State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
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 …
[HTML][HTML] Solar power forecasting using CNN-LSTM hybrid model
Photovoltaic (PV) technology converts solar energy into electrical energy, and the PV
industry is an essential renewable energy industry. However, the amount of power …
industry is an essential renewable energy industry. However, the amount of power …
How solar radiation forecasting impacts the utilization of solar energy: A critical review
The demand for energy generation from solar energy resource has been exponentially
increasing in recent years. It is integral for a grid operator to maintain the balance between …
increasing in recent years. It is integral for a grid operator to maintain the balance between …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
A review on global solar radiation prediction with machine learning models in a comprehensive perspective
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 …
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 …
Multi-scale solar radiation and photovoltaic power forecasting with machine learning algorithms in urban environment: A state-of-the-art review
Solar energy has been rapidly utilized in urban environments owing to its significant
potential to fulfill the energy demand. The precise forecasting of solar energy, including solar …
potential to fulfill the energy demand. The precise forecasting of solar energy, including solar …
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 …