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 renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction …
J Qu, Z Qian, Y Pei - Energy, 2021 - Elsevier
Accurate forecasting of photovoltaic power plays a pivotal role in the integration, operation,
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
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 …
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 …
A comprehensive review of hybrid models for solar radiation forecasting
M Guermoui, F Melgani, K Gairaa… - Journal of Cleaner …, 2020 - Elsevier
Solar radiation components assessment is a highly required parameter for solar energy
applications. Due to the non-stationary behavior of solar radiation parameters and variety of …
applications. Due to the non-stationary behavior of solar radiation parameters and variety of …
Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN …
Optimal utilisation of the sun's freely available energy to generate electricity requires efficient
predictive models of global solar radiation (GSR). These are necessary to provide solar …
predictive models of global solar radiation (GSR). These are necessary to provide solar …
Using enhanced crow search algorithm optimization-extreme learning machine model to forecast short-term wind power
LL Li, ZF Liu, ML Tseng, K Jantarakolica… - Expert Systems with …, 2021 - Elsevier
The strong volatility and randomness of wind power impact the grid and reduce the voltage
quality of the grid when wind power is connected to the grid in large scale. The power sector …
quality of the grid when wind power is connected to the grid in large scale. The power sector …
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 …
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
Solar energy is an alternative renewable energy resource that has the potential of cleanly
addressing the increasing demand for electricity in the modern era to overcome future …
addressing the increasing demand for electricity in the modern era to overcome future …