As the penetration of solar energy generation into power systems keeps rising, intra-hour
solar forecasting (IHSF) is becoming increasingly important for the secure and economical …

Sky image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty of solar power generation. However, a major …

A forecasting method for hourly-averaged, day-ahead power output (PO) from photovoltaic
(PV) power plants based on least-squares optimization of Numerical Weather Prediction …

The volatility of cloud movement introduces significant uncertainty in short-term solar power
forecasting, which can complicate the operation of modern power systems. This work …

With the increase in demand for energy, penetration of alternative sources of energy in the
power grid has increased. Photovoltaic (PV) energy is the most common and popular form of …

Forecasting solar energy generation is a challenging task because of the variety of solar
power systems and weather regimes encountered. Inaccurate forecasts can result in …

This brief proposes a new convex model predictive control (MPC) strategy for dynamic
optimal power flow between battery energy storage (ES) systems distributed in an ac …

Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic
and concentrating solar thermal power plants. Accurate solar nowcasting becomes …

Short term electricity trading to balance generation and demand provides an economic
opportunity to integrate larger shares of variable renewable energy sources in the power …

A novel intelligent hybrid model is proposed in this paper for accurate prediction and
modeling of solar power plants using the wavelet transform package (WTP) and generative …