Deep learning methods and applications for electrical power systems: A comprehensive review

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

Power quality disturbance detection and classification using signal processing and soft computing techniques: A comprehensive review

(2019) Manohar Mishra   International Transactions on Electrical Energy Systems

A deep spatial-temporal data-driven approach considering microclimates for power system security assessment

(2019) Tian-en Huang et al.   APPLIED ENERGY

Power Quality Disturbance Monitoring and Classification Based on Improved PCA and Convolution Neural Network for Wind-Grid Distribution Systems

(2019) Yue Shen et al.   Energies

Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources

(2019) Yaprakdal et al.   Energies

A Sequence-to-Sequence Deep Learning Architecture Based on Bidirectional GRU for Type Recognition and Time Location of Combined Power Quality Disturbance

(2019) Yaping Deng et al.   IEEE Transactions on Industrial Informatics

A review of deep learning for renewable energy forecasting

(2019) Huaizhi Wang et al.   ENERGY CONVERSION AND MANAGEMENT

A deep learning method for online capacity estimation of lithium-ion batteries

(2019) Sheng Shen et al.   Journal of Energy Storage

An Automatic Identification Framework for Complex Power Quality Disturbances Based on Multifusion Convolutional Neural Network

(2019) Wei Qiu et al.   IEEE Transactions on Industrial Informatics

Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks

(2018) Aowabin Rahman et al.   APPLIED ENERGY

Deep learning hybrid method for islanding detection in distributed generation

(2018) Xiangrui Kong et al.   APPLIED ENERGY

Complex power quality disturbances classification via curvelet transform and deep learning

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

Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †

(2018) Salah Bouktif et al.   Energies

A High Precision Artificial Neural Networks Model for Short-Term Energy Load Forecasting

(2018) Ping-Huan Kuo et al.   Energies

Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network

(2018) Hui Liu et al.   ENERGY CONVERSION AND MANAGEMENT

Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization

(2018) Jie Chen et al.   ENERGY CONVERSION AND MANAGEMENT

Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network

(2018) Hui Liu et al.   ENERGY CONVERSION AND MANAGEMENT

Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids

(2018) Zibin Zheng et al.   IEEE Transactions on Industrial Informatics

Rotor-Current-Based Fault Diagnosis for DFIG Wind Turbine Drivetrain Gearboxes Using Frequency Analysis and a Deep Classifier

(2018) Fangzhou Cheng et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

Short-Term Residential Load Forecasting Based on Resident Behaviour Learning

(2018) Weicong Kong et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning

(2018) Van Nhan Nguyen et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

A new ship energy management algorithm to the smart electricity grid system

(2018) Kenan Yiğit et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Advancing manufacturing systems research at NAMRC 46

(2018) Lihui Wang et al.   JOURNAL OF MANUFACTURING SYSTEMS

Data-Based Line Trip Fault Prediction in Power Systems Using LSTM Networks and SVM

(2018) Senlin Zhang et al.   IEEE Access

A cable fault recognition method based on a deep belief network

(2018) Xuebin qin et al.   COMPUTERS & ELECTRICAL ENGINEERING

Post-fault prediction of transient instabilities using stacked sparse autoencoder

(2018) Mohammed Mahdi et al.   ELECTRIC POWER SYSTEMS RESEARCH

Deep belief network based k-means cluster approach for short-term wind power forecasting

(2018) Kejun Wang et al.   ENERGY

A nonlinear hybrid wind speed forecasting model using LSTM network, hysteretic ELM and Differential Evolution algorithm

(2018) Ya-Lan Hu et al.   ENERGY CONVERSION AND MANAGEMENT

Deep learning adaptive dynamic programming for real time energy management and control strategy of micro-grid

(2018) Nan Wu et al.   JOURNAL OF CLEANER PRODUCTION

Deep Learning for fault detection in wind turbines

(2018) Georg Helbing et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Intelligent simultaneous fault diagnosis for solid oxide fuel cell system based on deep learning

(2018) Zehan Zhang et al.   APPLIED ENERGY

Multi-Step Short-Term Power Consumption Forecasting with a Hybrid Deep Learning Strategy

(2018) Ke Yan et al.   Energies

Online Recognition Method for Voltage Sags Based on a Deep Belief Network

(2018) Fei Mei et al.   Energies

Implementation of advanced functionalities for Distribution Management Systems: Load forecasting and modeling through Artificial Neural Networks ensembles

(2018) M. Saviozzi et al.   ELECTRIC POWER SYSTEMS RESEARCH

Assessment of deep recurrent neural network-based strategies for short-term building energy predictions

(2018) Cheng Fan et al.   APPLIED ENERGY

Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

(2018) Mengmeng Cai et al.   APPLIED ENERGY

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

(2018) Shouxiang Wang et al.   APPLIED ENERGY

Hybrid forecasting model based on long short term memory network and deep learning neural network for wind signal

(2018) Yong Qin et al.   APPLIED ENERGY

Probabilistic individual load forecasting using pinball loss guided LSTM

(2018) Yi Wang et al.   APPLIED ENERGY

Building Energy Consumption Prediction: An Extreme Deep Learning Approach

(2017) Chengdong Li et al.   Energies

Deterministic and probabilistic forecasting of photovoltaic power based on deep convolutional neural network

(2017) Huaizhi Wang et al.   ENERGY CONVERSION AND MANAGEMENT

When Weather Matters: IoT-Based Electrical Load Forecasting for Smart Grid

(2017) Liangzhi Li et al.   IEEE COMMUNICATIONS MAGAZINE

Dissolved gas analysis of insulating oil for power transformer fault diagnosis with deep belief network

(2017) Jiejie Dai et al.   IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION

Wind Turbine Gearbox Failure Identification With Deep Neural Networks

(2017) Long Wang et al.   IEEE Transactions on Industrial Informatics

Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting

(2017) Mahdi Khodayar et al.   IEEE Transactions on Industrial Informatics

Short-Term Electricity Price Forecasting With Stacked Denoising Autoencoders

(2017) Long Wang et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Hybrid Islanding Detection in Microgrid With Multiple Connection Points to Smart Grids Using Fuzzy-Neural Network

(2017) Saman Darvish Kermany et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

(2017) Waseem Rawat et al.   NEURAL COMPUTATION

Good Consumer or Bad Consumer: Economic Information Revealed from Demand Profiles

(2017) Yang Yu et al.   IEEE Transactions on Smart Grid

Real-Time Detection of False Data Injection Attacks in Smart Grid: A Deep Learning-Based Intelligent Mechanism

(2017) Youbiao He et al.   IEEE Transactions on Smart Grid

Deep Learning for Household Load Forecasting – A Novel Pooling Deep RNN

(2017) Heng Shi et al.   IEEE Transactions on Smart Grid

Short-term output power forecasting of photovoltaic systems based on the deep belief net

(2017) Ling-Ling Li et al.   Advances in Mechanical Engineering

Optimal operation of smart distribution networks: A review of models, methods and future research

(2016) Vasileios A. Evangelopoulos et al.   ELECTRIC POWER SYSTEMS RESEARCH

Coordinated control of distribution grid and electric vehicle loads

(2016) G.R. Bharati et al.   ELECTRIC POWER SYSTEMS RESEARCH

Maximizing performance of fuel cell using artificial neural network approach for smart grid applications

(2016) Y. Bicer et al.   ENERGY

Deep belief network based electricity load forecasting: An analysis of Macedonian case

(2016) Aleksandra Dedinec et al.   ENERGY

Unsupervised energy prediction in a Smart Grid context using reinforcement cross-building transfer learning

(2016) Elena Mocanu et al.   ENERGY AND BUILDINGS

Classification of Power Quality Disturbances via Deep Learning

(2016) Jian Ma et al.   IETE TECHNICAL REVIEW

A comprehensive stochastic energy management system in reconfigurable microgrids

(2016) Sajjad Golshannavaz et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Transfer learning for short-term wind speed prediction with deep neural networks

(2016) Qinghua Hu et al.   RENEWABLE ENERGY

Transformer fault diagnosis using continuous sparse autoencoder

(2016) Lukun Wang et al.   SpringerPlus

Robust Real-Time Load Profile Encoding and Classification Framework for Efficient Power Systems Operation

(2015) Ervin D. Varga et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

(2015) Muhammad Qamar Raza et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Predictive Deep Boltzmann Machine for Multiperiod Wind Speed Forecasting

(2015) Chun-Yang Zhang et al.   IEEE Transactions on Sustainable Energy

An Overview of Deep Generative Models

(2014) Jungang Xu et al.   IETE TECHNICAL REVIEW

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

(2012) Geoffrey Hinton et al.   IEEE SIGNAL PROCESSING MAGAZINE

Electricity demand load forecasting of the Hellenic power system using an ARMA model

(2009) S.Sp. Pappas et al.   ELECTRIC POWER SYSTEMS RESEARCH