相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Boosting energy harvesting via deep learning-based renewable power generation prediction
Zulfiqar Ahmad Khan et al.
JOURNAL OF KING SAUD UNIVERSITY SCIENCE (2022)
CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production
Ali Agga et al.
ELECTRIC POWER SYSTEMS RESEARCH (2022)
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
Deniz Korkmaz
APPLIED ENERGY (2021)
A temporal distributed hybrid deep learning model for day-ahead distributed PV power forecasting
Yinpeng Qu et al.
APPLIED ENERGY (2021)
Multi-timescale Forecast of Solar Irradiance Based on Multi-task Learning and Echo State Network Approaches
Zhou Wu et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)
Ultra-short-term multi-step wind power forecasting based on CNN-LSTM
Qianyu Wu et al.
IET RENEWABLE POWER GENERATION (2021)
MPF-Net: A computational multi-regional solar power forecasting framework
Faiza Mehmood et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)
Short-term self consumption PV plant power production forecasts based on hybrid CNN-LSTM, ConvLSTM models
Ali Agga et al.
RENEWABLE ENERGY (2021)
Deep learning neural networks for short-term photovoltaic power forecasting
A. Mellit et al.
RENEWABLE ENERGY (2021)
Sequential Learning-Based Energy Consumption Prediction Model for Residential and Commercial Sectors
Ijaz Ul Haq et al.
MATHEMATICS (2021)
Non-intrusive load decomposition based on CNN-LSTM hybrid deep learning model
Xinxin Zhou et al.
ENERGY REPORTS (2021)
Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks
Xiongjie Jia et al.
ENERGY REPORTS (2021)
Multi-Meteorological-Factor-Based Graph Modeling for Photovoltaic Power Forecasting
Lilin Cheng et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2021)
A hybrid deep learning model for short-term PV power forecasting
Pengtao Li et al.
APPLIED ENERGY (2020)
A novel convolutional neural network framework based solar irradiance prediction method
Na Dong et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2020)
Towards Efficient Electricity Forecasting in Residential and Commercial Buildings: A Novel Hybrid CNN with a LSTM-AE based Framework
Zulfiqar Ahmad Khan et al.
SENSORS (2020)
Very-Short-Term Power Prediction for PV Power Plants Using a Simple and Effective RCC-LSTM Model Based on Short Term Multivariate Historical Datasets
Biaowei Chen et al.
ELECTRONICS (2020)
Prediction of photovoltaic power output based on similar day analysis, genetic algorithm and extreme learning machine
Yi Zhou et al.
ENERGY (2020)
Deep learning methods and applications for electrical power systems: A comprehensive review
Asiye K. Ozcanli et al.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2020)
A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea
KiJeon Nam et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)
Day-ahead photovoltaic power forecasting approach based on deep convolutional neural networks and meta learning
Haixiang Zang et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2020)
Electrical Energy Prediction in Residential Buildings for Short-Term Horizons Using Hybrid Deep Learning Strategy
Zulfiqar Ahmad Khan et al.
APPLIED SCIENCES-BASEL (2020)
A short-term load forecasting model of multi-scale CNN-LSTM hybrid neural network considering the real-time electricity price
Xifeng Guo et al.
ENERGY REPORTS (2020)
Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations
Haixiang Zang et al.
RENEWABLE ENERGY (2020)
Short-Term Solar Irradiance Forecasting Based on a Hybrid Deep Learning Methodology
Ke Yan et al.
INFORMATION (2020)
Accurate photovoltaic power forecasting models using deep LSTM-RNN
Mohamed Abdel-Nasser et al.
NEURAL COMPUTING & APPLICATIONS (2019)
A novel two-stage forecasting model based on error factor and ensemble method for multi-step wind power forecasting
Yan Hao et al.
APPLIED ENERGY (2019)
A hybrid forecasting system based on fuzzy time series and multi-objective optimization for wind speed forecasting
Ping Jiang et al.
APPLIED ENERGY (2019)
Electric Energy Consumption Prediction by Deep Learning with State Explainable Autoencoder
Jin-Young Kim et al.
ENERGIES (2019)
A novel system based on neural networks with linear combination framework for wind speed forecasting
Jianzhou Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting
Fei Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition
Mumtaz Ali et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
On post-processing day-ahead NWP forecasts using Kalman filtering
Dazhi Yang
SOLAR ENERGY (2019)
Predicting residential energy consumption using CNN-LSTM neural networks
Tae-Young Kim et al.
ENERGY (2019)
Renewable energy prediction: A novel short-term prediction model of photovoltaic output power
Ling-Ling Li et al.
JOURNAL OF CLEANER PRODUCTION (2019)
A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network
Kejun Wang et al.
APPLIED ENERGY (2019)
A review of deep learning for renewable energy forecasting
Huaizhi Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Photovoltaic power forecasting based LSTM-Convolutional Network
Kejun Wang et al.
ENERGY (2019)
A novel photovoltaic power forecasting model based on echo state network
Xianshuang Yao et al.
NEUROCOMPUTING (2019)
Repeated wavelet transform based ARIMA model for very short-term wind speed forecasting
Aasim et al.
RENEWABLE ENERGY (2019)
A Survey of Deep Learning Techniques: Application in Wind and Solar Energy Resources
Shahab Shamshirband et al.
IEEE ACCESS (2019)
The combined value of wind and solar power forecasting improvements and electricity storage
Bri-Mathias Hodge et al.
APPLIED ENERGY (2018)
Integrated hydrogen supply networks for waste biogas upgrading and hybrid carbon-hydrogen pinch analysis under hydrogen demand uncertainty
Soonho Hwangbo et al.
APPLIED THERMAL ENGINEERING (2018)
Using a novel multi-variable grey model to forecast the electricity consumption of Shandong Province in China
Lifeng Wu et al.
ENERGY (2018)
One-day-ahead probabilistic wind speed forecast based on optimized numerical weather prediction data
Xinyu Zhao et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
Adaptive echo state network control for a class of pure-feedback systems with input and output constraints
Qiang Chen et al.
NEUROCOMPUTING (2018)
1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data
Osama Abdeljaber et al.
NEUROCOMPUTING (2018)
Real-time forecasting of wave heights using EOF - wavelet - neural network hybrid model
Jihee Oh et al.
OCEAN ENGINEERING (2018)
A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data
Amir Sharifian et al.
RENEWABLE ENERGY (2018)
Short-Term Spatio-Temporal Forecasting of Photovoltaic Power Production
Xwegnon Ghislain Agoua et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2018)
Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors
Laura Frias-Paredes et al.
ENERGY CONVERSION AND MANAGEMENT (2017)
The path towards sustainable energy
Steven Chu et al.
NATURE MATERIALS (2017)
Deep reservoir computing: A critical experimental analysis
Claudio Gallicchio et al.
NEUROCOMPUTING (2017)
An overview of Afghanistan's trends toward renewable and sustainable energies
Raheleh Rostami et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2017)
Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review
Mohammad Azhar Mat Daut et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2017)
PSO-based analysis of Echo State Network parameters for time series forecasting
Naima Chouikhi et al.
APPLIED SOFT COMPUTING (2017)
Deep learning based ensemble approach for probabilistic wind power forecasting
Huai-zhi Wang et al.
APPLIED ENERGY (2017)
A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset
Ravinesh C. Deo et al.
APPLIED ENERGY (2016)
Forecasting the load of electrical power systems in mid- and long-term horizons: a review
Swasti R. Khuntia et al.
IET GENERATION TRANSMISSION & DISTRIBUTION (2016)
Functional echo state network for time series classification
Qianli Ma et al.
INFORMATION SCIENCES (2016)
Deep learning for estimating building energy consumption
Elena Mocanu et al.
SUSTAINABLE ENERGY GRIDS & NETWORKS (2016)
Recursive wind speed forecasting based on Hammerstein Auto-Regressive model
Othman Ait Maatallah et al.
APPLIED ENERGY (2015)
A hybrid wind speed forecasting model based on phase space reconstruction theory and Markov model: A case study of wind farms in northwest China
Yun Wang et al.
ENERGY (2015)
Extended-power pinch analysis (EPoPA) for integration of renewable energy systems with battery/hydrogen storages
Iman Janghorban Esfahani et al.
RENEWABLE ENERGY (2015)
Root mean square error (RMSE) or mean absolute error (MAE)? - Arguments against avoiding RMSE in the literature
T. Chai et al.
GEOSCIENTIFIC MODEL DEVELOPMENT (2014)
Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment
Sultan Al-Yahyai et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2010)
Anomaly detection
Varun Chandola et al.
ACM COMPUTING SURVEYS (2009)
Forecasting ocean wave energy: Tests of time-series models
Gordon Reikard
OCEAN ENGINEERING (2009)