Solar Radiation Prediction Based on Convolution Neural Network and Long Short-Term Memory
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Solar Radiation Prediction Based on Convolution Neural Network and Long Short-Term Memory
Authors
Keywords
-
Journal
Energies
Volume 14, Issue 24, Pages 8498
Publisher
MDPI AG
Online
2021-12-17
DOI
10.3390/en14248498
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery
- (2021) Francisco J. Rodríguez-Benítez et al. APPLIED ENERGY
- Enhancements in Day-Ahead Forecasts of Solar Irradiation with Machine Learning: A Novel Analysis with the Japanese Mesoscale Model
- (2020) Joao Gari da Silva Fonseca et al. Journal of Applied Meteorology and Climatology
- Optimal Kernel ELM and Variational Mode Decomposition for Probabilistic PV Power Prediction
- (2020) Xiaomei Wu et al. Energies
- Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network
- (2020) Anh Ngoc-Lan Huynh et al. Energies
- SolarNet: A sky image-based deep convolutional neural network for intra-hour solar forecasting
- (2020) Cong Feng et al. SOLAR ENERGY
- Potential analysis of roof-mounted solar photovoltaics in Sweden
- (2020) Ying Yang et al. APPLIED ENERGY
- Design of experiments using artificial neural network ensemble for photovoltaic generation forecasting
- (2020) M.O. Moreira et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cites of queensland Australia
- (2019) Sujan Ghimire et al. JOURNAL OF CLEANER PRODUCTION
- 3D-CNN-based feature extraction of ground-based cloud images for direct normal irradiance prediction
- (2019) Xin Zhao et al. SOLAR ENERGY
- Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Using Data Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea
- (2019) Jong-Min Yeom et al. SENSORS
- Development of an ANN based corrective algorithm of the operational ECMWF global horizontal irradiation forecasts
- (2019) Sara Pereira et al. SOLAR ENERGY
- Inter-hour direct normal irradiance forecast with multiple data types and time-series
- (2019) Tingting ZHU et al. Journal of Modern Power Systems and Clean Energy
- OpenSolar: Promoting the openness and accessibility of diverse public solar datasets
- (2019) Cong Feng et al. SOLAR ENERGY
- A Hybrid Prediction Model for Solar Radiation Based on Long Short-Term Memory, Empirical Mode Decomposition, and Solar Profiles for Energy Harvesting Wireless Sensor Networks
- (2019) Yujia Ge et al. Energies
- Predicting solar energy generation through artificial neural networks using weather forecasts for microgrid control
- (2018) Fermín Rodríguez et al. RENEWABLE ENERGY
- Solar irradiance forecast using aerosols measurements: A data driven approach
- (2018) Abdullah Alfadda et al. SOLAR ENERGY
- Comparison of methodologies for cloud cover estimation in Brazil - A case study
- (2018) Eduardo Weide Luiz et al. Energy for Sustainable Development
- Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset
- (2018) Ariana Moncada et al. Energies
- Automatic inspection machine for maize kernels based on deep convolutional neural networks
- (2018) Chao Ni et al. BIOSYSTEMS ENGINEERING
- Empirical investigation on modeling solar radiation series with ARMA–GARCH models
- (2015) Huaiwei Sun et al. ENERGY CONVERSION AND MANAGEMENT
- Real-time forecasting of solar irradiance ramps with smart image processing
- (2015) Yinghao Chu et al. SOLAR ENERGY
- Direct normal irradiance forecasting and its application to concentrated solar thermal output forecasting – A review
- (2014) Edward W. Law et al. SOLAR ENERGY
- Prediction of hourly solar radiation using a novel hybrid model of ARMA and TDNN
- (2011) Wu Ji et al. SOLAR ENERGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started