Power quality problem classification using support vector machine

Susukh, Jatumeth; Premrudeepreechacharn, S.; Kasirawat, T.

doi:10.1109/ecticon.2009.5136965

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…For example, in Axelberg, Gu, and Bollen (2007) it is concluded that the classifier reduces its effectiveness when tested for field signals. Despite the fact that some authors focus their research using real signals (Axelberg et al, 2007;Eristi & Demir, 2012;Susukh, Premrudeepreechacharn, & Kasirawat, 2009), these waveforms present only one event at a time. However, this is not the typical case, since it is very frequent to have more than one event within the same time frame.…”

Section: Introductionmentioning

confidence: 99%

An effective Power Quality classifier using Wavelet Transform and Support Vector Machines

Yong

Bhowmik

Magnago

2015

Expert Systems with Applications

153

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Section: Introductionmentioning

confidence: 99%

An effective Power Quality classifier using Wavelet Transform and Support Vector Machines

Yong

Bhowmik

Magnago

2015

Expert Systems with Applications

153

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“…It can detect the supply voltage in real time. When a voltage sag occurs, the inverter of the DVR instantaneously generates a dynamic compensation voltage to compensate for the dropped voltage to the rated value, thus ensuring normal operation of sensitive loads in the power system (Ho and Chung, 2010;Li et al, 2007a;Susukh et al, 2009;Woodley, 2000).…”

Section: Introductionmentioning

confidence: 99%

Digital control strategy and realization for harmonic compensation of dynamic voltage restorer

Wang

Zhang

et al. 2014

Transactions of the Institute of Measurement and Control

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In order to make the dynamic voltage restorer (DVR) concurrently compensate for low-order harmonics and voltage sag, and eliminate the influence of digital control on system performance, we propose a novel double closed-loop digital control strategy, consisting of the fundamental proportional resonant (PR) control in a voltage loop and selective harmonic PR control in an inductance current loop. Then, we mainly analyse the discretization effects of the virtual LC method and the step response method, and further present a straightforward digital design method. Next, with this method, we design the parameters of the fundamental and selective harmonic PR controllers in the discrete domain, which inhibit the influence of sampling, calculation delay etc. on the steady-state error and the dynamic response performance. Finally, an 11-kVA DVR prototype is developed and tested. The experimental results indicate that the proposed control strategy satisfies the requirement of voltage quality for sensitive loads and achieves a good dynamic response performance.

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Efficient Support Vector Regression with Weighted Constraints

Wang

2011

Informatics in Control, Automation and Robotics

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Power quality problem classification using support vector machine

Cited by 5 publications

References 17 publications

An effective Power Quality classifier using Wavelet Transform and Support Vector Machines

An effective Power Quality classifier using Wavelet Transform and Support Vector Machines

Digital control strategy and realization for harmonic compensation of dynamic voltage restorer

Efficient Support Vector Regression with Weighted Constraints

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