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2015
DOI: 10.1109/tpwrd.2014.2362957
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Identification of Weak Areas of Network Based on Exposure to Voltage Sags—Part II: Assessment of Network Performance Using Sag Severity Index

Abstract: Abstract--This paper presents a new stochastic approach to comprehensive assessment of the impact of voltage sags in large scale power networks. The approach takes into account the stochastic nature of power system operation including load variation, uncertainty of fault clearing time by protection relays, fault rates of network components and the variation/uncertainty in equipment sensitivity to voltage sags. A new duration zone division method is used to derive sag duration and occurrence frequency based on … Show more

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Cited by 41 publications
(32 citation statements)
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“…In the study, Bus Performance Index (BPI) [24,25] is adopted to evaluate the severity of voltage sag phenomena from the perspective of utilities and customers in distribution networks. This index takes into account various sag characteristics simultaneously as well as sensitivity of equipment to voltage sags.…”
Section: Evaluation Methodologiesmentioning
confidence: 99%
“…In the study, Bus Performance Index (BPI) [24,25] is adopted to evaluate the severity of voltage sag phenomena from the perspective of utilities and customers in distribution networks. This index takes into account various sag characteristics simultaneously as well as sensitivity of equipment to voltage sags.…”
Section: Evaluation Methodologiesmentioning
confidence: 99%
“…Their residual part (i.e., the combined effect between DA −′ and FA − ) together with current DB − caused by the DG connected at B6 results in peak | − | at B6. The proposed approach is further validated on a 96-bus section of a generic UK distribution network [19,20], which is likely to be exposed to unbalance phenomena if unbalance sources exist in the network.…”
Section: Propagation Of Negative-sequence Voltagementioning
confidence: 99%
“…This concept is borrowed from utility reliability management practice [27], and driven by the need to compare the PQ performance among utility companies or among various feeders. Various techniques have been explored for VSSE in literature, e.g., fault location, probability based methods and Monte Carlo methods [28,29].…”
Section: Power Quality Sementioning
confidence: 99%