measurement errors produced by electricity meters are intolerable. In order to solve the dynamic error measurement of electrical energy, firstly, this paper proposes a three-phase pseudorandom dynamic test power signal model to reflect the main characteristics of dynamic loads. Secondly, a compressive measurement algorithm is proposed by the means of steady-state optimization to accurately measure the electrical energy. The experimental results confirm the effectiveness of the three-phase pseudorandom dynamic test signal model, the maximum errors of compressive measurement algorithm are superior to 1×10-13, the high precision enables the algorithm to accurately measure the electrical energy under different dynamic conditions.https://doi.org/10.1515/msr-2018-0029compressive measurementdynamic loadelectricity meterelectrical energy
collection DOAJ
language English
format Article
sources DOAJ
author Wang Xuewei
Wang Jing
spellingShingle Wang Xuewei
Wang Jing
Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm
Measurement Science Review
compressive measurement
dynamic load
electricity meter
electrical energy
author_facet Wang Xuewei
Wang Jing
author_sort Wang Xuewei
title Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm
title_short Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm
title_full Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm
title_fullStr Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm
title_full_unstemmed Pseudorandom Dynamic Test Power Signal Modeling and Electrical Energy Compressive Measurement Algorithm
title_sort pseudorandom dynamic test power signal modeling and electrical energy compressive measurement algorithm
publisher Sciendo
series Measurement Science Review
issn 1335-8871
publishDate 2018-10-01
description With the rapid construction of smart grid, many applications of the new generation and the large power dynamic loads are revolutionizing the electrical energy measurement of electricity meters. The dynamic measurement errors produced by electricity meters are intolerable. In order to solve the dynamic error measurement of electrical energy, firstly, this paper proposes a three-phase pseudorandom dynamic test power signal model to reflect the main characteristics of dynamic loads. Secondly, a compressive measurement algorithm is proposed by the means of steady-state optimization to accurately measure the electrical energy. The experimental results confirm the effectiveness of the three-phase pseudorandom dynamic test signal model, the maximum errors of compressive measurement algorithm are superior to 1×10-13, the high precision enables the algorithm to accurately measure the electrical energy under different dynamic conditions.
topic compressive measurement
dynamic load
electricity meter
electrical energy
url https://doi.org/10.1515/msr-2018-0029
work_keys_str_mv AT wangxuewei pseudorandomdynamictestpowersignalmodelingandelectricalenergycompressivemeasurementalgorithm
AT wangjing pseudorandomdynamictestpowersignalmodelingandelectricalenergycompressivemeasurementalgorithm
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