Spatio-temporal graph neural networks for multi-site PV power forecasting

J Simeunović, B Schubnel, PJ Alet… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Accurate forecasting of solar power generation with fine temporal and spatial resolution is
vital for the operation of the power grid. However, state-of-the-art approaches that combine …

Applications for solar irradiance nowcasting in the control of microgrids: A review

R Samu, M Calais, GM Shafiullah, M Moghbel… - … and Sustainable Energy …, 2021 - Elsevier
The integration of solar photovoltaic (PV) into electricity networks introduces technical
challenges due to varying PV output. Rapid ramp events due to cloud movements are of …

Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

S Theocharides, G Makrides, A Livera, M Theristis… - Applied Energy, 2020 - Elsevier
A main challenge towards ensuring large-scale and seamless integration of photovoltaic
systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high …

Irradiance variability quantification and small-scale averaging in space and time: A short review

GM Lohmann - Atmosphere, 2018 - mdpi.com
The ongoing world-wide increase of installed photovoltaic (PV) power attracts notice to
weather-induced PV power output variability. Understanding the underlying spatiotemporal …

Hybrid approaches based on deep whole-sky-image learning to photovoltaic generation forecasting

W Kong, Y Jia, ZY Dong, K Meng, S Chai - Applied Energy, 2020 - Elsevier
With the ever-increased penetration of solar energy in the power grid, solar photovoltaic
forecasting has become an indispensable aspect in maintaining power system stability and …

Machine Learning techniques for solar irradiation nowcasting: Cloud type classification forecast through satellite data and imagery

A Nespoli, A Niccolai, E Ogliari, G Perego, E Collino… - Applied Energy, 2022 - Elsevier
One of the most important modern challenges in making the renewable energy sources
more reliable is the development of new tools to better manage their non programmable …

Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery

FJ Rodríguez-Benítez, M López-Cuesta… - Applied Energy, 2021 - Elsevier
This work proposes and evaluates methods for extending the forecasting horizon of all-sky
imager (ASI)-based solar radiation nowcasts and estimating the uncertainty of these …

Forecasting solar irradiance at short horizons: Frequency and time domain models

G Reikard, C Hansen - Renewable energy, 2019 - Elsevier
A key issue in integrating solar power into the grid is short-term forecasting. Up to now, most
solar forecasting has been run in the time domain. But since the data are dominated by the …

An energy flow simulation tool for incorporating short-term PV forecasting in a diesel-PV-battery off-grid power supply system

T Jamal, C Carter, T Schmidt, GM Shafiullah, M Calais… - Applied Energy, 2019 - Elsevier
One of the primary technical challenges of integrating high levels of PV generation into
standalone off-grid power supply systems is their variable power output characteristics. In …

Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques

M López-Cuesta, R Aler-Mur, IM Galván-León… - Remote Sensing, 2023 - mdpi.com
Accurate solar radiation nowcasting models are critical for the integration of the increasing
solar energy in power systems. This work explored the benefits obtained by the blending of …