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 …

This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …

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 …

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 …

Following the fourth industrial revolution, and with the recent advances in information and
communication technologies, the digital twinning concept is attracting the attention of both …

The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …

The wake effect is a major and complex problem in the wind power industry. Wake steering,
such as controlling yaw angles of wind turbines, is a proven approach to mitigate the wake …

The new generation of artificial intelligence (AI), called AI 2.0, has recently become a
research focus. Data‐driven AI 2.0 will accelerate the development of smart energy and …

Machine learning has become a widely popular and successful paradigm, especially in data-
driven science and engineering. A major application problem is data-driven forecasting of …

To reduce network integration and boost energy trading, wind power forecasting can play an
important role in power systems. Furthermore, the uncertain and nonconvex behavior of …