On the public citation graph

Bayesian-Inference-Based Voltage Dip State Estimation

https://doi.org/10.1109/tim.2017.2734138
0 signed · 51 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119373940openalex-snapshot
System Reliability Theory: Models, Statistical Methods, and Applications
inferredcites →https://doi.org/10.1007/978-3-319-41644-1openalex-snapshot
Bayesian Inference : Data Evaluation and Decisions
inferredcites →https://doi.org/10.1016/j.epsr.2007.10.003openalex-snapshot
Short-circuit calculations in networks with distributed generation
inferredcites →https://doi.org/10.1016/j.epsr.2016.04.016openalex-snapshot
Harmonic disturbance location by applying Bayesian inference
inferredcites →https://doi.org/10.1049/iet-gtd.2010.0148openalex-snapshot
Voltage sag state estimation in power systems by applying genetic algorithms
inferredcites →https://doi.org/10.1049/ip-c.1983.0057openalex-snapshot
Accurate fault impedance locating algorithm
inferredcites →https://doi.org/10.1093/oso/9780198502784.001.0001openalex-snapshot
Approximating Integrals via Monte Carlo and Deterministic Methods
inferredcites →https://doi.org/10.1109/28.740859openalex-snapshot
Stochastic prediction of voltage sags in a large transmission system
inferredcites →https://doi.org/10.1109/icps.1998.692526openalex-snapshot
Stochastic prediction of voltage sags in a large transmission system
inferredcites →https://doi.org/10.1109/iecon.2015.7392216openalex-snapshot
Voltage dip state estimation in distribution networks by applying Bayesian inference
inferredcites →https://doi.org/10.1109/jpets.2015.2477598openalex-snapshot
A Bayesian Approach for Fault Location in Medium Voltage Grids With Underground Cables
inferredcites →https://doi.org/10.1109/pesgm.2014.6939168openalex-snapshot
Optimized monitoring of voltage sags in distribution systems caused by balanced and unbalanced short-circuits
inferredcites →https://doi.org/10.1109/tim.2009.2014504openalex-snapshot
State Estimation for the Localization of Harmonic Sources in Electric Distribution Systems
inferredcites →https://doi.org/10.1109/tim.2010.2045256openalex-snapshot
Accuracy Analysis of Algorithms Adopted in Voltage Dip Measurements
inferredcites →https://doi.org/10.1109/tim.2011.2126910openalex-snapshot
Harmonic Source Estimation in Distribution Systems
inferredcites →https://doi.org/10.1109/tim.2013.2243502openalex-snapshot
Robustness-Oriented Meter Placement for Distribution System State Estimation in Presence of Network Parameter Uncertainty
inferredcites →https://doi.org/10.1109/tim.2013.2278996openalex-snapshot
Survey on Voltage Dip Measurements in Standard Framework
inferredcites →https://doi.org/10.1109/tpwrd.2004.835052openalex-snapshot
The Influence of Fault Distribution on Stochastic Prediction of Voltage Sags
inferredcites →https://doi.org/10.1109/tpwrd.2005.860266openalex-snapshot
An Analytical Approach for Stochastic Assessment of Balanced and Unbalanced Voltage Sags in Large Systems
inferredcites →https://doi.org/10.1109/tpwrd.2007.905587openalex-snapshot
A Method for Voltage Sag State Estimation in Power Systems
inferredcites →https://doi.org/10.1109/tpwrd.2012.2218627openalex-snapshot
SVD Applied to Voltage Sag State Estimation
inferredcites →https://doi.org/10.1109/tpwrs.2004.825824openalex-snapshot
Failure Rate Modeling Using Equipment Inspection Data
inferredcites →https://doi.org/10.1109/tpwrs.2005.846174openalex-snapshot
Voltage Sag State Estimation for Power Distribution Systems
inferredcites →https://doi.org/10.1109/tpwrs.2005.857837openalex-snapshot
An Optimal Monitoring Program for Obtaining Voltage Sag System Indexes
inferredcites →https://doi.org/10.1109/tsg.2014.2343672openalex-snapshot
Optimization of State-Estimator-Based Operation Framework Including Measurement Placement for Medium Voltage Distribution Grid
inferredcites →https://doi.org/10.1198/tech.2004.s242openalex-snapshot
System Reliability Theory: Models, Statistical Methods, and Applications
inferredcites →https://doi.org/10.5860/choice.37-4522openalex-snapshot
Understanding power quality problems: voltage sags and interruptions
inferredcites →https://doi.org/10.6100/ir651978openalex-snapshot
Intelligent distribution network design

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3978436openalex-extracted
A Deep Learning Method Based on Bidirectional Wavenet for Voltage Sag State Estimation Via Limited Monitors in Power System
inferred← citeshttps://doi.org/10.2139/ssrn.4018993openalex-extracted
A Deep Learning Method Based on Bidirectional Wavenet for Voltage Sag State Estimation Via Limited Monitors in Power System
inferred← citeshttps://doi.org/10.1007/978-981-97-1351-6_43openalex-snapshot
Probability Density Assessment of Voltage Sag Based on Hamiltonian Monte Carlo Method
inferred← citeshttps://doi.org/10.1016/j.apenergy.2025.126891openalex-snapshot
Causes identification and sources localization method for multistage voltage sag under the influence of high penetration of renewable energy sources
inferred← citeshttps://doi.org/10.1016/j.ijepes.2019.06.005openalex-snapshot
Incorporating network uncertainties in voltage dip state estimation
inferred← citeshttps://doi.org/10.1016/j.ijepes.2022.108119openalex-snapshot
A novel voltage sag state estimation method based on complex network analysis
inferred← citeshttps://doi.org/10.1016/j.ijepes.2022.108757openalex-snapshot
Premium power supply scheme based on leasing mitigation equipment against voltage sag
inferred← citeshttps://doi.org/10.1016/j.ijepes.2025.111136openalex-snapshot
A practical approach to voltage sag estimation in power networks
inferred← citeshttps://doi.org/10.1088/1742-6596/1346/1/012024openalex-snapshot
Comprehensive Evaluation of Two-side Voltage Sag based on Local State Variable Weight and Complex Correlation Coefficient Method
inferred← citeshttps://doi.org/10.1109/access.2019.2935404openalex-snapshot
A Bayesian Inference Method and its Application in Fatigue Crack Life Prediction
inferred← citeshttps://doi.org/10.1109/access.2022.3202309openalex-snapshot
A Comprehensive Overview on Modified Versions of Stockwell Transform For Power Quality Monitoring
inferred← citeshttps://doi.org/10.1109/cieec47146.2019.cieec-2019107openalex-snapshot
Comparison of the Application Effect of Existing Classification Algorithms by Measured Voltage Dip
inferred← citeshttps://doi.org/10.1109/contesa52813.2021.9657149openalex-snapshot
A 2-d State Observer Using Particle Filter by Incorporation of Batch-to-Batch Dynamics
inferred← citeshttps://doi.org/10.1109/icee50131.2020.9260574openalex-snapshot
Estimation of Number of Voltage Sags in the IEEE 14-Bus Network Using Bayesian and Artificial Neural Network: A Case Study
inferred← citeshttps://doi.org/10.1109/pesgm51994.2024.10688503openalex-snapshot
A Bayesian Method to Infer Parameters in Power Flow Models Using Linear Sensitivities
inferred← citeshttps://doi.org/10.1109/tpwrd.2018.2865906openalex-snapshot
Voltage Sag Estimation in Sparsely Monitored Power Systems Based on Deep Learning and System Area Mapping
inferred← citeshttps://doi.org/10.1109/tpwrd.2022.3198854openalex-snapshot
Multi-Stage Voltage Sag State Estimation Using Event-Deduction Model Corresponding to EF, EG, and EP
inferred← citeshttps://doi.org/10.1109/tpwrd.2024.3404567openalex-snapshot
A Generic Severity Estimation Method for Lightning-Caused Voltage Sags by Using Multiplatform Monitoring Data Mining
inferred← citeshttps://doi.org/10.12677/airr.2023.122016openalex-snapshot
Power Line Sag Interval Prediction Basedon QRGBDT for UAV InspectionScenario
inferred← citeshttps://doi.org/10.29121/ijetmr.v5.i9.2018.285openalex-snapshot
TO SURVEY POWER QUALITY OF HIGH VOLTAGE KEY-CUSTOMER BY USING VOLTAGE EVENT RECORD
inferred← citeshttps://doi.org/10.3389/fphy.2025.1624919openalex-snapshot
Grid fault diagnosis based on the deep pyramid convolutional neural network
inferred← citeshttps://doi.org/10.3390/en15062273openalex-snapshot
A Deep Learning Method Based on Bidirectional WaveNet for Voltage Sag State Estimation via Limited Monitors in Power System
inferred← citeshttps://doi.org/10.5204/thesis.eprints.124659openalex-snapshot
Distribution Network State Estimation, Time Dependency and Fault Detection
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.