Even if all transformers are of the same specifications, each becomes a unique entity to be cared for, especially when it ages. Digital Twin maps each transformer in the substation. The Digital Twin of a power transformer can also be used for controlling the actuator. To know more equitelpower.com

1. Digital TWIN: A Digital Revolution

2. Even if all transformers are of the
same specifications, each
becomes a unique entity to be
cared for, especially when it ages.
Digital Twin maps each
transformer in the substation. The
Digital Twin of a power
transformer can also be used for
controlling the actuator.
The increasing digitalization of assets is resulting in an avalanche of data. The
knowledge of these assets could be leveraged for making better-informed
decisions. When the present grid moves more towards the smart grid, a more
pervasiveness of information and communication technology could be expected.

3. The increasing penetration of intermittent renewable energy sources and
incorporation of utility-scale energy storage systems in the near future and
technologies like electric vehicles adds in more uncertainties in the energy grid.
The power transformers in the grid assume a very significant role in the
transmission and distribution of power. A failure of which could result in
catastrophic consequences in terms of stability of the grid and its economic
implications. The modern grid is not a mere interconnection of energy devices, it
is also a network of measurement devices and communication such as
Supervisory Control And Data Acquisition (SCADA).
IoT and big data
According to a survey published by the International Council on Large Electric
Systems (CIGRE) one of the major failures of the transformer was related to
insulation breakdowns. The transformer condition is monitored using oil tests,
temperature measurements and onsite inspections. Various tests are in place for
testing power transformer while it is in operation –like Dissolved Gas Analysis
(DGA), partial discharge detector, Furfuraldehyde Analysis (FFA), temperature
measurements, thermal imaging, etc., many of which are available for online
monitoring of transformers as discrete units as well as integrated solutions. With
the expansion of the Industrial Internet of Things (IIoT), the addition of more such
online monitoring systems becomes obvious.
Digital Twins of transformers
Internet of Things (IoT) is an interconnection of physical ‘things’ that can interact
with its physical environment with sensors/actuators along with computing and
communication capabilities to exchange data with the internet. The IoT devices
have become ubiquitous in consumer electronics with the rise of smartphones,
wearable health monitors, home automation controllers, etc. IoT in the context of
the industrial environment is termed as Industrial Internet of Things (IIoT). The
increased acceptance of smart grid technologies accelerates the deployment of
IIoT in power systems, especially in the advanced metering infrastructure, digital
protection systems, phasor measurement units, intelligent electronic devices, and
asset monitoring systems. These produce an enormous amount of data in the
power system, which could be overwhelming for traditional decision-making

4. approaches. When considering an example of a 50 Hz three-phase voltage signal
sampled at 128 samples per cycle, generates a dataset of 19200 samples per
second. The collection of data, which is characterized by massive volume, high
velocity, and heterogeneous variety is termed big data. The data from the big data
analytics are applied to make sense of the collected data.
The concept of Digital Twin was introduced in a presentation related to product
life management by Dr. Michael Grieves of the University of Michigan in 2002.
The name Digital Twin was put forth by John Vickers of NASA in 2010. The Digital
Twin encompasses the physical system in the real world, its digital model, and the
communication linking them both. The digital thread concept forms the basic
subunit of a Digital Twin, which is essentially the information that could trace back
to the real-world system. The expansion in the Digital Twin is fuelled by the
Internet of Things (IoT) and reducing costs of computational and storage
resources. The data from various sensors are aggregated by the monitoring
system. The raw data collected from the sensors along with additional features
when used with appropriate machine learning algorithms could be used to create
a more realistic model of a real physical asset. A Digital Twin goes a step further
to keep the digital footprint of the transformer throughout its lifetime. The data
collected over time is analyzed for trends of relevant features. This enables
Digital Twins to be used for condition monitoring, predictive maintenance, and
remaining useful life estimation. Digital Twin creates a digital trace, so in case of
a mishap, it can be investigated with the digital counterpart. The Digital Twin
concept has been researched in various industry segments such as
manufacturing, healthcare, driverless autonomous vehicles, and machine-to-
machine interactions.
Digital Twins of transformers are virtual replicas of physical transformers, which
engineers and consultants can use to run simulations and test scenarios before
the actual devices are built, deployed, or operated. Digital Twin technology has
moved beyond the manufacturing segment and into the merging worlds of the
Internet of Things, Artificial Intelligence, and Data Analytics. Digital Twin collects
data from sensors and analyses to initiate the response through actuators.

5. The Digital Twin may be deployed either on a cloud platform or an edge
computing device. The Digital Twin deployed on the cloud platform can take
advantage of higher computing resources and big data analytics. A Digital Twin
on edge may be used for quick dynamic decisions and controls in order to avoid
any latency in communication channels and information processing. Also, the
edge-based solution is called for when considering privacy and information
security. So, one of the strategies is to have an edge model for quick decisions
and computationally demanding analytics on cloud.
Asset management and
Predictive maintenance using
Digital Twin
The Digital Twin concept provides a great choice for modeling complex systems
such as a power transformer. A Digital Twin of a transformer is a virtual image of
the real-world transformer, which captures its historical, static and dynamic
characteristics. Any changes in the actual transformer parameters get reflected in
its digital counterpart. The time-based variation of various parameters of the
transformer need to be captured as transformer health is influenced by aging and
maintenance operation. The model is initially loaded with a set of scenarios and
while in operation its measurements from the transformer are used as feedback to
keep the model updated. The Digital Twin of the transformer once made can be
used for simulating the power transformer in all different conditions.
One of the popular yardsticks for transformer health is the dissolved gas content
in the transformer oil. Traditionally dissolved gas analysis is performed in an
external lab by taking an oil sample, now an online DGA kit is being set up along
with the transformer. The condition evaluation criterion based on the DGA results
is mentioned in IEC 60599 and IEEE C57.104.
Several studies could be observed in the literature, which tries to estimate various
transformer conditions based on DGA results. This includes traditional ratio
methods, Duval’s Triangle method, and intelligent methods like fuzzy logic,
Artificial Neutral Networks (ANN), Support Vector Machines (SVM), etc. The DGA

6. in itself does not give a complete picture of the transformer condition. DGA results
are just one among several measurements associated with a power transformer.
The data generated from multiple sensors need to be collectively analyzed along
with operational history to comprehend the condition of the transformer.
The monitoring device generates data continuously about the transformer under
observation. This is apart from maintenance data, lab test results and equipment
details. The Digital Twin keeps on building the digital thread of an asset right from
its deployment, operation, and finally up to its termination. The magnitude of the
data makes it difficult for humans to understand, but an appropriate algorithm
could comprehend. In a substation with multiple transformers even if all
transformers were of the same specifications, each becomes a unique entity to be
cared for especially when it ages. So, each transformer in the substation would be
mapped over to a unique Digital Twin. The operator can use the Digital Twin and

7. its visualization real-time monitoring, situational awareness, stability analysis,
planning, fault identification, schedule upcoming maintenance, and take better
decisions. The Digital Twin of power transformers could also be used for
controlling the actuators as power transformers are now being equipped with
actuators like valves, cooling systems, dehumidifiers, tap changers, etc. The
utility company may use its collection of Digital Twins of its fleet of power
transformers for contingency analysis, maintenance schedule, and budget
allocations.