[HTML][HTML] Advances in solar forecasting: Computer vision with deep learning

Q Paletta, G Terrén-Serrano, Y Nie, B Li… - Advances in Applied …, 2023 - Elsevier
Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …

Quantifying the value of probabilistic forecasting for power system operation planning

Q Wang, A Tuohy, M Ortega-Vazquez, M Bello, E Ela… - Applied Energy, 2023 - Elsevier
A recent key research area in renewable energy integration is the development of tools and
methods to capture and accommodate the uncertainty associated with the forecast errors …

Power system flexibility analysis using net-load forecasting based on deep learning considering distributed energy sources and electric vehicles

ET Rizi, M Rastegar, A Forootani - Computers and Electrical Engineering, 2024 - Elsevier
Today, wind and solar energy sources have opened their place in the power system due to
their environmental appeal. With the presence of these renewable energy sources (RESs) …

Estimation of regulation reserve requirements in California ISO: a data-driven method

L He, J Zhang, B Hobbs - 2023 IEEE Power & Energy Society …, 2023 - ieeexplore.ieee.org
This paper proposes a data-driven method to estimate real-time regulation reserve
requirements in the California Independent System Operator (CAISO) balancing authority …

Comparative studies on different time series models for wind power generation forecasting

AL De Ocampo, A Alon, GF Apolinario… - … IEEE Conference on …, 2023 - ieeexplore.ieee.org
Integration of wind to existing energy sources requires understanding of its intermittent
behavior which can be addressed by accurate forecasts. This paper opts to identify time …