A DAQ-based sampling wattmeter for IEEE Std. 1459-2010 powers measurements. Uncertainty evaluation in nonsinusoidal conditions

Cataliotti, Antonio; Cosentino, Valentina; Cara, Dario Di; Lipari, Alessandro; Nuccio, S.

doi:10.1016/j.measurement.2014.10.033

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…The other low-cost calibration option is to use a PC and Data Acquisition (DAQ) board-based system. It has been demonstrated that such systems can achieve impressive accuracies at a fraction of the cost of commercial standards [46,47], in a research environment. DAQ-based calibrators are set to become popular in future, although the technology probably needs more time to become commercialised.…”

Section: Calibration In Mandvmentioning

confidence: 99%

Low-cost energy meter calibration method for measurement and verification

2017

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Energy meters need to be calibrated for use in Measurement and Verification (M&V) projects. However, calibration can be prohibitively expensive and affect project feasibility negatively. This study presents a novel low-cost in-situ meter data calibration technique using a relatively low accuracy commercial energy meter as a calibrator. Calibration is achieved by combining two machine learning tools: the SIMulation EXtrapolation (SIMEX) Measurement Error Model and Bayesian regression. The model is trained or calibrated on half-hourly building energy data for 24 hours. Measurements are then compared to the true values over the following months to verify the method. Results show that the hybrid method significantly improves parameter estimates and goodness of fit when compared to Ordinary Least Squares regression or standard SIMEX. This study also addresses the effect of mismeasurement in energy monitoring, and implements a powerful technique for mitigating the bias that arises because of it. Meters calibrated by the technique presented have adequate accuracy for most M&V applications, at a significantly lower cost.

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Section: Calibration In Mandvmentioning

confidence: 99%

Low-cost energy meter calibration method for measurement and verification

2017

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“…2 Salah satu yang harus dilakukan oleh laboratorium adalah mengevaluasi dan menghitung ketidakpastian pengukuran yang dihasilkan, seperti di bidang tekstil, farmasi, [3][4][5] dan kelistrikan. 6,7 Ketidakpastian adalah parameter hasil pengukuran yang memberikan karakter sebaran nilai-nilai yang secara layak dapat diberikan pada besaran ukur. 8 Ketidakpastian pengukuran menunjukkan besarnya akurasi yang dihasilkan oleh suatu laboratorium uji.…”

Section: Pendahuluanunclassified

Evaluasi Ketidakpastian Pengukuran Uji Kekuatan Tarik Kain Cara Pita Tiras

Islam

Sana

2017

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Sebuah studi tentang evaluasi ketidakpastian pengukuran pada uji kekuatan tarik kain cara pita tiras. Studi dilakukan untuk mendapatkan model dan mengestimasi ketidakpastian pengukuran. Model pengukuran dibuat dengan memperhitungkan metoda dan proses utama pengujian kekuatan tarik kain cara pita tiras. Model pengukuran yang dihasilkan yaitu : besarnya kekuatan tarik kain cara pita tiras berbanding lurus dengan gaya yang dihasilkan oleh alat uji kekuatan tarik (F) dan ketentuan lebar kain pada metoda (L s ), serta berbanding terbalik dengan lebar kain contoh uji (L k ) atau F = F . . Formulasi tersebut dijadikan sebagai acuan dalam menentukan komponen-komponen berkontribusi pada ketidakpastian totalnya, yaitu repeability hasil uji, alat uji kekuatan tarik kain, lebar contoh uji dan tetal kain.Kata kunci: pengukuran, ketidakpastian, kekuatan tarik kain, pita tiras.

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“…In specialized literature, such a method is not currently described, although it is largely used. Different approaches are possible, but in this article, the most intuitive and clear method is presented [1,2].…”

Section: Introductionmentioning

confidence: 99%

A Method of Reducing Errors Due to Sampling in the Measurement of Electric Power

Oancea

2024

Applied Sciences

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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.

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A DAQ-based sampling wattmeter for IEEE Std. 1459-2010 powers measurements. Uncertainty evaluation in nonsinusoidal conditions

Cited by 10 publications

References 31 publications

Low-cost energy meter calibration method for measurement and verification

Low-cost energy meter calibration method for measurement and verification

Evaluasi Ketidakpastian Pengukuran Uji Kekuatan Tarik Kain Cara Pita Tiras

A Method of Reducing Errors Due to Sampling in the Measurement of Electric Power

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