Abstract:

With the rapid development of renewable energy and the continuous advancement of smart grid technology, grid energy storage joint scheduling has become an important means to improve the operational efficiency and reliability of the power system. This article proposes a deep learning based power grid energy storage joint scheduling strategy, which achieves intelligent scheduling of the power grid and energy storage system through data preprocessing and feature extraction, deep learning model construction and optimization, scheduling strategy formulation and implementation, and other steps. The experimental results show that this strategy can significantly improve the energy utilization efficiency of the power system, reduce operating costs, and provide strong support for the sustainable development of the power system.

Key words: deep learning, dispatch, energy storage