储能科学与技术2025，Vol.14Issue(6)：2555-2557,3.DOI:10.19799/j.cnki.2095-4239.2025.0484
基于深度学习的电网-储能联合调度策略设计
Design of power grid energy storage joint dispatch strategy based on deep learning
刘震宇 1陈建 1尹兆磊 1杨慢慢1
作者信息
- 1. 国网冀北电力有限公司承德供电公司,河北 承德 067000
- 折叠
摘要
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.关键词
深度学习/调度/储能Key words
deep learning/dispatch/energy storage分类
能源科技引用本文复制引用
刘震宇,陈建,尹兆磊,杨慢慢..基于深度学习的电网-储能联合调度策略设计[J].储能科学与技术,2025,14(6):2555-2557,3.
