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1.上海交通大学电子信息与电气工程学院,上海市 201100
2.国网上海市电力公司,上海市 200122
马墅研(2001—),女,硕士研究生,主要研究方向:电力大数据分析、数字孪生等。E-mail:mashuyan0809@163.com
贺兴(1986—),男,通信作者,副研究员,博士生导师,主要研究方向:电力系统大数据分析方法、随机矩阵、数字孪生等。E-mail:hexing_hx@126.com
张庄俨(2001—),男,博士研究生,主要研究方向:电力大数据分析、数字孪生等。E-mail:zhangzhuangyan@sjtu.edu.cn
收稿日期:2024-06-13,
修回日期:2024-11-11,
网络出版日期:2025-01-08,
纸质出版日期:2025-08-25
移动端阅览
马墅研,贺兴,张庄俨等.面向多主体协同与智能涌现的能源互联网元宇宙架构设计[J].电力系统自动化,2025,49(16):1-8.
MA Shuyan,HE Xing,ZHANG Zhuangyan,et al.Architecture Design of Energy Internet Metaverse for Multi-agent Collaboration and Intelligent Emergence[J].Automation of Electric Power Systems,2025,49(16):1-8.
马墅研,贺兴,张庄俨等.面向多主体协同与智能涌现的能源互联网元宇宙架构设计[J].电力系统自动化,2025,49(16):1-8. DOI: 10.7500/AEPS20240613003.
MA Shuyan,HE Xing,ZHANG Zhuangyan,et al.Architecture Design of Energy Internet Metaverse for Multi-agent Collaboration and Intelligent Emergence[J].Automation of Electric Power Systems,2025,49(16):1-8. DOI: 10.7500/AEPS20240613003.
当今能源系统趋向于开放式、扁平化发展,能源管理模式从源随荷动逐渐转向源荷互动,对传统配电网基于假设简化的还原论认知方式与经验条例的集中式管理模式提出了挑战。在此背景下,文中提出了一种融合电力专业知识、前沿机器学习与智能涌现技术的能源互联网元宇宙架构,重构系统认知与优化决策体系。首先,结合电力数智化转型趋势,阐述了元宇宙的内涵及实施路径。然后,基于数据密集型科学发现范式,设计了面向多主体协同与智能涌现的功能模块化架构,构建了可仿真可分析的能源互联网生态系统。最后,面向复杂系统的全流程认知与决策需求,从数据空间、特征空间和决策空间3个虚拟空间角度,探讨数据赋能的实现方案。中国上海临港新片区等工程示范结果显示,该架构为多主体复杂能源系统建模与仿真提供了新路径,实现了分布式能源资源的高效利用和灵活调控。
Current energy system tends to be open and flat
and the energy management mode has gradually shifted from source varing with load to source-load interaction
which challenges the centralized management mode of traditional distribution networks based on the reductionism cognitive approach of assumption simplification and empirical regulations. In this context
this paper proposes an architecture of Energy Internet metaverse that integrates electric power expertise
cutting-edge machine learning
and smart emergence technology to reconstruct the system cognition and optimization decision-making system. First
the connotation and implementation path of the metaverse are elaborated with the trend of electric power digital and intelligent transformation. Then
based on the data-intensive scientific discovery paradigm
this paper designs a functional modular architecture oriented to multi-agent collaboration and intelligent emergence. It also constructs a simulation-analyzable Energy Internet ecosystem. Finally
facing the needs of the whole process cognition and decision-making of complex systems
the realization scheme of data empowerment is discussed from the perspective of three virtual spaces
namely
data space
feature space
and decision space. The results of engineering demonstrations such as Lingang new area in Shanghai
China
show that the architecture provides a new path for the modeling and simulation of multi-agent complex energy systems
and realizes the efficient utilization and flexible regulation of distributed energy resources.
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