[HTML][HTML] Advances in solar forecasting: Computer vision with deep learning
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 …
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
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 …
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) …
their environmental appeal. With the presence of these renewable energy sources (RESs) …
Estimation of regulation reserve requirements in California ISO: a data-driven method
This paper proposes a data-driven method to estimate real-time regulation reserve
requirements in the California Independent System Operator (CAISO) balancing authority …
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 …
behavior which can be addressed by accurate forecasts. This paper opts to identify time …