Review on photovoltaic power and solar resource forecasting: current status and trends

TC Carneiro, PCM de Carvalho… - Journal of Solar …, 2022 - asmedigitalcollection.asme.org
Photovoltaic (PV) power intermittence impacts electrical grid security and operation. Precise
PV power and solar irradiation forecasts have been investigated as significant reducers of …

A point prediction method based automatic machine learning for day-ahead power output of multi-region photovoltaic plants

W Zhao, H Zhang, J Zheng, Y Dai, L Huang, W Shang… - Energy, 2021 - Elsevier
Solar power generation (SPG) is essentially dependent on spatial and meteorological
characteristics which makes the planning and operation of power systems difficult. To …

A double decomposition-based modelling approach to forecast weekly solar radiation

R Prasad, M Ali, Y Xiang, H Khan - Renewable Energy, 2020 - Elsevier
To meet the future energy demand and avert any looming crises, efforts are being carried
out to utilize sustainable and renewable energy resources. In this paper, the naturally …

Statistical learning for NWP post-processing: A benchmark for solar irradiance forecasting

H Verbois, YM Saint-Drenan, A Thiery, P Blanc - Solar Energy, 2022 - Elsevier
The share of solar power in the global and local energy mixes has increased dramatically in
the past decade. Consequently, there has been a significant rise in the interest for solar …

A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used

CM Travieso-González, F Cabrera-Quintero… - Applied Sciences, 2024 - mdpi.com
The increasing penetration of solar energy into the grid has led to management difficulties
that require high accuracy forecasting systems. New techniques and approaches are …

[HTML][HTML] Hybrid solar irradiance nowcasting and forecasting with the SCOPE method and convolutional neural networks

Z Liao, CFM Coimbra - Renewable Energy, 2024 - Elsevier
We use a full year (2018) of GOES-R satellite data to produce 5-minute resolved information
on cloud coverage for 7 Surface Radiation Budget Network (SURFRAD). The remote …

Short-term solar radiation forecasting using a new seasonal clustering technique and artificial neural network

H Ali-Ou-Salah, B Oukarfi… - International Journal of …, 2022 - Taylor & Francis
Solar radiation represents the most important parameter for sizing and planning solar power
systems. However, solar radiation depends significantly on meteorological conditions which …

Extremely randomized tree: a new machines learning method for predicting coagulant dosage in drinking water treatment plant

S Heddam - Water engineering modeling and mathematic tools, 2021 - Elsevier
Coagulation using metal salts such as aluminum sulfate and ferric sulfate is the most well-
known method used during the coagulation–flocculation process and mainly adopted in the …

A deep-learning algorithm with two-stage training for solar forecast post-processing

H Quan, Y Ge, B Liu, W Zhang, D Srinivasan - Solar Energy, 2024 - Elsevier
Post-processing is a common strategy to boost the quality of irradiance forecasts from
numerical weather prediction (NWP). This work approaches this problem from a machine …

Sky-Image-Based Sun-Blocking Index and PredRNN++ for Accurate Short-Term Solar Irradiance Forecasting

RA Rajagukguk, H Lee - Building and Environment, 2024 - Elsevier
Accurate solar irradiance forecasting is crucial for optimizing solar energy utilization and
significantly improves the reliability and efficiency of related systems and technologies. This …