Machine Learning Techniques Applied to On-Line Voltage Stability Assessment: A Review
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Machine Learning Techniques Applied to On-Line Voltage Stability Assessment: A Review
Authors
Keywords
-
Journal
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-10-05
DOI
10.1007/s11831-019-09368-2
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- PMU-based voltage stability prediction using least square support vector machine with online learning
- (2018) Hao Yang et al. ELECTRIC POWER SYSTEMS RESEARCH
- Voltage stability assessment using multi-objective biogeography-based subset selection
- (2018) Hanieh Mohammadi et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- The Amalgamation of SVR and ANFIS Models with Synchronized Phasor Measurements for On-Line Voltage Stability Assessment
- (2017) Mohammed Amroune et al. Energies
- Voltage stability monitoring of power systems using reduced network and artificial neural network
- (2017) Syed Mohammad Ashraf et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Load frequency control in deregulated power system integrated with SMES–TCPS combination using ANFIS controller
- (2016) Abhijith Pappachen et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- A comprehensive review of the voltage stability indices
- (2016) Javad Modarresi et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- PMU based voltage security assessment of power systems exploiting principal component analysis and decision trees
- (2015) Hanieh Mohammadi et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Genetic algorithm based support vector machine for on-line voltage stability monitoring
- (2015) K.S. Sajan et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Bioprocess considerations for microalgal-based wastewater treatment and biomass production
- (2015) Xianhai Zeng et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Distributed continuation power flow method for integrated transmission and active distribution network
- (2015) Jinquan ZHAO et al. Journal of Modern Power Systems and Clean Energy
- Support Vector Regression Model for the prediction of Loadability Margin of a Power System
- (2014) M.V. Suganyadevi et al. APPLIED SOFT COMPUTING
- Power system voltage stability monitoring using artificial neural networks with a reduced set of inputs
- (2014) A.R. Bahmanyar et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Online Voltage Security Assessment Based on Wide-Area Measurements
- (2013) M. Beiraghi et al. IEEE TRANSACTIONS ON POWER DELIVERY
- Wavelet based feature extraction of voltage profile for online voltage stability assessment using RBF neural network
- (2013) Sina Hashemi et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Voltage stability assessment in power network using self organizing feature map and radial basis function
- (2012) Kabir Chakraborty et al. COMPUTERS & ELECTRICAL ENGINEERING
- Progressive entropy based contingency grouping for deriving decision trees for multiple contingencies
- (2012) Venkat Krishnan et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- ANN based online voltage estimation
- (2011) P. Aravindhababu et al. APPLIED SOFT COMPUTING
- Using PV and QV curves with the meaning of static contingency screening and planning
- (2011) A.C. Zambroni de Souza et al. ELECTRIC POWER SYSTEMS RESEARCH
- Fuzzy multi-objective reactive power clearing considering reactive compensation sources
- (2011) A.H. Khazali et al. ENERGY
- On-line voltage stability assessment using radial basis function network model with reduced input features
- (2011) D. Devaraj et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Online Monitoring of Voltage Stability Margin Using an Artificial Neural Network
- (2010) Debbie Q Zhou et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Decision Tree-Based Online Voltage Security Assessment Using PMU Measurements
- (2009) Ruisheng Diao et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Contingency evaluation and monitorization using artificial neural networks
- (2009) G. Joya et al. NEURAL COMPUTING & APPLICATIONS
- Online fuzzy voltage collapse risk quantification
- (2008) A. Berizzi et al. ELECTRIC POWER SYSTEMS RESEARCH
- Generation rescheduling using ANN-based computation of parameter sensitivities of the voltage stability margin
- (2008) S. Chakrabarti et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- A method for computing minimum voltage stability margins of power systems
- (2008) D.B. Bedoya et al. IET Generation Transmission & Distribution
- Adaptive-neuro-fuzzy inference system approach for transmission line fault classification and location incorporating effects of power swings
- (2008) M.J. Reddy et al. IET Generation Transmission & Distribution
- Fuzzy neural network based voltage stability evaluation of power systems with SVC
- (2007) P.K. Modi et al. APPLIED SOFT COMPUTING
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now