Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …
giving directions of solar energy conversion systems (design, modeling, and operation) …
Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
Hourly stepwise forecasting for solar irradiance using integrated hybrid models CNN-LSTM-MLP combined with error correction and VMD
Accurate and reliable solar irradiance forecasting is critical for distribution planning and
modern smart grid management and dispatch. However, due to the time series of solar …
modern smart grid management and dispatch. However, due to the time series of solar …
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 …
Comparison of Support Vector Machine and Extreme Gradient Boosting for predicting daily global solar radiation using temperature and precipitation in humid …
The knowledge of global solar radiation (H) is a prerequisite for the use of renewable solar
energy, but H measurements are always not available due to high costs and technical …
energy, but H measurements are always not available due to high costs and technical …
Forecasting of solar radiation using different machine learning approaches
V Demir, H Citakoglu - Neural Computing and Applications, 2023 - Springer
In this study, monthly solar radiation (SR) estimation was performed using five different
machine learning-based approaches. The models used are support vector machine …
machine learning-based approaches. The models used are support vector machine …
Review on probabilistic forecasting of photovoltaic power production and electricity consumption
DW Van der Meer, J Widén, J Munkhammar - Renewable and Sustainable …, 2018 - Elsevier
Abstract tAccurate forecasting simultaneously becomes more important and more
challenging due to the increasing penetration of photovoltaic (PV) systems in the built …
challenging due to the increasing penetration of photovoltaic (PV) systems in the built …
[HTML][HTML] Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China
Accurate estimation of global solar radiation (R s) is essential to the design and assessment
of solar energy utilization systems. Existing empirical and machine learning models for …
of solar energy utilization systems. Existing empirical and machine learning models for …
PV power forecasting based on data-driven models: a review
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 …
the grid and its stability. This paper presents a review of the recent developments in the field …