Industrial control systems (ICS) and supervisory control and data acquisition (SCADA)
systems, which control critical infrastructure such as power plants and water treatment …

Accurate wind power prediction is critical for efficient grid management and the integration of
renewable energy sources into the power grid. This study presents an effective deep …

Accurate and stable prediction of regional wind power is crucial for optimal scheduling and
renewable energy utilization in the power grid. In this paper, a novel multi-objective …

Currently, numerous machine learning (ML) techniques are being applied in the field of
renewable energy (RE). These techniques may not perform well if they do not have enough …

Wind and solar energy forecasting have become crucial for the inclusion of renewable
energy in electrical power systems. Although most works have focused on point prediction, it …

There is recent interest in using model hubs–a collection of pre-trained models–in computer
vision tasks. To employ a model hub, we first select a source model and then adapt the …

Over the past decades, energy forecasting has attracted many researchers. The
electrification of the modern world influences the necessity of electricity load, wind energy …

Wind speed interval prediction is one of the most long-standing challenges because of the
high uncertainty and the complex spatial–temporal correlation between wind turbines. In this …

Wind power constitutes a pivotal component in the quest for carbon neutrality, serving as a
principal renewable energy source. Enhancing the accuracy of wind power forecasting …

Integrating new renewable energy resources requires robust and reliable forecasts to
ensure a stable electrical grid and avoid blackouts. Sophisticated representation learning …