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
Optimizing solar and wind forecasting with iHow optimization algorithm and multi-scale attention networks

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Explainable and physics-constrained PV power prediction via a hybrid framework Integrating secondary decomposition and improved Transformer-LSTM

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Citizen CATE 2024: Extending Totality During the 8 April 2024 Total Solar Eclipse with a Distributed Network of Community Participants

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A hybrid transformer–TCN–GRU based model for thermal load forecasting of a large university campus

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Short-Term photovoltaic power forecasting based on K-means++ clustering, secondary decomposition and TCN-BiLSTM-Attention model

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Large-scale resource assessments for solar photovoltaics: A review of potential definitions, methodologies and future research needs

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Mapping Europe’s rooftop photovoltaic potential with a building-level database

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A hybrid TCN-LSTM-attention framework for multi-scenario short-term photovoltaic power forecasting incorporating physics-informed neural network strategy

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A comprehensive review of deep learning for solar nowcasting: Enhancing accuracy, reliability, and interpretability

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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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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 539 FWCI90.4768

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

article Full Text OpenAlex 409 FWCI50.391

Solar energy status in the world: A comprehensive review

review Full Text OpenAlex 408 FWCI68.5952

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

article Full Text OpenAlex 374 FWCI46.3825

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

article Full Text OpenAlex 353 FWCI44.6345

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

article Full Text OpenAlex 337 FWCI42.7436

Short term load forecasting based on ARIMA and ANN approaches

article Full Text OpenAlex 316 FWCI40.0084

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

article Full Text OpenAlex 314 FWCI52.6561

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

article Full Text OpenAlex 299 FWCI13.7318

Machine Learning in Weather Prediction and Climate Analyses—Applications and Perspectives

article Full Text OpenAlex 292 FWCI24.937