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 …
History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining
Text mining is an emerging topic that advances the review of academic literature. This paper
presents a preliminary study on how to review solar irradiance and photovoltaic (PV) power …
presents a preliminary study on how to review solar irradiance and photovoltaic (PV) power …
HBO-LSTM: Optimized long short term memory with heap-based optimizer for wind power forecasting
The forecasting and estimation of wind power is a challenging problem in renewable energy
generation due to the high volatility of wind power resources, inevitable intermittency, and …
generation due to the high volatility of wind power resources, inevitable intermittency, and …
A combined forecasting model for time series: Application to short-term wind speed forecasting
Wind speed forecasting has been growing in popularity, owing to the increased demand for
wind power electricity generation and developments in wind energy competitiveness. Many …
wind power electricity generation and developments in wind energy competitiveness. Many …
A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets
In recent years, clean energies, such as wind power have been developed rapidly.
Especially, wind power generation becomes a significant source of energy in some power …
Especially, wind power generation becomes a significant source of energy in some power …
Verification of deterministic solar forecasts
The field of energy forecasting has attracted many researchers from different fields (eg,
meteorology, data sciences, mechanical or electrical engineering) over the last decade …
meteorology, data sciences, mechanical or electrical engineering) over the last decade …
Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization
This study proposes an effective combined model system for wind speed forecasting tasks.
In this model,(a) improved hybrid time series decomposition strategy (HTD) is developed to …
In this model,(a) improved hybrid time series decomposition strategy (HTD) is developed to …
A comprehensive review of hybrid models for solar radiation forecasting
Solar radiation components assessment is a highly required parameter for solar energy
applications. Due to the non-stationary behavior of solar radiation parameters and variety of …
applications. Due to the non-stationary behavior of solar radiation parameters and variety of …
Electric load forecasting by complete ensemble empirical mode decomposition adaptive noise and support vector regression with quantum-based dragonfly algorithm
Z Zhang, WC Hong - Nonlinear dynamics, 2019 - Springer
Accurate electric load forecasting can provide critical support to makers of energy policy and
managers of power systems. The support vector regression (SVR) model can be hybridized …
managers of power systems. The support vector regression (SVR) model can be hybridized …
A current perspective on the accuracy of incoming solar energy forecasting
The state-of-the-art in the accuracy of solar resources forecasting is obtained by using
results reported in 1705 accuracy tests reported in several geographic regions (North …
results reported in 1705 accuracy tests reported in several geographic regions (North …