A fortunate decision that you can trust -- Digital Twins as enabler for
the next generation of EMS and sophisticated operator assistance systems
Abstract
The operation of power systems is becoming more intricate due to the
energy transition’s effects. This includes a rising share of
intermittent and decentralized renewable generation, increased
uncertainty in energy supply, and market-driven cross-border electricity
transportation in Europe. These changes necessitate improved
observability and control of critical system parameters to ensure power
system reliability. Additionally, the transition requires enhanced
resilience against cyber threats and system stability issues. To address
these challenges, innovative approaches like the Digital Twin (DT)
concept and data-driven techniques are proposed.
The Digital Twin involves virtual representations of systems that mirror
physical conditions, connecting the physical and digital realms through
sensor data streams. This concept holds potential for applications
demanding better observability and predictive capabilities. As power
systems evolve towards higher automation, the DT becomes integral to
discussions on autonomous systems and advanced power grid operation.
This paper introduces the concept of DT-centered Energy Management
Systems (EMS) and highlights its advantages in enabling future power
grid automation.
To implement DT in EMS, high-fidelity analytical models are required for
accurate representation of the physical system. Combining DT with
analytics allows holistic understanding, enabling novel automation and
control methods by linking the physical and digital realms.
A Single Source of Truth (SSoT) is foundational for creating a DT of
complex infrastructures. The SSoT integrates diverse data sources,
eliminating translation issues between software tools and data silos.
This consolidates grid data, enhancing efficiency, flexibility, and
reliability. SSoT-based DT enables adaptability to changing conditions,
supporting efficient market participation and network reliability.
The proposed EMS architecture employs DT as the core component for
monitoring and control. It combines predictive modeling, dynamic state
estimation,, model validation as well as parameter tuning to enhance the
model fidelity and simulation accuracy. The ained trust in the decisions
derived from the model results facilitates the developement of advanced
decision support and operator assistance systems.
To address power system stability challenges, Dynamic Security
Assessment (DSA) using a DT is introduced. DSA extends beyond
traditional Static Security Assessment by considering transient
dynamics. DT-based DSA involves real-time and offline components,
continuously updating models and assessing grid security against
congestions and contingencies.
A trust model is introduced to assess the coherence and state of a DT.
It encompasses facets like functional correctness, safety, security,
reliability, credibility, and usability. By applying trust across
subsystems and services, a holistic view of the digitalized energy
system’s health and state is achieved.
This paper presents the concept of applying the DT as the core instance
in the next generation of EMS and discusses the advantages of this
prospective novel EMS architecture. It describes the evolutionary
development in the power system domain from basic Digital Twin
applications to systems that enable automated power grid operation in
future.
In conclusion, the integration of Digital Twin concept into EMS offers
novel opportunities for power system operation and automation. It
enhances observability, predictive capabilities, and decision support,
enabling resilient and efficient grid management in the context of the
energy transition. The presented trust model ensures system reliability
and facilitates informed decision-making.