Metaverse Framework Designing for Energy Scheduling in Energy Internet of Things Considering Emergence [version 2; peer review: 1 approved, 3 approved with reservations, 1 not approved]

Abstract

The traditional scheduling approach, which primarily considers energy oligarchs like large-scale loads and large-scale generators, is challenged by the rapid rise of distributed energy resources (DERs) in energy internet of things (EIoT). Metaverse is emerging as one of the most promising technologies considering emergence from DERs in EIoT. Our work, from a macro perspective in the virtual space, provides a metaverse framework to harness the swarm intelligence that emerges from the aggregation behavior of massive diverse DERs in EIoT. The presented framework is built upon virtual twins, data science, systems theory, and 4th-Paradigm (data-intensive scientific discovery paradigm), enabling a novel energy scheduling mode. Our goal is to achieve data empowerment and intelligence improvement through data connectivity, virtual and real interaction, which will ultimately result in a new theory on complex system scheduling.

Keywords

• metaverse
• scheduling
• virtual twin
• data-intensive scientific discovery paradigm
• swarm intelligence
• eng