Virtual instrument as a tool for teaching power quality

2009 ◽  
Vol 1 (07) ◽  
pp. 842-847 ◽  
Author(s):  
Vladimir Dimcev ◽  
Zivko Kokolanski ◽  
Cvetan Gavrovski ◽  
Mare Srbinovska
2013 ◽  
Vol 427-429 ◽  
pp. 2441-2444
Author(s):  
Wei Chen ◽  
Long Chen ◽  
Ming Li

This paper presents a software design useful for power quality analysis and data management. The software was programmed in LabVIEW and Oracle, running on Windows in a regular PC. LabVIEW acquires data continuously from the lower machine via TCP/IP. Using its database connection toolkit, LabVIEW accesses to Oracle to stores and retrieve the power quality data according to different indicators. A friendly GUI was built for data display and user operation, taking advantage of the powerful data-handling capacity of LabVIEW and its rich controls. Moreover, Excel reports can be exported using report generation toolkit in LabVIEW. The software greatly improves the data analysis and management capacity.


2011 ◽  
Vol 143-144 ◽  
pp. 917-920
Author(s):  
Geng Hui Zhu ◽  
Jiao Xia Wang

The monitoring of power quality is the foundation and prerequisite of its improvement. There are a lot of disadvantages in the conventional method of power quality monitoring, the adoption of the virtual instrument and network technology can overcome these disadvantages very well. Remote power quality monitoring system based on LabVIEW was put forward, as well as the way of the combination of software and hardware and the realization procedure is illustrated in detail in this paper. Then the merits of this way are mentioned, and the additional functions that can be further developed. This paper provides a more convenient way for the realization of remote power quality monitoring


2016 ◽  
Vol 13 (10) ◽  
pp. 7099-7109
Author(s):  
M. K Elango ◽  
A Jagadeesan ◽  
K. Mohana Sundaram

This paper develops a real time solution for detecting the Power Quality events. Fourteen events are generated through experimental setup and the signals are acquired through a voltage Data Acquisition Card, NI DAQ-9225, controlled by a Virtual Instrument software package. The features extracted from the Wavelet Transformation are fed into the Back Propagation Neural Network for training. By the virtue of a Neural Network property, it gets self-adapted and self-learned aiding in automatic classification of Power Quality Events. A combination of Wavelet Transform technique and Neural Networks are employed to detect and characterize the Power Quality Disturbances. The result obtained shows the effectiveness of the Wavelet Packet Transform based Back Propagation algorithm in classifying the Power Quality Disturbances. The results produced by the proposed methodology based Back Propagation Algorithm is verified with the Power Quality Analyser.


2012 ◽  
Vol 466-467 ◽  
pp. 759-762 ◽  
Author(s):  
Fan Yang ◽  
Hui Zhao

The traditional quality analysis system has many disadvantages such as the bulky, expensive, fixed functional modules, poor extension, monotonous display etc. Combined with the virtual instrument technology, the paper propose design ideas of instrument Virtual power quality analysis based on LabWindows/CVI, including design of hardware circuit and software, obtain harmonic amplitude and phase by making use of fast Fourier transform. The analyzer has high accuracy, stable, and good anti-jamming performance, meet the electric power system testing requirements.


2018 ◽  
Vol 17 (2) ◽  
pp. 93
Author(s):  
Dragan Živanović ◽  
Milan Simić ◽  
Dragan Denić ◽  
Živko Kokolanski

Generation of typical power quality (PQ) events, based on Script files and virtual instrumentation, is presented in this paper. Such approach provides definition and generation of three-phase voltage signals with various PQ events defined according to relevant international quality standards. Using of Script files enables easy and flexible generation of long-time voltage signals with complex PQ disturbances, according to the predefined test algorithms and scenarios. Detailed front panels and block diagrams of developed virtual instrument for signal generation are described in the paper. As specific examples, generated signals defined using the Script files are presented. Experimental confirmation of described software supported method is performed using the three-phase PQ analyzer Fluke 435. Some specific test waveforms and obtained experimental results are shown.


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