Deep learning models for solar irradiance forecasting: A comprehensive review
P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
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 …
Machine learning methods for solar radiation forecasting: A review
Forecasting the output power of solar systems is required for the good operation of the
power grid or for the optimal management of the energy fluxes occurring into the solar …
power grid or for the optimal management of the energy fluxes occurring into the solar …
How solar radiation forecasting impacts the utilization of solar energy: A critical review
N Krishnan, KR Kumar, CS Inda - Journal of Cleaner Production, 2023 - Elsevier
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 …
Solar radiation forecasting using artificial neural network and random forest methods: Application to normal beam, horizontal diffuse and global components
Three methods, smart persistence, artificial neural network and random forest, are compared
to forecast the three components of solar irradiation (global horizontal, beam normal and …
to forecast the three components of solar irradiation (global horizontal, beam normal and …
Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting
Solar and wind energy are inherently time-varying sources of energy on scales from minutes
to seasons. Thus, the incorporation of such intermittent and stochastic renewable energy …
to seasons. Thus, the incorporation of such intermittent and stochastic renewable energy …
Multi-scale solar radiation and photovoltaic power forecasting with machine learning algorithms in urban environment: A state-of-the-art review
J Tian, R Ooka, D Lee - Journal of Cleaner Production, 2023 - Elsevier
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 …
Critical review of data, models and performance metrics for wind and solar power forecast
Global climatic changes and increased carbon footprints provided the main impetus for the
decrease in the use of fossil fuels for electricity generation and transportation. Matured …
decrease in the use of fossil fuels for electricity generation and transportation. Matured …
Climate change impact on photovoltaic power potential in China based on CMIP6 models
China has the largest worldwide cumulative installed photovoltaic (PV) capacity, which is
expected to be 1300 GW in 2050. Industrial production, population explosion and fossil fuel …
expected to be 1300 GW in 2050. Industrial production, population explosion and fossil fuel …
Ensemble approach of optimized artificial neural networks for solar photovoltaic power prediction
The use of data-driven ensemble approaches for the prediction of the solar Photovoltaic
(PV) power production is promising due to their capability of handling the intermittent nature …
(PV) power production is promising due to their capability of handling the intermittent nature …
[HTML][HTML] Review of methods to account for the solar spectral influence on photovoltaic device performance
The accuracy of photovoltaic (PV) performance forecasts is essential for improving grid
penetration, fault detection, and financing of new installations. Failing to account for the …
penetration, fault detection, and financing of new installations. Failing to account for the …