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A Method of Reducing Errors Due to Sampling in the Measurement of Electric Power.
- Source :
- Applied Sciences (2076-3417); May2024, Vol. 14 Issue 9, p3827, 14p
- Publication Year :
- 2024
-
Abstract
- Featured Application: Improving the measurement of electricity consumption by reducing errors is the main objective of this article. As a concrete application, the presented algorithm is used for the determination of electricity meters by the end user. With minimal costs, a correct assessment of energy consumption can be made, and therefore the calculated electricity costs should be accurate. Although data acquisition is a very usual technique, several aspects are not always considered, such as the synchronization of the acquired measures and the evaluation of the resulting errors. This paper aims to highlight this fact by the mathematical determination of the necessary correction and the implementation of software meant to evaluate the performances of acquisition systems. As an example, a three-phased acquisition system was developed in order to monitor the currents and voltages on the three phases. Also, other measures were performed, such as of power and phase. The components on each phase did not have to be fully identified because a whole system calibration could be performed in the first stage. The calibration consisted in finding the weighting coefficients for each measured quantity. The implemented solution for three-phased measure acquisition started from the hypothesis of a sampling frequency that respected the Shannon theorem. The distance between two samples was small enough to consider a linear evolution between two moments for the same measure. Errors that affected the above-mentioned measures, due to the fact that the samples were examined in different moments, were analyzed and brought to the minimum value. Finding a solution to reduce the sampling errors is closely related to reducing the costs. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 14
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 177181630
- Full Text :
- https://doi.org/10.3390/app14093827