The industrial process consumes substantial energy and emits large amounts of carbon
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …

Wind power prediction is crucial for successfully integrating large-scale wind energy with the
grid and achieving a carbon-neutral energy mix. However, previous studies encountered …

Wind speed forecasting is of considerable economic and social significance; however, it
remains challenging. Most state-of-the-art methods attempt to select the optimal predictor for …

Developing advanced battery materials, monitoring and predicting the health status of
batteries, and effectively managing retired batteries are crucial for accelerating the closure of …

Isolated microgrids have been widely used on campuses, becoming an important part of
their power-supply infrastructure. In this study, a stochastic optimal scheduling strategy that …

This research constructed the innovative Local-EMD-WaveNet, a multi-channel neural
network model, specifically designed for the prediction of significant wave height (SWH) at a …

Electricity consumption prediction is crucial for the operation, strategic planning, and
maintenance of power grid infrastructure. The effective management of power systems …

Structural health monitoring (SHM) is key in civil engineering because of the importance and
the aging of the infrastructure. We argue that applying leading-edge, data-driven methods of …

Accurately predicting residential solar energy consumption is crucial for efficient electricity
production, supply, and power dispatch. However, conventional forecasting methods often …

Accurate peak load forecasting is crucial to ensuring the reliable operation of the power
system. However, existing prediction models often neglect full explanations for peak loads …