Categorization and Analysis of Power System Transients

Bollen, M.H.J.; Styvaktakis, E.; Gu, Irene Yu‐Hua

doi:10.1109/tpwrd.2004.843386

Cited by 105 publications

(54 citation statements)

References 14 publications

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“…6 shows the voltage and frequency waveforms during an islanding event with a dynamic load. Since the load reactive power for the dynamic load has no frequency dependence (refer to (21)) and the DG operates at unity power factor, the frequency during islanding will not stabilize and, thus, islanding becomes easy to detect. For RLC loads, similar results are obtained with Similarly, for brevity, some nonislanding events are presented in Figs.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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A Bayesian Passive Islanding Detection Method for Inverter-Based Distributed Generation Using ESPRIT

Najy¹,

Zeineldin²,

Alaboudy³

et al. 2011

IEEE Trans. Power Delivery

111

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In this paper, a new passive islanding detection method for grid-connected inverter-based distributed-generation (DG) systems is proposed. A statistical signal-processing algorithm known as estimation of signal parameters via rotational invariance techniques is used to extract new features from measurements of the voltage and frequency at the point of common coupling as islanding indicators. The new features are defined based on a damped-sinusoid model for power system voltage and frequency waveforms, and include modal initial amplitudes, oscillation frequencies, damping factors, and initial phases. A set of training cases generated on the IEEE 34-bus system was used to train a naïve-Bayes classifier that discriminates islanding and nonislanding events. Cross-validation was used to evaluate the performance of the proposed islanding detection method. The results show that by using the new features extracted from ESPRIT, the classifier is capable of discriminating islanding and nonislanding events with an accuracy close to 100%. Index Terms-Estimation of signal parameters via rotational invariance techniques (ESPRIT), inverter-based distributed generation (DG), islanding detection, naïve-Bayes classification, power systems.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The implementation of the algorithm in power systems was first proposed in [21]. In power systems, the most common type of waveform encountered is one where a disturbance causes an oscillating transient that dies away with time.…”

Section: A Espritmentioning

confidence: 99%

A Bayesian Passive Islanding Detection Method for Inverter-Based Distributed Generation Using ESPRIT

Najy¹,

Zeineldin²,

Alaboudy³

et al. 2011

IEEE Trans. Power Delivery

111

View full text Add to dashboard Cite

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“…1,2 Voltage sensors based on electro-optical crystals such as Bi 4 Ge 3 O 12 , bismuth silicate and LiNbO 3 have been applied in high voltage systems [3][4][5][6][7][8] because of their wide operating bands, rapid response characteristics, low electromagnetic interference characteristics, and low optical transmission loss. However, some of these sensors have high half-wave voltages and low electro-optic coefficients, and are less sensitive to low voltage signals.…”

Section: Introductionmentioning

confidence: 99%

Temperature characteristics of Pockels electro-optic voltage sensor with double crystal compensation

et al. 2016

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Voltage sensors based on the Pockels electro-optic effect in LiNbO 3 crystals have been applied to practical engineering measurements because of their passive nature, wide operating bands, and low transmission loss. However, the temperature of the measurement environment can greatly affect the dynamic responses of these sensors because the natural birefringence of a single LiNbO 3 crystal voltage sensor (SVS) is related to its temperature. To improve the stability of this sensor over a wide temperature range, a double crystal compensation method is introduced in this paper to compensate for the natural birefringence of the SVS. A double LiNbO 3 crystal voltage sensor (DVS) was fabricated, and its working point drift characteristics and amplitude-frequency response were investigated over the temperature range from 0 • C to 50• C. The effects of two intrinsic parameters of the LiNbO 3 crystal were also investigated. Comparison between an existing SVS and the proposed DVS showed that the DVS resisted environmental temperature fluctuations more strongly. C 2016 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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“…Furthermore, nonlinear power electronic loads such as converter driven equipment have become increasingly common in power system. Poor quality [2,3] is attributed due to the various power line disturbances. In brief, PQ problems can cause system equipment malfunction; computer data loss and memory malfunction of sensitive loads such as computer, programmable logic controller controls, protection and relaying equipment; and erratic operation of electronic controls [4].…”

Section: Introductionmentioning

confidence: 99%