A digital twin is a digital representation of a physical asset or system – it is the bridge between the digital and physical world. Currently, there are two versions that are pertinent to the power and grid industry:
- Asset digital twins - at the asset level, a digital twin can model the performance of power equipment such as a transformer, generator, or a protection device. These assets are designed, built, and operated in heavily digitised environments, using the technologies mentioned above.
- System digital twins – it can also be used to model systems such as electrical networks, power plants, cable systems or complete substations.
Diagnostics
As a diagnostics tool, digital twins can provide valuable insight into why a power outage occurred, determine the root cause, and build a plan that will mitigate similar, future events.
Here the power management platform – represented by the digital twin - is built on top of a model of the actual electrical network itself. In turn, this introduces new workflows that find the root cause faster. For example, it allows the engineer to replay an incident step-by-step, inspecting measurements on any part of the network at any time.
Those same measurements from the real system can also be fed as inputs into the digital twin assets to determine if for example a breaker operated, and if not, why.
The digital representation of the real
Digital twins allow operators to run simulations before deploying it. It is therefore a valuable training and maintenance tool. As a real-world example, if an employee is scheduled to visit a substation to maintain transformers, he or she might have to go through a complex set of operations such as isolating each transformer from the utility and powering the downstream feeder from another transformer.
The above can be fully simulated on the substation digital twin before the employee leaves the office. Also, when onsite, with a connection to the digital twin, the employee can verify the planned switching actions before executing it.
Designing new electrical networks for large facilities is another important application where digital twins add value. Automation and control schemes, communication architectures, and switchgear and cabling layouts benefit from being tested and validated in a digital twin simulation before investing in costly construction and commissioning.
A mirror ball
Predictive maintenance is one of the most common uses of digital twins today. For example, a digital twin of a generator can tell you when maintenance is needed by comparing the predicted behaviour to the actual behaviour based on historic activity.
Facility energy use forecasting and validation is another common prediction application. Here, the digital twin of the facility is fed with the process, occupancy, temperature, or other parameters. The facility digital twin outputs the expected energy consumption over the next day, week, or season. This data can justify investments, confirm the facility is operating as expected, or validate investments made in the past.
Sustainability
Interestingly, one of the emerging uses of digital twin technology is in the design of environmentally conscious grid infrastructure. The digital twin model has an important role to play in equipment and systems’ decarbonisation as it provides valuable data at all stages of the product and project lifecycle.
During the design stage, digital twins are used to build and update a virtual model. Input simulates each step of the project on a single platform such as equipment’s mechanical, electrical, thermal, and environmental properties.
Therefore, digital twins provide a risk-free way to analyse, test, and experiment with different design scenarios, processes, equipment, and operations before making any changes to the physical asset’s design.
Digital twin technology has the potential to play an invaluable role in the power and grid industry, be it in daily operations or the sustainable infrastructure of the future.
