Effects of balanced and unbalanced voltage sags on DC adjustable-speed drives

Pedra, J.; Sainz, L.; Córcoles, F.; Bergas, J.; Hoyo, Alfredo de Blas del

doi:10.1016/j.epsr.2007.07.007

Cited by 13 publications

(3 citation statements)

References 11 publications

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“…Some characteristics, e.g., "single-event characteristics" and "single-segment characteristics", are introduced in [8][9][10]. Besides magnitude and duration, which are defined in standards [1][2][3][4], additional characteristics are required, e.g., the sag type [9], phase-angle jump [10], point-on-wave [15], unbalance [1,16], etc. In general, segmentation is a prerequisite process to obtain these characteristics that helps network operators and end-users to analyze sag events completely.…”

Section: Application Of the Segmentation Methods To A Voltage Sag Wavementioning

confidence: 99%

An Adaptive Approach for Voltage Sag Automatic Segmentation

Xiao

Zhang

et al. 2018

Energies

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Voltage sag characterization is essential for extracting information about a sag event’s origin and how sag events impact sensitive equipment. In response to such needs, more characteristics are required, such as the phase-angle jump, point-on-wave, unbalance, and sag type. However, the absence of an effective automatic segmentation method is a barrier to obtaining these characteristics. In this paper, an automatic segmentation method is proposed to improve this situation. Firstly, an extended voltage sag characterization method is described, in which segmentation plays an important role. Then, a multi-resolution singular value decomposition method is introduced to detect the boundaries of each segment. Further, the unsolved problem of how to set a threshold adaptively for different waveforms is addressed, in which the sag depth, the mean square error, and the entropy of the sag waveform are considered. Simulation data and field measurements are utilized to validate the effectiveness and reliability of the proposed method. The results show that the accuracies of both boundary detection and segmentation obtained using the proposed method are higher than those obtained using existing methods. In general, the proposed method can be implemented into a power quality monitoring system as a preprocess to support related research activities.

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Section: Application Of the Segmentation Methods To A Voltage Sag Wavementioning

confidence: 99%

An Adaptive Approach for Voltage Sag Automatic Segmentation

Xiao

Zhang

et al. 2018

Energies

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“…As they can be provoked by different events related to a transmission or distribution network or even to the customer, the frequency of voltage sags can be between a few ten and even several thousand times per year [3]. The impact of disturbances caused by voltage sags on production losses, different types of electrical machines and industrial equipment have already been reported [4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Instantaneous positive‐sequence current applied for detecting voltage sag sources

Polajžer

Štumberger

Dolinar

2015

IET Generation, Transmission & Distribution

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This study proposes a method for detecting voltage-sag sources, using only the measurements of line currents. Instantaneous symmetrical components are introduced for accommodating the transient nature of voltage sag events, where a magnitude and phase change in the instantaneous positive-sequence current is used as a criterion. The proposed method is compared with conventional phasor-based methods known from the literature. All the discussed methods for voltage sag source detection, both the already known and the proposed ones, were evaluated by applying extensive simulations, laboratory tests and field testing. When compared with the phasor-based methods, the proposed method showed faster response, a higher degree of confidence and superior effectiveness, especially for transient voltage sag events in networks with distributed generation and active loads.

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“…However, from the point of view of effective data analysis, the two basic characteristics defined in these standards are insufficient for extracting information about underlying cause of voltage sag and the status of the power system. In addition, rather than magnitude and duration, new type electronic equipment may be sensitive to additional characteristics [5]- [8]. International working group JWG C4.110 sponsored by CIGRE/CIRED/UIE has presented a report about the research results aiming at improving the understanding of the compatibility between installations and the electricity supply [8].…”

Section: Introductionmentioning

confidence: 99%

Automatic segmentation method for voltage sag detection and characterization

Xiao

Yun-Ling

et al. 2018

2018 18th International Conference on Harmonics and Quality of Power (ICHQP)

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Although characterization of voltage sag is an essential part of voltage sag studies, the way that taking magnitude and duration as acknowledged basic characteristics cannot describe sag characteristics versus time. Hence automatic segmentation, which divides monitoring data sequence into segments, and characterization algorithm are proposed in this paper. The difficulty that how to divide segment automatically is overcome through two-stage segmentation algorithm based on singular value decomposition method. Then multi-dimension characteristics such as magnitude, duration, phase-angle jump, sag type and so on can be calculated. Hundreds of sag events data including measured in field and synthetic are utilized to validate the effectiveness and reliability of proposed method. Moreover, the detection and characterization algorithm are ported to installed monitors and backstage data center with C programming, timesaving and practical get validated.

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Effects of balanced and unbalanced voltage sags on DC adjustable-speed drives

Cited by 13 publications

References 11 publications

An Adaptive Approach for Voltage Sag Automatic Segmentation

An Adaptive Approach for Voltage Sag Automatic Segmentation

Instantaneous positive‐sequence current applied for detecting voltage sag sources

Automatic segmentation method for voltage sag detection and characterization

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