Power quality: a review

Kazibwe, W.E.; Ringlee, R. J.; Woodzell, G.W.; Sendaula, H.M.

doi:10.1109/67.53204

Cited by 26 publications

(9 citation statements)

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“…According to the periodicity of power disturbances, the power disturbance waveforms can be classified as stationary or non-stationary signals [1][2]. For stationary signals or periodic waveforms, Fast Fourier transform (FT) is good for signal analysis.…”

Section: Introductionmentioning

confidence: 99%

Power Disturbance Recognition Using Back-Propagation Neural Networks

Wang¹

2012

IJET

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This paper presents power disturbance recognition using back-propagation neural networks (BPNN). First, the discrete wavelet transform is used to extract the features of the power disturbance waveforms in the form of series coefficients of several levels. The Parseval theory is then utilized to calculate the energy of each level so that the number of coefficients can be reduced; then, the extracted results are used for recognition by the BPNN. Multi-event power disturbances are also fed to the recognition system for testing. From experiment results, the recognition rate is at least 83.67%. It proves the feasibility of the proposed method. Index Terms-Discrete wavelet transforms (DWT), power quality, back-propagation neural networks, parseval theory.

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Section: Introductionmentioning

confidence: 99%

Power Disturbance Recognition Using Back-Propagation Neural Networks

Wang¹

2012

IJET

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“…Power quality events can be classified into seven types; flicker, frequency variation, harmonics, swell (over voltages), transient, voltage interruptions and voltage sag (under voltage) [1]- [3]. Among these types of power quality events, voltage sag is the most important problem to be considered especially by the industries [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

Voltage sags observation through optimal monitor locations

Salim

Nor

2010

Proceedings of 14th International Conference on Harmonics and Quality of Power - ICHQP 2010

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the concern towards voltage sag has increased rapidly due to the amount of losses it created. Throughout the world, many researchers have proposed a study on the characteristics and the mitigation methods which may be used to overcome or reduce the effect cause by the voltage sag. In this paper, a method that used a minimum number of power quality monitors has been proposed to monitor the occurrence of voltage sags in the utility system. By using the area of vulnerability concept, the optimal monitor locations with zero blind spot area can be determined. The proposed method also used the concept of monitor redundancy to ensure the correctness of the monitor reading, validation purposes and to ensure the reliability of the monitoring system is 100%. The proposed method has been tested with two standards system; IEEE 30-bus system and IEEE 300-bus system and the results then is compared with other monitoring method.

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“…ue to the extensive application of nonlinear loads and the introduction of renewable energy devices the load current usually contains harmonic components that affect the operating characteristic of the overcurrent relay. The technical literature is filled with documents and references to harmonics in power systems [1][2][3][4][5][6][7][8][9], however, few have addressed the influence of these waveform distortions on protective relays [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Impact of harmonics on tripping time of overcurrent relays

Masoum

Islam

Tan

et al. 2007

2007 Australasian Universities Power Engineering Conference

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Theoretical and experimental analyses are used to investigate the effects of harmonics on the operation of overcurrent relays. Two analytical approaches based on relay characteristics provided by the manufacturer and simulations using PSCAD software package are used to estimate tripping times under non-sinusoidal operating conditions. The tests were conducted such that the order and the magnitude of harmonics could be controlled by employing a computer-based single-phase harmonic source. Computed and measured tripping times are compared and suggestions on the application of overcurrent relays in harmonically polluted environments are provided.

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Power quality: a review

Cited by 26 publications

References 0 publications

Power Disturbance Recognition Using Back-Propagation Neural Networks

Power Disturbance Recognition Using Back-Propagation Neural Networks

Voltage sags observation through optimal monitor locations

Impact of harmonics on tripping time of overcurrent relays

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