A current perspective on the accuracy of incoming solar energy forecasting

R Blaga, A Sabadus, N Stefu, C Dughir… - Progress in energy and …, 2019 - Elsevier
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 …

A comprehensive review and analysis of solar forecasting techniques

P Singla, M Duhan, S Saroha - Frontiers in Energy, 2021 - Springer
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 …

[HTML][HTML] Time series ARIMA model for prediction of daily and monthly average global solar radiation: The case study of Seoul, South Korea

MH Alsharif, MK Younes, J Kim - Symmetry, 2019 - mdpi.com
Forecasting solar radiation has recently become the focus of numerous researchers due to
the growing interest in green energy. This study aims to develop a seasonal auto-regressive …

Forecasting solar power using long-short term memory and convolutional neural networks

W Lee, K Kim, J Park, J Kim, Y Kim - IEEE access, 2018 - ieeexplore.ieee.org
As solar photovoltaic (PV) generation becomes cost-effective, solar power comes into its
own as the alternative energy with the potential to make up a larger share of growing energy …

[HTML][HTML] A novel EMD and causal convolutional network integrated with Transformer for ultra short-term wind power forecasting

N Li, J Dong, L Liu, H Li, J Yan - International Journal of Electrical Power & …, 2023 - Elsevier
Accurate wind power forecasting can enhance the safety, stability, economy and
controllability of the power system. Traditional physical methods and statistical methods are …

[HTML][HTML] Systematic review on impact of different irradiance forecasting techniques for solar energy prediction

K Sudharshan, C Naveen, P Vishnuram… - Energies, 2022 - mdpi.com
As non-renewable energy sources are in the verge of exhaustion, the entire world turns
towards renewable sources to fill its energy demand. In the near future, solar energy will be …

Day-ahead spatiotemporal solar irradiation forecasting using frequency-based hybrid principal component analysis and neural network

H Lan, C Zhang, YY Hong, Y He, S Wen - Applied Energy, 2019 - Elsevier
Owing to a shortage of fossil fuels, environmental pollution and the greenhouse effect,
renewable energy generation has become important in a modern smart grid. However, the …

An accurate GRU-based power time-series prediction approach with selective state updating and stochastic optimization

W Zheng, G Chen - IEEE Transactions on Cybernetics, 2021 - ieeexplore.ieee.org
Accurate power time-series prediction is an important application for building new
industrialized smart cities. The gated recurrent units (GRUs) models have been successfully …

[HTML][HTML] Solar radiation forecasting using machine learning and ensemble feature selection

ES Solano, P Dehghanian, CM Affonso - Energies, 2022 - mdpi.com
Accurate solar radiation forecasting is essential to operate power systems safely under high
shares of photovoltaic generation. This paper compares the performance of several machine …

A robust auto encoder-gated recurrent unit (AE-GRU) based deep learning approach for short term solar power forecasting

A Rai, A Shrivastava, KC Jana - Optik, 2022 - Elsevier
The increasing presence of solar power plants shows its potency as one of the key
renewable energy resource to fulfill energy needs of the community. This increasing …