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[HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective
Economic development and the comfort-loving nature of human beings in recent years have
resulted in increased energy demand. Since energy resources are scarce and should be …
resulted in increased energy demand. Since energy resources are scarce and should be …
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 …
[HTML][HTML] Global wind energy resources decline under climate change
Wind energy is poised to play a major role in the energy transition. The objective of this work
is to investigate the effects of climate change on global wind energy resources. For this …
is to investigate the effects of climate change on global wind energy resources. For this …
A review of very short-term wind and solar power forecasting
Installed capacities of wind and solar power have grown rapidly over recent years, and the
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
Artificial intelligence techniques in smart grid: A survey
The smart grid is enabling the collection of massive amounts of high-dimensional and multi-
type data about the electric power grid operations, by integrating advanced metering …
type data about the electric power grid operations, by integrating advanced metering …
A novel genetic LSTM model for wind power forecast
Variations of produced power in windmills may influence the appropriate integration in
power-driven grids which may disrupt the balance between electricity demand and its …
power-driven grids which may disrupt the balance between electricity demand and its …
Near real-time wind speed forecast model with bidirectional LSTM networks
Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
[HTML][HTML] Dynamic grid stability in low carbon power systems with minimum inertia
The power system transition to large penetrations of renewable generation has become a
core target of decarbonisation roadmaps in many countries. However, switching from …
core target of decarbonisation roadmaps in many countries. However, switching from …
Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …