The Power Quality Monitoring System Based on Virtual Instrument

Yang, Huping; Zhipeng, Bi

doi:10.1109/wcse.2009.47

Cited by 8 publications

(2 citation statements)

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“…It contains functions that are easily understood and utilized by the user, and a variety of features and tools that are familiar to EE [7]. This set of tools can be used for acquiring, analyzing, displaying and storing data [8].…”

Section: Proposed Systemmentioning

confidence: 99%

Design of Power Quality Virtual Lab Toolbox using LabVIEW/Multisim

Haidar¹,

Moussa²,

Hassan³

et al. 2023

RE&PQJ

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This paper presents a Power Quality (PQ) virtual lab that can be used by electrical engineers (EE) to enhance their knowledge and awareness on power quality disturbances in accordance to power quality standards. It will offer the EE the facility to become more aware about the problems tackling power systems and nonlinear devices, and their effects on the power quality indices. This work is built using NI LabVIEW/Multisim and is composed out of many simulations and experiments each with its learning objectives. The established measured power quality indices are mainly the root mean square (RMS), the total harmonic distortion (THD), the distortion index (DIN), the telephone influence factor (TIF), the crest factor (CF), the voltage transformer product (VT), the current transformer product (IT), the displacement power factor (DPF), the true power factor (TPF) and the unbalance factor (UF). Each of these indices is measured and analyzed in order to check how they are affected by the PQ issues.

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Section: Proposed Systemmentioning

confidence: 99%

Design of Power Quality Virtual Lab Toolbox using LabVIEW/Multisim

Haidar¹,

Moussa²,

Hassan³

et al. 2023

RE&PQJ

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“…Other monitoring systems perform real-time processing and provide PQ indicators [10]- [13]. However, industrial grade instrumentation specifically designed for PQ monitoring is relatively expensive, hence the focus in recent years on development of virtual instrumentation-based PQ monitoring systems [14]- [19], as well as algorithms for fast and accurate detection and classification of PQ disturbances, such as the ones presented in [20], [21]. These solutions are decentralized and are more flexible and cost-effective, but require a large amount of curated PQ disturbance data, which can be difficult to obtain.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the uncertainty of a virtual power quality disturbance generator and its use in power quality classifier evaluation

Velkovski,

Markovska,

Kokolanski

et al. 2023

Acta IMEKO

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This paper presents the metrological evaluation of a proposed virtual power quality (PQ) disturbance generator. It explains in detail the calibration and measurement uncertainty estimation procedures for the RMS voltage and frequency of the generator, presents the results, and discusses their implications. The results indicate that the measurement uncertainty of the generator is satisfactory for all reference points, making it suitable for generation of PQ signals for research purposes, particularly in the development, testing, and improvement of PQ event classifiers. Additionally, the paper introduces a virtual power quality disturbance classifier for real-time classification of PQ events and verifies its accuracy through testing using the proposed PQ disturbance generator.

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