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 …
A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems
The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …
application on the multivariable prediction of IES parameters have mostly been carried out …
[HTML][HTML] Hourly predictions of direct normal irradiation using an innovative hybrid LSTM model for concentrating solar power projects in hyper-arid regions
Although solar energy harnessing capacity varies considerably based on the employed
solar energy technology and the meteorological conditions, accurate direct normal …
solar energy technology and the meteorological conditions, accurate direct normal …
Short-term photovoltaic power forecasting using an LSTM neural network and synthetic weather forecast
MS Hossain, H Mahmood - Ieee Access, 2020 - ieeexplore.ieee.org
In this paper, a forecasting algorithm is proposed to predict photovoltaic (PV) power
generation using a long short term memory (LSTM) neural network (NN). A synthetic …
generation using a long short term memory (LSTM) neural network (NN). A synthetic …
Application of support vector machine models for forecasting solar and wind energy resources: A review
Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …
research has proved that renewable energy sources, especially solar and wind, can be …
Solar photovoltaic generation forecasting methods: A review
S Sobri, S Koohi-Kamali, NA Rahim - Energy conversion and management, 2018 - Elsevier
Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
Sunshine duration measurements and predictions in Saharan Algeria region: An improved ensemble learning approach
Sunshine duration is an important atmospheric indicator used in many agricultural,
architectural, and solar energy applications (photovoltaics, thermal systems, and passive …
architectural, and solar energy applications (photovoltaics, thermal systems, and passive …
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 …
A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models
The uncertainty associated with modeling and performance prediction of solar photovoltaic
systems could be easily and efficiently solved by artificial intelligence techniques. During the …
systems could be easily and efficiently solved by artificial intelligence techniques. During the …
Taxonomy research of artificial intelligence for deterministic solar power forecasting
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …
stochastic and volatile nature of solar power pose significant challenges to the reliable …