FDST-based PQ event detection and energy metering implementation on FPGA-in-the-loop and NI-LabVIEW

Power quality (PQ) is crucial parameter in determining the robustness and accuracy of any energy-metering algorithm. It immensely affects the performance of energy meters in terms of measurement accuracy. This study presents digital implementation of fast discrete Stockwell transform (FDST) with aut...

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Vydané v:IET science, measurement & technology Ročník 11; číslo 4; s. 453 - 463
Hlavní autori: Jaiswal, Supriya, Ballal, Makarand S
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: The Institution of Engineering and Technology 01.07.2017
Predmet:
ALTERA Cyclone IV E FPGA board
data loggers
data logging
energy‐metering algorithm
fast discrete Stockwell transform
fast Fourier transform
fast Fourier transforms
field programmable gate array
field programmable gate arrays
filter‐based design
loss evaluation
mathematics computing
MATLAB
NI‐LabVIEW
power meters
power quality‐event detection
remote control access
Research Article
SEM virtual instrument
smart energy meter
smart meters
virtual instrumentation
fast Fourier transforms
data loggers
fast discrete Stockwell transform
field programmable gate arrays
mathematics computing
filter-based design
NI-LabVIEW
data logging
MATLAB
fast Fourier transform
remote control access
smart meters
virtual instrumentation
smart energy meter
SEM virtual instrument
energy-metering algorithm
ALTERA Cyclone IV E FPGA board
field programmable gate array
power meters
power quality-event detection
loss evaluation
ISSN:1751-8822, 1751-8830
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Popis
Shrnutí:Power quality (PQ) is crucial parameter in determining the robustness and accuracy of any energy-metering algorithm. It immensely affects the performance of energy meters in terms of measurement accuracy. This study presents digital implementation of fast discrete Stockwell transform (FDST) with automatic scaling for accurate PQ-event detection (ED) and energy metering. Comparative analysis of FDST-based energy-metering algorithm is carried out with existing algorithms such as fast Fourier transform and filter-based design. The results demonstrate that FDST-based energy-metering algorithm surpasses existing algorithms in terms of accuracy, complexity, and adaptability under PQ events. In addition, new statistical features are proposed to classify and measure PQ events. The real-time implementation of the proposed FDST-based smart energy meter (SEM) is performed in national instruments (NI) laboratory virtual instrument engineering workbench (LabVIEW) and validated through field programmable gate array (FPGA)-in-the-loop using MATLAB and Altera Cyclone IV E FPGA board. The experimental results show satisfactory performance in terms of accuracy and resource utilisation. The effect of PQ events over energy metering is evaluated in terms of percentage loss in billing units. The features of the proposed SEM virtual instrument are real-time accurate PQ-ED, energy metering, loss evaluation, data logging, and remote control access.
ISSN:1751-8822
1751-8830
DOI:10.1049/iet-smt.2016.0481