[HTML][HTML] Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction
D Markovics, MJ Mayer - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The increase of the worldwide installed photovoltaic (PV) capacity and the intermittent
nature of the solar resource highlights the importance of power forecasting for the grid …
nature of the solar resource highlights the importance of power forecasting for the grid …
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
The energy industry is at a crossroads. Digital technological developments have the
potential to change our energy supply, trade, and consumption dramatically. The new …
potential to change our energy supply, trade, and consumption dramatically. The new …
Deep learning models for solar irradiance forecasting: A comprehensive review
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
Prediction of solar energy guided by pearson correlation using machine learning
Solar energy forecasting represents a key element in increasing the competitiveness of solar
power plants in the energy market and reducing the dependence on fossil fuels in economic …
power plants in the energy market and reducing the dependence on fossil fuels in economic …
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations
Accurate short-term solar irradiance forecasting is crucial for ensuring the optimum
utilization of photovoltaic power generation sources. This study addresses this issue by …
utilization of photovoltaic power generation sources. This study addresses this issue by …
A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network
K Wang, X Qi, H Liu - Applied Energy, 2019 - Elsevier
Accurate photovoltaic power forecasting is of great help to the operation of photovoltaic
power generation system. However, due to the instability, intermittence, and randomness of …
power generation system. However, due to the instability, intermittence, and randomness of …
Photovoltaic power forecasting based LSTM-Convolutional Network
K Wang, X Qi, H Liu - Energy, 2019 - Elsevier
The volatile and intermittent nature of solar energy itself presents a significant challenge in
integrating it into existing energy systems. Accurate photovoltaic power prediction plays an …
integrating it into existing energy systems. Accurate photovoltaic power prediction plays an …
A review on global solar radiation prediction with machine learning models in a comprehensive perspective
Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …
for economic and environmental considerations. However, because solar-radiation …
Taxonomy research of artificial intelligence for deterministic solar power forecasting
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …
stochastic and volatile nature of solar power pose significant challenges to the reliable …