Wind power grid-connected power prediction and optimization based on Internet of Things and deep learning

The growing integration of renewable energy into modern grids demands accurate wind power forecasting to ensure stable operations and efficient energy management. Existing methods often overlook nonlinear patterns and fail to fully exploit the Internet of Things (IoT)-based data acquisition, along with advanced deep learning-driven optimization for grid-connected power prediction and optimization. This research proposes a novel framework for grid-connected wind power prediction and optimization