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 …

[HTML][HTML] Comprehensive review of deep reinforcement learning methods and applications in economics

A Mosavi, Y Faghan, P Ghamisi, P Duan, SF Ardabili… - Mathematics, 2020‏ - mdpi.com
The popularity of deep reinforcement learning (DRL) applications in economics has
increased exponentially. DRL, through a wide range of capabilities from reinforcement …

Advanced ensemble model for solar radiation forecasting using sine cosine algorithm and newton's laws

ESM El-Kenawy, S Mirjalili, SSM Ghoneim… - IEEE …, 2021‏ - ieeexplore.ieee.org
As research in alternate energy sources is growing, solar radiation is catching the eyes of
the research community immensely. Since solar energy generation depends on …

PV power forecasting based on data-driven models: a review

P Gupta, R Singh - International Journal of Sustainable …, 2021‏ - Taylor & Francis
Accurate PV power forecasting techniques are a prerequisite for the optimal management of
the grid and its stability. This paper presents a review of the recent developments in the field …

Model-based predictive control of a solar hybrid thermochemical reactor for high-temperature steam gasification of biomass

Y Karout, A Curcio, J Eynard, S Thil, S Rodat… - Clean …, 2023‏ - mdpi.com
The present paper deals with both the modeling and the dynamic control of a solar hybrid
thermochemical reactor designed to produce syngas through the high-temperature steam …

[PDF][PDF] A novel long term solar photovoltaic power forecasting approach using LSTM with Nadam optimizer: A case study of India

J Sharma, S Soni, P Paliwal, S Saboor… - Energy Science & …, 2022‏ - Wiley Online Library
Solar photovoltaic (PV) power is emerging as one of the most viable renewable energy
sources. The recent enhancements in the integration of renewable energy sources into the …

Stacked LSTM sequence-to-sequence autoencoder with feature selection for daily solar radiation prediction: A review and new modeling results

S Ghimire, RC Deo, H Wang, MS Al-Musaylh… - Energies, 2022‏ - mdpi.com
We review the latest modeling techniques and propose new hybrid SAELSTM framework
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …

[HTML][HTML] A review on neural network based models for short term solar irradiance forecasting

AM Assaf, H Haron, HN Abdull Hamed, FA Ghaleb… - Applied Sciences, 2023‏ - mdpi.com
The accuracy of solar energy forecasting is critical for power system planning, management,
and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant …

A review of solar forecasting techniques and the role of artificial intelligence

K Barhmi, C Heynen, S Golroodbari, W van Sark - Solar, 2024‏ - mdpi.com
Solar energy forecasting is essential for the effective integration of solar power into electricity
grids and the optimal management of renewable energy resources. Distinguishing itself from …

A cohesive structure of Bi-directional long-short-term memory (BiLSTM)-GRU for predicting hourly solar radiation

NE Michael, RC Bansal, AAA Ismail, A Elnady… - Renewable Energy, 2024‏ - Elsevier
Uncertain weather scenarios have an impact on the output of solar farms and therefore affect
the security of the grid. It is advantageous for power system operators to forecast solar …