能源互联网现行调控模式主要面向大负荷、大火电机组等能量大户,不适应其分布式能源资源(distributed energy resources,DER)渗透率不断提升的趋势.该文旨在建立多DER 主体群智调控框架,通过在虚拟空间系统性地揭示并利用DER的聚合涌现规律,激发其主观能动性,从而开启调度新模式.具体而言,拟以系统论、数据密集型科学发现范式(第四范式)等为指导思想,以虚拟孪生、大数据分析、机器学习与人机混合智能等为内核,以数字孪生、虚拟仿真推演、高维统计、时空数据分析、深度神经网络、人在回路与知识嵌入等为技术手段,设计并逐步完善"虚拟孪生+数据科学+系统论+第四范式"的系统性框架.该框架旨在通过数据贯通、数业融合、虚实交互等手段实现数据赋能提智工程系统,最终形成复杂系统调度新理论.
System Theory Study on Situation Awareness of Energy Internet of Things Based on Digital Twins and Metaverse(III):Theory and Framework for Energy Scheduling and Management Considering Swarm Intelligence
The rapid growth of distributed energy resources(DER)in energy internet of things(EIoT)poses a challenge to traditional scheduling modes,which mainly cater to large-scale loads and generators.In response,our work proposes a novel framework that leverages swarm intelligence arising from the aggregation behavior of diverse DERs in the virtual space.Our framework integrates virtual twins,data science,systems theory,and 4th-Paradigm(data-intensive scientific discovery paradigm),to facilitate a cutting-edge energy scheduling approach.Concretely,we use system theory and 4th-Paradigm as the guiding ideology;we set big data analysis,machine learning,and human-machine hybrid intelligence as the core;we take digital twin,virtual simulation,high-dimensional statistics,spatial-temporal data analysis,human-in-the-loop,and knowledge embedding as the technical means.Our goal is to achieve data empowerment and intelligence improvement through seamless data connectivity,virtual-real interaction,ultimately leading to the development of a new theory on complex system scheduling.
schedulingvirtual twindistributed energy resourcesdata-intensive scientific discovery paradigmswarm intelligencedata empowerment
万方数据
维普
