Deep learning for power quality

Multiple power quality disturbances analysis in photovoltaic integrated direct current microgrid using adaptive morphological filter with deep learning algorithm

(2022) P.K. Dash et al.   APPLIED ENERGY

A new deep learning method for the classification of power quality disturbances in hybrid power system

(2022) Belkis Eristi et al.   ELECTRICAL ENGINEERING

An End-to-End Deep Learning Method for Voltage Sag Classification

(2022) Radovan Turović et al.   Energies

A Novel Microgrid Islanding Detection Algorithm Based on a Multi-Feature Improved LSTM

(2022) Yan Xia et al.   Energies

A Deep Learning Method Based on Bidirectional WaveNet for Voltage Sag State Estimation via Limited Monitors in Power System

(2022) Yaping Deng et al.   Energies

Voltage Sags Characterization Using Fault Analysis and Deep Convolutional Neural Networks

(2022) Sergio Turizo et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

An Improved Power Quality Disturbance Detection Using Deep Learning Approach

(2022) Kavaskar Sekar et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Deep learning-based multi-model ensemble method for classification of PQDs in a hydrogen energy-based microgrid using modified weighted majority algorithm

(2022) Gökay Bayrak et al.   INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

Deep Learning Based a New Approach for Power Quality Disturbances Classification in Power Transmission System

(2022) Ismail Topaloglu   Journal of Electrical Engineering & Technology

Power quality 24-hour prediction using differential, deep and statistics machine learning based on weather data in an off-grid

(2022) Ladislav Zjavka   JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

An efficient DLN2-CRSO approach based dynamic stability enhancement in micro-grid system

(2022) V. Anantha Krishnan et al.   APPLIED ENERGY

Optimal deep learning based aggregation of TCLs in an inverter fed stand-alone microgrid for voltage unbalance mitigation

(2022) Souvik Bera et al.   ELECTRIC POWER SYSTEMS RESEARCH

A novel semi-supervised method for classification of power quality disturbance using generative adversarial network

(2021) Xianzhong Jian et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications

(2021) Wojciech Samek et al.   PROCEEDINGS OF THE IEEE

Unsupervised deep learning and analysis of harmonic variation patterns using big data from multiple locations

(2021) Chenjie Ge et al.   ELECTRIC POWER SYSTEMS RESEARCH

A Novel Deep Learning-Based Diagnosis Method Applied to Power Quality Disturbances

(2021) Artvin-Darien Gonzalez-Abreu et al.   Energies

Open source dataset generator for power quality disturbances with deep-learning reference classifiers

(2021) R. Machlev et al.   ELECTRIC POWER SYSTEMS RESEARCH

Variations in harmonic voltage at the sub-10-minute time scale

(2021) Aurora Gil-de-Castro et al.   ELECTRIC POWER SYSTEMS RESEARCH

An adaptive deep learning framework to classify unknown composite power quality event using known single power quality events

(2021) Hatem Sindi et al.   EXPERT SYSTEMS WITH APPLICATIONS

A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification

(2021) Hatem Sindi et al.   EXPERT SYSTEMS WITH APPLICATIONS

A novel Multi-LSTM based deep learning method for islanding detection in the microgrid

(2021) Asiye Kaymaz Özcanlı et al.   ELECTRIC POWER SYSTEMS RESEARCH

The Turbulent Past and Uncertain Future of AI: Is there a way out of AI's boom-and-bust cycle?

(2021) Eliza Strickland   IEEE SPECTRUM

Statistical Models of EAF Harmonics Developed for Harmonic Estimation Directly From Waveform Samples Using Deep Learning Framework

(2021) Nagihan Severoglu et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

Review of AI applications in harmonic analysis in power systems

(2021) Ahmadreza Eslami et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Deep Learning Method With Manual Post-Processing for Identification of Spectral Patterns of Waveform Distortion in PV Installations

(2021) Roger Alves de Oliveira et al.   IEEE Transactions on Smart Grid

CNN / Bi‐LSTM‐based deep learning algorithm for classification of power quality disturbances by using spectrogram images

(2021) İlyas Özer et al.   International Transactions on Electrical Energy Systems

A Novel Label-Guided Attention Method for Multilabel Classification of Multiple Power Quality Disturbances

(2021) Dexi Gu et al.   IEEE Transactions on Industrial Informatics

Real‐time recognition of power quality disturbance‐based deep belief network using embedded parallel computing platform

(2020) Ziming Chen et al.   IEEJ Transactions on Electrical and Electronic Engineering

Dropout vs. batch normalization: an empirical study of their impact to deep learning

(2020) Christian Garbin et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Hybrid fractional fuzzy PID design for MPPT-pitch control of wind turbine-based bat algorithm

(2020) Oussama Maroufi et al.   ELECTRICAL ENGINEERING

Deep-Learning-Based Harmonics and Interharmonics Predetection Designed for Compensating Significantly Time-Varying EAF Currents

(2020) Ebrahim Balouji et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications

(2020) Thanh Thi Nguyen et al.   IEEE Transactions on Cybernetics

Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications

(2020) Andreas Venzke et al.   IEEE Transactions on Smart Grid

A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems

(2019) Lefeng Cheng et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Classification of multiple power quality events via compressed deep learning

(2019) Hui Liu et al.   International Transactions on Electrical Energy Systems

Investigating the impact of data normalization on classification performance

(2019) Dalwinder Singh et al.   APPLIED SOFT COMPUTING

The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting

(2019) E. Camporeale   SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS

Classifying Power Quality Disturbances Based on Phase Space Reconstruction and a Convolutional Neural Network

(2019) Kewei Cai et al.   Applied Sciences-Basel

Signal Processing and Deep Learning Techniques for Power Quality Events Monitoring and Classification

(2019) Hui Liu et al.   ELECTRIC POWER COMPONENTS AND SYSTEMS

An Optimal Wavelet Packets Basis Method for Cascade Hydro-PV-Pumped Storage Generation Systems to Smooth Photovoltaic Power Fluctuations

(2019) Fan Wu et al.   Energies

Optimal designing of static var compensator to improve voltage profile of power system using fuzzy logic control

(2019) Amirreza Naderipour et al.   ENERGY

Convolutional Autoencoder Based Feature Extraction and Clustering for Customer Load Analysis

(2019) Seunghyoung Ryu et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Recognition method of voltage sag causes based on Bi‐LSTM

(2019) Zhicong Zheng et al.   IEEJ Transactions on Electrical and Electronic Engineering

Complex power quality disturbances classification via curvelet transform and deep learning

(2018) Hui Liu et al.   ELECTRIC POWER SYSTEMS RESEARCH

Visual Analytics for Explainable Deep Learning

(2018) Jaegul Choo et al.   IEEE COMPUTER GRAPHICS AND APPLICATIONS

A Robust Transform-Domain Deep Convolutional Network for Voltage Dip Classification

(2018) Azam Bagheri et al.   IEEE TRANSACTIONS ON POWER DELIVERY

A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network

(2018) Shouxiang Wang et al.   APPLIED ENERGY

Methods for Harmonic Analysis and Reporting in Future Grid Applications

(2017) S. Elphick et al.   IEEE TRANSACTIONS ON POWER DELIVERY

Machine Learning With Big Data: Challenges and Approaches

(2017) Alexandra L'Heureux et al.   IEEE Access

Machine Learning

(2016) Panos Louridas et al.   IEEE SOFTWARE

Deep learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances

(2015) Suhail Khokhar et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Automatic recognition system of underlying causes of power quality disturbances based on S-Transform and Extreme Learning Machine

(2014) Hüseyin Erişti et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Toward Scalable Systems for Big Data Analytics: A Technology Tutorial

(2014) Han Hu et al.   IEEE Access

Detection and Classification of Single and Combined Power Quality Disturbances Using Neural Networks

(2013) Martin Valtierra-Rodriguez et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Wavelet-based feature extraction and selection for classification of power system disturbances using support vector machines

(2010) Hüseyin Erişti et al.   ELECTRIC POWER SYSTEMS RESEARCH

Direct Measurement of Power Quality Over Railway Networks With Results of a 16.7-Hz Network

(2010) Andrea Mariscotti   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Bridging the gap between signal and power

(2009) Math Bollen et al.   IEEE SIGNAL PROCESSING MAGAZINE

The Use of Genetic Algorithms for the Design of Resonant Compensators for Active Filters

(2009) W. Lenwari et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Analyzing Harmonic Monitoring Data Using Supervised and Unsupervised Learning

(2009) Ali Asheibi et al.   IEEE TRANSACTIONS ON POWER DELIVERY

Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network

(2008) S. Mishra et al.   IEEE TRANSACTIONS ON POWER DELIVERY