能源研究与管理2026，Vol.18Issue(1)：98-106,123,10.DOI:10.16056/j.2096-7705.2026.01.012
基于强化学习的多元混合储能聚合协调优化调度
Coordinated Optimal Dispatch of Multi-Element Hybrid Energy Storage Aggregation Based on Reinforcement Learning
李睿 1庞德放 2邓睿锋 3张瑞君 1王袁琛 3刘承志 1陈桥 3梁小龙 4贾利军 4李建斌5
作者信息
- 1. 华电新能源集团股份有限公司,北京 100031
- 2. 西安交通大学 自动化科学与工程学院,西安 710049
- 3. 华电电力科学研究院有限公司,杭州 310030
- 4. 内蒙古华电腾格里绿色能源有限公司巴彦浩特光伏分公司,内蒙古阿拉善左旗 750300
- 5. 西安交通大学 能源与动力工程学院,西安 710049
- 折叠
摘要
Abstract
To address the power fluctuations and economic dispatch challenges caused by the high penetration of renewable energy in park-level microgrids,this paper proposes a coordinated optimal dispatch method for multi-type hybrid energy storage aggregation based on deep reinforcement learning.The objective is to achieve dynamic and accurate allocation of heterogeneous energy storage resources and reduce the overall operating cost of the system.First,an aggregated system model incorporating flywheel energy storage,lithium-ion batteries,and vanadium redox flow batteries is established.Considering time-of-use electricity pricing,differentiated operation and maintenance costs,and a tiered carbon trading mechanism,an economic dispatch model is formulated with the minimization of the daily total operating cost as the objective.Subsequently,the deep deterministic policy gradient(DDPG)algorithm is introduced to solve the optimization problem.The results show that,the proposed method enables frequency-based cooperative operation among different storage technologies,where flywheel energy storage suppresses high-frequency power fluctuations,vanadium redox flow batteries perform long-duration peak shaving and valley filling,and lithium-ion batteries provide flexible regulation.Compared with the scenario without energy storage,the total daily operating cost of the system is significantly reduced,with the cost-saving rate eventually stabilizing at 23.9％.The results indicate that the proposed method effectively exploits the complementary characteristics of multiple energy storage technologies,improving the economic performance of the park while promoting low-carbon operation.关键词
混合储能系统/聚合调度/锂离子电池/钒液流电池/飞轮储能/深度强化学习Key words
hybrid energy storage system/aggregated scheduling/lithium battery/vanadium redox flow battery/flywheel ener-gy storage/deep reinforcement learning分类
能源科技引用本文复制引用
李睿,庞德放,邓睿锋,张瑞君,王袁琛,刘承志,陈桥,梁小龙,贾利军,李建斌..基于强化学习的多元混合储能聚合协调优化调度[J].能源研究与管理,2026,18(1):98-106,123,10.
