专题：Solar Radiation and Photovoltaics

This cluster of papers focuses on the application of machine learning methods, particularly artificial neural networks, for forecasting solar radiation and photovoltaic power generation. It covers topics such as solar energy integration, grid-connected PV plant performance prediction, solar position algorithms, and GIS-based site selection for solar farms.
最新文献
Citizen CATE 2024: Extending Totality During the 8 April 2024 Total Solar Eclipse with a Distributed Network of Community Participants

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Feature selection and hyperparameter tuning in transformer-based deep learning models for photovoltaic power forecasting using the Swordfish Movement Optimization Algorithm (SMOA)

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ADNM-UNet: An Asymmetric Dual-Branch Noncausal Mamba U-Net With Multiscale Attention Enhancement for Cloud Mask Nowcasting

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Climate change will increase high-temperature risks, degradation, and costs of rooftop photovoltaics globally

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Machine learning and analytical hybridization models for evaluating climate change impacts on solar agrivoltaic systems and photosynthetically active radiation in Nigeria

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Novel hybrid BiLSTM-BiGRU and CNN-LSTM architectures for enhanced solar irradiance forecasting in semi-arid climates

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Multi-step short-term solar energy forecasting using Fourier-enhanced BiLSTM and neural additive models

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A Two-Stage Optimization Method for Real-Time Parameterization of PV-Farm Digital Twins

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Integrating LCZ framework and ENVI-met simulation for multi-scale assessment of urban thermal characteristics and blue-green infrastructure performance

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Redesigning the Decoder and Loss Function of Diffusion Transformer for PV Temporal Simulation

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近5年高被引文献
Kepler optimization algorithm: A new metaheuristic algorithm inspired by Kepler’s laws of planetary motion

article Full Text OpenAlex 521 FWCI91.7174

Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction

article Full Text OpenAlex 388 FWCI49.3489

Solar energy status in the world: A comprehensive review

review Full Text OpenAlex 382 FWCI67.3412

CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production

article Full Text OpenAlex 359 FWCI46.0682

COA-CNN-LSTM: Coati optimization algorithm-based hybrid deep learning model for PV/wind power forecasting in smart grid applications

article Full Text OpenAlex 334 FWCI44.2126

Hybrid VMD-CNN-GRU-based model for short-term forecasting of wind power considering spatio-temporal features

article Full Text OpenAlex 317 FWCI41.9623

Short term load forecasting based on ARIMA and ANN approaches

article Full Text OpenAlex 303 FWCI39.9988

Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model

article Full Text OpenAlex 300 FWCI52.9943

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System

article Full Text OpenAlex 293 FWCI13.6609

A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality

review Full Text OpenAlex 281 FWCI35.9778