Propagation of Asymmetrical Sags and the Influence of Boundary Crossing Lines on Voltage Sag Prediction

Aung, Myo Thu; Milanović, Jovica V.; Gupta, C. P.

doi:10.1109/tpwrd.2004.835427

Cited by 49 publications

(12 citation statements)

References 6 publications

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“…The study was performed on a generic distribution system (GDS) comprised of four 275-kV transmission infeeds, 132-kV and 33-kV subtransmission networks (predominantly meshed), and an 11-kV distribution network (predominantly radial) [3], [4]. The GDS consists of 295 buses, 296 overhead lines and underground cables, and a large number of switches and circuit breakers (CBs) in order to alter the network topology for preventive control and better reliability of the system.…”

Section: Study Resultsmentioning

confidence: 99%

“…For the voltage sag assessment, the method of fault positions is used considering fault positions on network buses as well as on transmission lines (one fault position per bus and six fault positions per line) [3]. Voltage sag magnitudes at the network buses are calculated for symmetrical and unsymmetrical faults at these fault positions spread throughout the GDS (a total of about 8300 faults).…”

Section: Study Resultsmentioning

confidence: 99%

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Probabilistic Assessment of Financial Losses due to Interruptions and Voltage Sags—Part II: Practical Implementation

Milanović

Gupta

2006

IEEE Trans. Power Delivery

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111

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The second part of this paper presents a practical implementation and application of the methodology for the stochastic assessment of the annual financial losses due to interruptions and voltage sags discussed in the first part of this paper. The costs of interruptions and voltage sags are determined separately and then combined in order to estimate the total financial losses in the network. The methodology is illustrated on a generic realistic distribution network with all relevant network components modeled appropriately. Finally, different network topologies are compared taking into account total financial losses in the network. It is shown that the inclusion of the financial losses due to voltage sags that may account for up to about 20% of the interruption costs may alter the network topology ranking.

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Section: Study Resultsmentioning

confidence: 99%

Section: Study Resultsmentioning

confidence: 99%

Probabilistic Assessment of Financial Losses due to Interruptions and Voltage Sags—Part II: Practical Implementation

Milanović

Gupta

2006

IEEE Trans. Power Delivery

Self Cite

111

View full text Add to dashboard Cite

show abstract

“…Both of these tables show the average error in per unit across all estimated profiles of the given fault type. This error is calculated using (5).…”

Section: A Comparison Using Average Errorsmentioning

confidence: 99%

“…Although voltage monitoring at all buses in the network is the most effective way to assess sag performance [5], such a 978-1-4244-7245-1/10/$26.00 ©2010 IEEE monitoring scheme is unaffordable and only a limited number of monitors can be located in a network. This poses the need to determine the minimum number and location of monitors that guarantee the maximum observability of sag events which allows estimating the sag performance of monitored and non-monitored buses.…”

Section: Introductionmentioning

confidence: 99%

A comparison of voltage sag estimation algorithms using optimal monitorring locations

Woolley

Avendano-Mora

Milanović

2010

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

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The aim of voltage profile sag estimation (VPSE) is to reconstruct the voltage profile at non-monitored buses using measurements only from monitored buses. This paper compares two methods for voltage profile estimation: one which focuses on fault localization and another which reconstructs profiles using voltage thresholds. The two algorithms are compared using a generic 295 bus generic distribution network and 4 sets of monitoring locations. The 4 monitoring locations are selected using a bespoke artificial immune system optimization algorithm. The results of the two methods are compared by analyzing the distribution of error between the two methods and the estimated generalized sag tables of both algorithms. Preliminary results suggest that the two methods are very comparable in performance. Both algorithms are shown to be sensitive to the selected monitoring locations, and perform well even when the number of monitors is much less than the number of buses.

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“…Voltage sag generally refers to instantaneous short-duration reduction in root-mean-square (RMS) voltage, which the characteristic duration of voltage sag is between 0.5 to 30 cycles with typical magnitude of 0.1 to 0.9 per unit [1,2,3]. Voltage sag is one of important power quality disturbances in power system due to its widespread effect if happens.…”

Section: Introductionmentioning

confidence: 99%

Voltage sag evaluation in unbalanced three-phase distribution network with distributed generations

Jia¹,

Liu²,

Meng³

et al. 2015

International Conference on Renewable Power Generation (RPG 2015)

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This paper proposes a new algorithm to evaluate the voltage sag in unbalanced three-phase distribution network with distributed generations DG . The paper models fault characteristics (fault line, location, type, duration, impedance) and DG output. By using two point estimation method (2PEM), the random probability problem in voltage sag simulation is transformed into multiple deterministic problems. Through computing the mean, the standard deviation and the third central moment of each node in distribution network, the probability density functions (PDF) of each node can be got based on Cornish-Fisher expansion (CFE) series, and then the voltage sag index System Average Root Mean Square Variation Frequency Index (SARFI) can be computed. Weak branches in distribution network are analyzed. Experiments have been made on the IEEE 13-bus test case with the consideration of two stochastic DG units. Thirteen scenarios simulations about voltage sag and comparison with Monte Carlo Simulation have been made. The comparisons with different wind turbine models have been provided. The feasibility and effectiveness of the proposed algorithm for voltage sag evaluation have been proved.

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Propagation of Asymmetrical Sags and the Influence of Boundary Crossing Lines on Voltage Sag Prediction

Cited by 49 publications

References 6 publications

Probabilistic Assessment of Financial Losses due to Interruptions and Voltage Sags—Part II: Practical Implementation

Probabilistic Assessment of Financial Losses due to Interruptions and Voltage Sags—Part II: Practical Implementation

A comparison of voltage sag estimation algorithms using optimal monitorring locations

Voltage sag evaluation in unbalanced three-phase distribution network with distributed generations

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