Deep learning models for solar irradiance forecasting: A comprehensive review
P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
Convergence of photovoltaic power forecasting and deep learning: State-of-art review
Deep learning (DL)-based PV Power Forecasting (PVPF) emerged nowadays as a
promising research direction to intelligentize energy systems. With the massive smart meter …
promising research direction to intelligentize energy systems. With the massive smart meter …
Interpretable wind speed prediction with multivariate time series and temporal fusion transformers
Wind power has been utilized well in power systems, so steady and successful wind speed
forecasting is crucial to security management power grid market economy. To date, most …
forecasting is crucial to security management power grid market economy. To date, most …
Developing a wind power forecasting system based on deep learning with attention mechanism
C Tian, T Niu, W Wei - Energy, 2022 - Elsevier
Large-scale wind power grid integration is challenging, requiring accurate and stable wind
power forecasting to reduce operational risk and improve the scheduling efficiency of the …
power forecasting to reduce operational risk and improve the scheduling efficiency of the …
Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN …
Optimal utilisation of the sun's freely available energy to generate electricity requires efficient
predictive models of global solar radiation (GSR). These are necessary to provide solar …
predictive models of global solar radiation (GSR). These are necessary to provide solar …
Dense skip attention based deep learning for day-ahead electricity price forecasting
The forecasting of the day-ahead electricity price (DAEP) has become more of interest to
decision makers in the liberalized market, as it can help optimize bidding strategies and …
decision makers in the liberalized market, as it can help optimize bidding strategies and …
Ultra-short-term spatiotemporal forecasting of renewable resources: An attention temporal convolutional network-based approach
J Liang, W Tang - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
The rapid increase in the penetration of renewable energy resources characterized by high
variability and uncertainty is bringing new challenges to the power system operation. To …
variability and uncertainty is bringing new challenges to the power system operation. To …
Evaluating the most significant input parameters for forecasting global solar radiation of different sequences based on Informer
C Jiang, Q Zhu - Applied Energy, 2023 - Elsevier
The number of existing global solar radiation (GSR) observation stations is limited, and it is
challenging to meet the demand for scientific research and production. Different forecasting …
challenging to meet the demand for scientific research and production. Different forecasting …
Application of deep learning to the prediction of solar irradiance through missing data
R Girimurugan, P Selvaraju… - International Journal …, 2023 - Wiley Online Library
The task of predicting solar irradiance is critical in the development of renewable energy
sources. This research is aimed at predicting the photovoltaic plant's irradiance or power …
sources. This research is aimed at predicting the photovoltaic plant's irradiance or power …
Ensemble learning based multi-modal intra-hour irradiance forecasting
S Shan, C Li, Z Ding, Y Wang, K Zhang… - Energy Conversion and …, 2022 - Elsevier
Accurate intra-hour irradiance forecasting plays an important role in improving the
effectiveness of photovoltaic power management. More and more sensors, for example, total …
effectiveness of photovoltaic power management. More and more sensors, for example, total …