On future power system digital twins: A vision towards a standard architecture
Wouter Zomerdijk, Peter Palensky, Tarek AlSkaif, Pedro P. Vergara

TL;DR
This paper envisions a standardized architecture for digital twins in power systems, integrating AI and ML to enhance system lifecycle management and address current challenges in measurement, modeling, and uncertainty.
Contribution
It introduces a tailored definition of power system digital twins and proposes a comprehensive, standard ecosystem architecture for their integration and application.
Findings
Proposes a standard digital twin ecosystem architecture for power systems.
Highlights integration of AI/ML to improve digital twin functionalities.
Discusses challenges like measurement errors and uncertainty management.
Abstract
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, the authors 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, the authors 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…
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Taxonomy
TopicsElectric Power Systems and Control
MethodsFocus
