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Renewable energy sources integration via machine learning modelling: A systematic literature review
T Alazemi, M Darwish, M Radi - Heliyon, 2024 - cell.com
The use of renewable energy sources (RESs) at the distribution level has become
increasingly appealing in terms of costs and technology, expecting a massive diffusion in the …
increasingly appealing in terms of costs and technology, expecting a massive diffusion in the …
Wind power forecasting based on daily wind speed data using machine learning algorithms
Wind energy is a significant and eligible source that has the potential for producing energy
in a continuous and sustainable manner among renewable energy sources. However, wind …
in a continuous and sustainable manner among renewable energy sources. However, wind …
Long-term wind power forecasting using tree-based learning algorithms
The intermittent and uncertain nature of wind places a premium on accurate wind power
forecasting for the reliable and efficient operation of power grids with large-scale wind power …
forecasting for the reliable and efficient operation of power grids with large-scale wind power …
Recent approaches of forecasting and optimal economic dispatch to overcome intermittency of wind and photovoltaic (PV) systems: A review
Renewable energy sources (RESs) are the replacement of fast depleting, environment
polluting, costly, and unsustainable fossil fuels. RESs themselves have various issues such …
polluting, costly, and unsustainable fossil fuels. RESs themselves have various issues such …
[PDF][PDF] Short-term wind energy forecasting using deep learning-based predictive analytics
Wind energy is featured by instability due to a number of factors, such as weather, season,
time of the day, climatic area and so on. Furthermore, instability in the generation of wind …
time of the day, climatic area and so on. Furthermore, instability in the generation of wind …
Machine learning techniques for renewable energy forecasting: A comprehensive review
Over the past decade, renewable energy resources, such as wind, solar, biomass, ocean
energy and other kinds of energy, are becoming attractive technologies for building green …
energy and other kinds of energy, are becoming attractive technologies for building green …
[HTML][HTML] Wind power long-term scenario generation considering spatial-temporal dependencies in coupled electricity markets
Wind power has been increasing its participation in electricity markets in many countries
around the world. Due to its economical and environmental benefits, wind power generation …
around the world. Due to its economical and environmental benefits, wind power generation …
Assessment of Three Learning Machines for Long‐Term Prediction of Wind Energy in Palestine
T Khatib, R Deria, A Isead - Mathematical Problems in …, 2020 - Wiley Online Library
In this research, an approach for predicting wind energy in the long term has been
developed. The aim of this prediction is to generate wind energy profiles for four cities in …
developed. The aim of this prediction is to generate wind energy profiles for four cities in …
Evolution of artificial neural development
GM Khan - Studies in Computational Intelligence, 2018 - Springer
Gul Muhammad Khan In Search of Learning Genes Page 1 Studies in Computational
Intelligence 725 Gul Muhammad Khan Evolution of Artificial Neural Development In Search of …
Intelligence 725 Gul Muhammad Khan Evolution of Artificial Neural Development In Search of …
Long-term forecasting of intermittent wind and photovoltaic resources by using Adaptive Neuro Fuzzy Inference System (ANFIS)
Forecasting of intermittent solar photovoltaic (PV) and wind resources is crucial for future
power system efficient operation. This paper presents the use of Adaptive Neuro Fuzzy …
power system efficient operation. This paper presents the use of Adaptive Neuro Fuzzy …