A comprehensive review and analysis of solar forecasting techniques
In the last two decades, renewable energy has been paid immeasurable attention to toward
the attainment of electricity requirements for domestic, industrial, and agriculture sectors …
the attainment of electricity requirements for domestic, industrial, and agriculture sectors …
Combining solar irradiance measurements, satellite-derived data and a numerical weather prediction model to improve intra-day solar forecasting
Isolated power systems need to generate all the electricity demand with their own renewable
resources. Among the latter, solar energy may account for a large share. However, solar …
resources. Among the latter, solar energy may account for a large share. However, solar …
[HTML][HTML] Assessment of different deep learning methods of power generation forecasting for solar PV system
WC Kuo, CH Chen, SH Hua, CC Wang - Applied Sciences, 2022 - mdpi.com
An increase in renewable energy injected into the power system will directly cause a
fluctuation in the overall voltage and frequency of the power system. Thus, renewable …
fluctuation in the overall voltage and frequency of the power system. Thus, renewable …
[HTML][HTML] A comparison study based on artificial neural network for assessing PV/T solar energy production
This paper aims to employ and perform a comparison study of PV/T energy data prediction
systems using different ANNs techniques. Several studies focus on photovoltaic thermal …
systems using different ANNs techniques. Several studies focus on photovoltaic thermal …
A review and evaluation of solar forecasting technologies
After the oil crisis in 1973, the planet has to believe in alternate sources of energy aside from
conventional energy resources. Among different renewable resources, solar energy is one …
conventional energy resources. Among different renewable resources, solar energy is one …
Univariate time series prediction of solar power using a hybrid wavelet-ARMA-NARX prediction method
This paper proposes a new hybrid method for super short-term solar power prediction. Solar
output power usually has a complex, nonstationary, and nonlinear characteristic due to …
output power usually has a complex, nonstationary, and nonlinear characteristic due to …
A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long‐Term Wind Speed Forecasting in Malaysia
Since wind power is directly influenced by wind speed, long‐term wind speed forecasting
(WSF) plays an important role for wind farm installation. WSF is essential for controlling …
(WSF) plays an important role for wind farm installation. WSF is essential for controlling …
Solar radiation forecasting using gradient boosting based ensemble learning model for various climatic zones
India is seeing a massive boost in solar power installations in the recent years. It is expected
that solar energy utilization will be increasing exponentially in near future. Solar radiation …
that solar energy utilization will be increasing exponentially in near future. Solar radiation …
[HTML][HTML] Prediction and evaluation of photovoltaic-thermal energy systems production using artificial neural network and experimental dataset
Abstract Photovoltaic/thermal (PV/T) systems combine two collectors, which increase
efficiency, reduce cost and space, and produce electricity and heat, simultaneously. Many …
efficiency, reduce cost and space, and produce electricity and heat, simultaneously. Many …
[HTML][HTML] Deep learning neural networks for short-term PV Power Forecasting via Sky Image method
WC Kuo, CH Chen, SY Chen, CC Wang - Energies, 2022 - mdpi.com
Solar photovoltaic (PV) power generation is prone to drastic changes due to cloud cover.
The power is easily affected within a very short period of time. Thus, the accuracy of …
The power is easily affected within a very short period of time. Thus, the accuracy of …