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A review of very short-term wind and solar power forecasting
Installed capacities of wind and solar power have grown rapidly over recent years, and the
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
How solar radiation forecasting impacts the utilization of solar energy: A critical review
The demand for energy generation from solar energy resource has been exponentially
increasing in recent years. It is integral for a grid operator to maintain the balance between …
increasing in recent years. It is integral for a grid operator to maintain the balance between …
CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production
Climate change is pushing an increasing number of nations to use green energy resources,
particularly solar power as an applicable substitute to traditional power sources. However …
particularly solar power as an applicable substitute to traditional power sources. However …
A review of deep learning for renewable energy forecasting
As renewable energy becomes increasingly popular in the global electric energy grid,
improving the accuracy of renewable energy forecasting is critical to power system planning …
improving the accuracy of renewable energy forecasting is critical to power system planning …
Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM
More and more photovoltaic (PV) power generation is incorporated into the grid. However,
the intermittence and fluctuation of solar energy have brought huge challenges to the safe …
the intermittence and fluctuation of solar energy have brought huge challenges to the safe …
Dual stream network with attention mechanism for photovoltaic power forecasting
The operations of renewable power generation systems highly depend on precise
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
A hybrid deep learning model for short-term PV power forecasting
P Li, K Zhou, X Lu, S Yang - Applied Energy, 2020 - Elsevier
The integration of PV power brings great economic and environmental benefits. However,
the high penetration of PV power may challenge the planning and operation of the existing …
the high penetration of PV power may challenge the planning and operation of the existing …
[HTML][HTML] Trends and gaps in photovoltaic power forecasting with machine learning
The share of solar energy in the electricity mix increases year after year. Knowing the
production of photovoltaic (PV) power at each instant of time is crucial for its integration into …
production of photovoltaic (PV) power at each instant of time is crucial for its integration into …
Taxonomy research of artificial intelligence for deterministic solar power forecasting
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …
stochastic and volatile nature of solar power pose significant challenges to the reliable …
Solar photovoltaic generation forecasting methods: A review
Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …