  The energy sector's digital transformation brings mutually dependent
communication and energy infrastructure, tightening the relationship between
the physical and the digital world. Digital twins (DT) are the key concept for
this. This paper initially discusses the evolution of the DT concept across
various engineering applications before narrowing its focus to the power
systems domain. By reviewing different definitions and applications, we present
a new definition of DTs specifically tailored to power systems. Based on the
proposed definition and extensive deliberations and consultations with
distribution system operators, energy traders, and municipalities, we introduce
a vision of a standard DT ecosystem architecture that offers services beyond
real-time updates and can seamlessly integrate with existing transmission and
distribution system operators' processes, while reconciling with concepts such
as microgrids and local energy communities based on a system-of-systems view.
We also discuss our vision related to the integration of power system DTs into
various phases of the system's life cycle, such as long-term planning,
emphasizing challenges that remain to be addressed, such as managing
measurement and model errors, and uncertainty propagation. Finally, we present
our vision of how artificial intelligence and machine learning can enhance
several power systems DT modules established in the proposed architecture.
