综合智慧能源2025，Vol.47Issue(7)：44-54,11.DOI:10.3969/j.issn.2097-0706.2025.07.005
基于双层网络PER-MADDPG算法的综合能源系统协调优化调度
Coordinated optimization scheduling of integrated energy system based on PER-MADDPG algorithm with two-layer network
摘要
Abstract
To ensure the economic operation of an integrated energy system(IES),a coordinated optimization scheduling method for IES based on energy routers is proposed to address the issues such as difficulty in solving optimization scheduling models,slow convergence,and unsatisfactory performance in traditional model-driven scheduling methods.The IES was divided into three regions using three electrical,thermal,and cooling energy routers.Energy devices were modelled,and a Markov cooperative game model for IES optimization scheduling was established,forming a framework of centralized training and distributed execution.A Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm based on an improved two-layer Actor-Critic network was used,where the two-layer Critic network evaluated action values to avoid their overestimation.Additionally,a prioritized experience replay mechanism was incorporated to improve data utilization efficiency in the experience replay pool without compromising the diversity of data.The simulation results showed that the proposed algorithm was 10.13 s faster in calculation speed and reduced daily scheduling costs by 1 638.13 yuan compared to the unimproved method,achieving coordinated optimization scheduling of IES while ensuring system economic efficiency.关键词
综合能源系统/协调优化调度/马尔可夫博弈/能量路由器/双层Actor-Critic网络/优先经验回放机制Key words
integrated energy system/coordinated optimization scheduling/Markov game/energy router/two-layer Actor-Critic network/prioritized experience replay mechanism分类
信息技术与安全科学引用本文复制引用
陈亮,刘桂英,粟时平,唐长久,王辰浩,郭思桐..基于双层网络PER-MADDPG算法的综合能源系统协调优化调度[J].综合智慧能源,2025,47(7):44-54,11.基金项目
湖南省自然科学基金项目(2023JJ40053)Natural Science Foundation of Hunan Province of China(2023JJ40053) （2023JJ40053）
