Accuracy improvement of the stochastic digital electrical energy meter

Urekar, Marjan; Pejic, Dragan; Vujičić, Vladimir; Avramov-Zamurovic, Svetlana

doi:10.1016/j.measurement.2016.11.038

Cited by 19 publications

(11 citation statements)

References 4 publications

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“…Therefore, they can be improved without new hardware design. Some improvements in that sense were presented in [4] and [8]. The first reference describes the improvement in terms of accuracy, while the second one shows how to determine the consumer's profile (capacitive, inductive, thermogenic or mixed) and its behavior.…”

Section: Discussionmentioning

confidence: 99%

“…8 and 9 it can be seen that the A/D conversion and MAC operations (MACmultiply and accumulate) are extremely simple. The instrument is, therefore, simple and reliable, and it has a small number of systematic errors that can be easily identified and eliminated [8]. The first scheme is intended for measurement of the mean value of a product of two analog signals f 1 (t) and f 2 (t) (e.g.…”

Section: Further Improvement Of the Mm4 Instrumentmentioning

confidence: 99%

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A brief overview of stochastic instruments for measuring flows of electrical power and energy

Vujičić¹,

Pejic

Radonjić

2019

FACTA U EE

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This paper gives a brief overview of three instruments suitable for measuring the flow of electrical power and energy. The first instrument is a single-phase power analyzer, while the other two instruments are double and quadruple three-phase power analyzers. In addition to overviewing these instruments, the paper presents a possible improvement of a quadruple three-phase power analyzer. The implementation of this improvement would make it possible to use a quadruple three-phase power analyzer as support for the phasor measurement unit.

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Section: Discussionmentioning

confidence: 99%

Section: Further Improvement Of the Mm4 Instrumentmentioning

confidence: 99%

A brief overview of stochastic instruments for measuring flows of electrical power and energy

Vujičić¹,

Pejic

Radonjić

2019

FACTA U EE

Self Cite

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“…Recent results in domain of power measurement [15] expose high accuracy reached with only dual bit A/D converter structure improved with offset error suppression technique. Similar technique is also extended to frequency measurement system [16] where noise immunity creates valuable advantage.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, for reliable statistical result, 50 measurements per one coefficient must be taken into account. Overall, for one coefficient it takes 9 20 50 20, 000 100 2 10 , C N       (15) arithmetic operations. Applying IEEE standard 1547-2003 [20], for complete analysis of the signal in distributive network, 50 harmonics has to be measured, where every harmonic has it's cosine and sine component.…”

Section: Theory Of Operationmentioning

confidence: 99%

“…In Fig. 5 we can see N requests and M threads in pool, where M < N. Creating new threads burdens CPU and if we have, like in the given simulation 100 requests that has to be fulfilled while each request assumes 2×10 9 arithmetic operations (15), time savings can be significant. The only limitation in Thread Pool usage is that all threads in the pool must be with the same priority and order of thread execution can't be controlled as well as number of threads in the pool, since the Run-time environment creates and controls threads.…”

Section: Usage Of Thread Poolingmentioning

confidence: 99%

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Acceleration of Digital Stochastic Measurement Simulation Based on Concurrent Programming

Pjevalica¹,

Pjevalica²,

Kaštelan³

et al. 2018

ElAEE

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A/D conversion methods improved through stochastic signal superposition, along with oversampling techniques present significant research direction in the area of signal processing and measurement. Concerning that accuracy of those methods rises with length of measurement interval, i.e. integration time; it turns them appropriate for calculation / measurement of the orthogonal transformations. Simulation and validation of above mentioned digital stochastic methods, requires significant computing resource allocation. Long measurement intervals assigned for processing of numerous arithmetic operations over oversampled input signals presents the most demanding computing requirements. In this paper, a novel digital stochastic measurement simulation approach is presented and validated. Simulation approach is based on Concurrent Programming technique. General orthogonal transformations are analysed through the stochastic measurement technique. As a reference test case Discrete Fourier Transform is calculated over several periodic input signals converted by the stochastic A/D converter. Time required for a simulation test case accomplishment is analysed as a main performance metric. Final results have proven that Concurrent Programming technique improves simulation speed, without other consequences on measurement performance.

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Stochastic Smart Grid Meter for Industry 4.0—From an Idea to the Practical Prototype

Urekar¹,

Kozarov²

2022

Springer Proceedings in Mathematics &Amp; Statistics

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Accuracy improvement of the stochastic digital electrical energy meter

Cited by 19 publications

References 4 publications

A brief overview of stochastic instruments for measuring flows of electrical power and energy

A brief overview of stochastic instruments for measuring flows of electrical power and energy

Acceleration of Digital Stochastic Measurement Simulation Based on Concurrent Programming

Stochastic Smart Grid Meter for Industry 4.0—From an Idea to the Practical Prototype

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