[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 …
Automated deep CNN-LSTM architecture design for solar irradiance forecasting
Accurate prediction of solar energy is an important issue for photovoltaic power plants to
enable early participation in energy auction industries and cost-effective resource planning …
enable early participation in energy auction industries and cost-effective resource planning …
Digital twins: A brief overview of applications, challenges and enabling technologies in the last decade
OT Eleftheriou, CN Anagnostopoulos - Digital Twin, 2022 - digitaltwin1.org
The concept of Digitals Twins (DTs) is an evolving idea, which is becoming the center of
attention for the industry and the scientific community. It can be described as the pairing of …
attention for the industry and the scientific community. It can be described as the pairing of …
Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks
Integrating photovoltaics (PV) into electricity grids is challenged by potentially large
fluctuations in power generation. In recent years, sky image-based PV output prediction …
fluctuations in power generation. In recent years, sky image-based PV output prediction …
SKIPP'D: A SKy Images and Photovoltaic Power Generation Dataset for short-term solar forecasting
Large-scale integration of photovoltaics (PV) into electricity grids is challenged by the
intermittent nature of solar power. Sky-image-based solar forecasting using deep learning …
intermittent nature of solar power. Sky-image-based solar forecasting using deep learning …
[HTML][HTML] A network of sky imagers for spatial solar irradiance assessment
A network of seven low-cost hemispheric sky-imaging cameras has been installed in the Los
Angeles basin. This network of cameras provides wide sky coverage to perform spatial solar …
Angeles basin. This network of cameras provides wide sky coverage to perform spatial solar …
PV power output prediction from sky images using convolutional neural network: The comparison of sky-condition-specific sub-models and an end-to-end model
Photovoltaics (PV), the primary use of solar energy, is growing rapidly. However, the
variable output of PV under changing weather conditions may hinder the large-scale …
variable output of PV under changing weather conditions may hinder the large-scale …
Quantitative analysis of the quality constituents of Lonicera japonica Thunberg based on Raman spectroscopy
Q Zeng, Z Cheng, L Li, Y Yang, Y Peng, X Zhou… - Food Chemistry, 2024 - Elsevier
Quantitative analysis of the quality constituents of Lonicera japonica (**yinhua [JYH]) using
a feasible method provides important information on its evaluation and applications …
a feasible method provides important information on its evaluation and applications …
[HTML][HTML] A novel sky image-based solar irradiance nowcasting model with convolutional block attention mechanism
Global horizontal irradiance (GHI) is a crucial factor impacting photovoltaic (PV) production,
and is required for accurate real-time photovoltaic power forecasting. And it is a new …
and is required for accurate real-time photovoltaic power forecasting. And it is a new …
Deep learning-based image regression for short-term solar irradiance forecasting on the edge
EA Papatheofanous, V Kalekis, G Venitourakis… - Electronics, 2022 - mdpi.com
Photovoltaic (PV) power production is characterized by high variability due to short-term
meteorological effects such as cloud movements. These effects have a significant impact on …
meteorological effects such as cloud movements. These effects have a significant impact on …