Energy And Utilities Asset Optimisation Through Digital Twin Technology
In this presentation XMPro CEO, Pieter Van Schalkwyk discusses Energy and Utilities Asset Optimisation through Digital Twin technology.
Looking to learn more about energy and utilities asset optimization using digital twin technology? This informative video presentation provides engineers in the energy and utilities industries with a comprehensive understanding of the basics of digital twin technology, as well as its applications and benefits in asset optimization.
In this video, Pieter answers the most commonly asked questions regarding digital twins, including what exactly is a digital twin, why is it important in asset optimization, and how can it be implemented in your organization.
With a focus on the unique needs of engineers in the energy and utilities industries, this presentation provides an in-depth analysis of the advantages of using digital twin technology in asset optimization. From increased efficiency and reduced costs to improved safety and productivity, digital twin technology offers a range of benefits that can revolutionize the way assets are managed in these industries.
Whether you're an engineer looking to stay ahead of the curve in energy and utilities asset optimization or simply curious about the possibilities of digital twin technology, this video is a must-watch. So sit back, relax, and get ready to learn all about energy and utilities asset optimization through digital twin technology.
Tags: Energy, Utilities, Digital Twin, Asset Optimization, Engineering, Efficiency, Safety, Productivity, Cost Reduction
Transcript
I'm beautiful and I will run you through
how energy and utilities do asset
optimization using digital twin
technology
when we speak to Executives in energy
and utilities and specifically around
asset optimization using digital twins
we kind of hear the same three questions
what is a digital twin why should I care
and how do I get started
so I'll start with what is a digital
twin we were early member of the digital
twin Consortium and in that Consortium
of 250 organizations came up with a
definition of a digital twin is a
virtual representation of a real world
entity or process that is synchronized
at a specific frequency and Fidelity and
the key is that it synchronizes the
visual representation of an entity which
could be a physical entity or something
like a business process
It Is underpinned by three things which
is it needs to improve understanding
decision making and effective action it
needs to use real-time historical and
historical data to help you analyze what
happened in the past what's happening
right now and what's likely to happen in
the future
now digital twins should be driven from
a business perspective around outcomes
we grade them around specific use cases
or applications
they are powered by integration a key
aspect using data and guided by
Specialists to understand the domain
where they operate and typically these
are implemented in the in the industrial
environment like energy utilities
through ID and ID systems
if we explain this in a picture on the
left hand side we have the physical
entity or the physical twin
and on the right hand side we have the
digital twin which consists of a model
consists of data that is synchronized at
a certain twinning right
and
during that synchronization we create an
instance or instantiate the digital twin
based on the model I can have one model
and a thousand pumps in this example and
sometimes the digital twin would feed
information back
do the equipment but that is not
necessary from a digital twin definition
perspective but it does need
synchronization from the physical to the
virtual side of it so 50 000 foot view
of what it is now you also get very
simple discrete digital twins like a
Transformer not that it's a simple piece
of equipment but you can create it a
simple digital twin around that which
could be part of a composite digital
twin for example the substation and that
substation is part of a larger bigger
Network which then becomes a system of
systems Challenge and that's how the
scope and scale of digital Twins and the
interoperability challenge with it grows
what does life look like like right now
with our digital twins well operations
maintenance safety and all these other
functions have their own little systems
on the right hand side where they
sometimes duplicate data and have
different systems and each of them or do
have their own capabilities in different
silos what a digital twin brings it's
really that proxy that allows you to use
common capabilities in the middle and
then let the different areas of the
business create use cases we'll get back
to these six core capabilities as you
see them there when you talk a little
bit later on how to build these things
so just remember the paper clip will get
back to that
the second question that we get is why
should I K now again in energy and
utilities
some of the examples here is really
around the measurable Roi and this is
how microgreens talks about the
impediments of digital Twins and why you
know from an adoption perspective one of
them is that you have to have
value-based use cases because
accountants are the killers of Joy
according to him and if you didn't know
he was the founder of the term
uh digital twins looking at energy
utilities and specifically
on the asset side predictive maintenance
according to Kinsey McKinsey and study
that was done anywhere between 10 to 20
my reduction of Maintenance costs as
well as increase in asset availability
but in 10 to 20 if you put that in
context of your organization it's
massive likewise with performance asset
Performance Management how do we improve
the utilization and and the asset
productivity again you can see anywhere
to doing five percent now if we move
that into the grid operation side of
things
on the
transmission side again anywhere from 10
to 20 in reduction in Grid related
outage times
from Navigant research the if we can now
start integrating some of these other
new generation or alternative energy
sources and we can do that in a
structured way then again the impact
anyway from three to five percent in
terms of improvement of getting those
online and lastly does it Disaster
Recovery things like natural
disasters and those how do we recover
from that how do we recover quicker and
this is from the electric power
Institute some of the numbers that they
are there
there's also been a shift in power so
how we did it traditionally we had
generation units and then we had load
units and we just it was just a
continuous optimization problem
will be moving to now
we have generators that are also
consumers and it's a really much more of
a balancing act and we have to sense the
side and act in a different way it
requires collaboration orchestration and
a lot more con flexibility compared to
where we came from historically now in
order to do that and this is from
Gartner to move now where we right now
have a limited amount of Renewables as
that changes and how we also centralized
everything even from the decision
support and the applications that we use
very monolithic applications and and
structures that we had moving into
intelligent distributed organizations
recomposable decisions the way to do
that is by one adopting digital twins in
the context of the discussion today as
well as composable capabilities and how
we do that
now again this all needs
executive support and we need to
Drive the ROI and the levers that they
have is really around and where digital
twins can support the the the ROI on the
investment is to help
with these assets around to run more
often to produce more or or enhance the
output while it's operating or running
improve the integration of distributed
assets and also minimize the cost in the
process all in the framework of enhanced
safety and also improving ESG across
these four key drivers or key threads
around business performance the process
optimization ESG monitoring compliance
and also asset performance and this is a
strategic initiative set now in order to
drive that a lot of organizations are
creating different initiatives so
underneath of those different
initiatives to address that but the real
trick is in moving from a strategic to a
tactical and operational side and
thinking about what the decision support
and automation requirements are at each
level of the triangle to turn the
strategy into execution at both the
Tactical and operational levels
when we look at this from a digital twin
perspective a little bit more bioropical
you'll see on the left hand side we have
strategic tactical and operational so
right at the top from a strategic
perspective I want to see all those Roi
drivers and I potentially even want to
see it across different sites which may
also have a tactical implication but
then I go into the asset health and then
the process household operational Health
with the equipment and again at
operational tactical levels and this is
what the digital twin can help you do
and one of the key things is you can
create metrics at every level to see how
good you are at doing that
now a different perspective on this and
the role of a digital twin is to create
that common operating picture for
operational awareness and response and
the whole idea is to change from
reactive to more prescriptive operations
and many organizations now inbound
utilities and asset intensive complex
Industries have
all array of complex assets where
there's already scada systems PLC
sensors and everything in there a whole
bunch of different applications inside
the organization Erp GIS name them ML
and then we're trying to use people
processes and automation to respond to
events that happens in all of this
context
and there are signals going from from
the assets into these systems and
transactions in terms of what people
need to do and we have subject matter
experts that have a deep understanding
of these of these assets and how they
operate now what we are trying to do is
first of all connect to all of those
signals and data and create some event
intelligence and in Excel Pro we do that
through what we call our data streams so
it's a visual way of connecting and
handling the integration to all of these
complex things around a specific use
case or application that we are trying
to do so it's a visual way of connecting
the data so that we can create
visualization so looking at the same
data at all the different levels but
from a different perspective or
different lens operationally I see
information and this is what we refer to
as event intelligence we are now
connected to these real-time data
streams and it now feeds our common
operating picture with the the or from
from the same data sources but a
different lens in perspective at the
Strategic level at the planning or
tactical level what's my view for the
next two two weeks a month a quarter
versus what's happening right now at
operational level and what do I do need
to do right now and this gives us
operations intelligence so now we've now
moved from event intelligence to being
able to operate in a better white and
again adding some more capability to
this is being able to create
recommendations that you can consolidate
from all of these different places and
have a consistent way that you present
how people respond
to different
events that happen but using again a
similar structure whether that strategic
level tactical level or even bringing it
from the underlying systems that sits at
the bottom for us that's the Holy Grail
of a common operating pictures not just
seeing the picture but to know what to
do and have prescriptive recommendations
which allows your smartest people to
kind of pull those Roi levers so they
know how to now manipulate those levers
which will reduce the risk of you being
blindsided by key events that are likely
to happen or happening
and it also improves the accountability
and close the feedback loop that
provides visibility and opportunity for
Learning and this is a whole new
business process but if I look at
digital twins in terms of business
processes this is not new this is from
Gartner in terms of you know looking for
example at an asset a digital twin what
you are trying to do is the asset
Performance Management
um you know when something's wrong we
want to rise a ticket for maintenance we
want to make sure that we've got people
we want to know that we've got space we
want to schedule the maintenance effort
and also create tasks and worklets for
for technicians to go out and do that
and then at that stage we can take the
asset offline for maintenance so once we
find a
vibration data that gives us an alert it
goes to full circle so in a way that's a
similar description but this is just a
new this is just a business process with
a different way of actuating and
responding to it instead of human to
human workflies this is now initiated
through machines and iot and sensors the
still analysis process there's still a
work plan process and there's still the
execution of making sure that it's done
and the values that's in improving the
yield and in terms of the business
outcomes making it more profitable
from an excellent Pro point of view with
a common operating picture it's the same
you know it's about integrating all of
this heterogeneous data in a drag and
drop way and then being able to combine
um off-the-shelf analytics with some
maybe some more advanced analytics
developed by your own SM
es in-house
getting that into the systems so that
you can go and create work orders and
things like that in Erp and eam and some
of the other systems and then create a
an interactive user experience a lot and
as we're moving into AR VR and some of
the others how do we support that so we
can help that technician to do the best
best job and then verifying and checking
that the work has been done
so we can close the loop on this the
next question that we get is so this is
all well and great but how do I get
started
so
the way that we get started and again
this is just based on a concept of
composable architecture there are many
different pictures I personally like
this one of well Gardner where it talks
about all these package business
capabilities that sit at the center so
how can we create these reusable blocks
almost like Lego blocks how can I create
all of these blocks and then allow my
subject matter experts where all the
data and everything comes from all the
existing systems that we have to be able
to compose new applications and this
this composition platform can handle
integration orchestration where you
exported at the operation and the
governance as we go through and then we
just build these applications on top
we've taken that same approach and just
applied it to the different types of
data and information that we see in the
industrial and specifically power
utilities environments so physics-based
models analytics iot and temporal data
transactional data and visual models and
master data as part of this you can see
all the the different types of that
lives in there through that we can now
create package business capabilities so
we can have Leak Detection we can do
current monitoring you can do ask
reusable little blocks of capabilities
and compose that together
to be able to grow digital twins that's
where X and profit we see ourselves as a
digital twin composition platform that's
really good at handling the integration
composition orchestration
the development of all of this and the
management as well as the ux spot that's
sort of on top of it while all of this
is integrated into Legacy Business
Systems I.T systems iot systems and kind
of the modern data Fabrics that we see a
lot of organizations Implement right now
that enables us to build
digital twins for Performance Management
fault detection automation
um
emissions and different we can reuse a
lot of the things that we've done and
the connections and and capabilities
have been packaged together in order to
do that from X and pro perspective the
way that we that we do that on the left
hand side we've got our data streams
which is the how do we connect and
integrate and compose and orchestrate on
the right hand side is more the ux and
the ux development in our application
designer so I mentioned earlier in terms
of the little paper clip and those six
capabilities that we saw inside digital
twin Consortium I had the opportunity to
lead a group that created the
capabilities of a periodic table and we
categorized all the capabilities of a
digital 20 into six main groups naming
uh data services integration
intelligence user experience management
and trustworthiness as the key
categories for these and inside that for
example with data services we have data
streaming data transformation so a whole
bunch of of core capabilities there's
actually 62 so in integration on
Intelligence on ux on how to manage all
of this and also from a trustworthiness
this is available on the digital twin
Consortium website
um so I'm not going to draw down into
much more detail you can get some
information there but there but you can
compose any digital twin by using some
of these blocks
and it gives so here's an example of
condition monitoring for a wind form in
this one I only use these capabilities
and if I want to create energy
prediction then suddenly I have machine
learning artificial intelligence and
some of the other things I need to add
which also helps us to start a
conversation around what capabilities do
we have in organization and which of
them should we look at building
partnering acquiring so there's a whole
bunch of things but it also helps us to
also not just focus on the smart
technical things because this is not a
technology or this is not an
architecture this is just core
capabilities but some of it relates to
trustworthiness like security safety
and also how do we handle things like
event logging and some of managing these
things at scale
so what does it look like as a typical
example so here is that wind form and
this is a remote Operation Center
so I can see my overall portfolio of
Wind forms and Silo forms and all sorts
of different
assets that I have I can see at the
moment they're all green so pretty happy
with those I can also see key outcomes
and I'll drill into much more detail on
each of these but it's really around how
can we make sure that we are outcomes
focused that we provide contextual
metadata context for decision makers how
do we focus on the asset itself and the
asset performance how can we provide
Advanced analysis as well as
collaboration and all of this and also
you know how do we provide access to
knowledge all in a common operating
picture
so with that
I'll get into a little bit more detail
on how we compose the digital twins for
us it's a three-step process the first
step is
orchestrating all of this data the
second part is and in a visual way the
second part is creating the visual
experience in this instance it's a it's
a desktop app but it could be mobile it
could be Irv or any one of those and
then how do we create recommendations
because that's a key thing you actually
the real outcome that you're looking for
is the actions that come from
recommendations so if I touch on the
first part in terms of how we build this
orchestration what you'll see here is
typically how we do it at XM Pro we've
got a visual drag and drop data stream
designer and with this I can now bring
in information from the router and the
gearbox the power the your pitch all of
that from other Telemetry using mqtt
these are all draggable blocks under
listeners there's a whole Library it's
extensible Library
um and I can drag these on I can then do
some and I can bring contacts like make
model and all that from Maxima in this
instance I can then transform that data
so there's a whole range there's a whole
bunch of blocks that are all around uh
Transformations doing calculations and
all of that
um I can add clean Wrangle data in all
of that and then the next step is
applying some AI to it you can see I'm
running a python model to predict
likelihood of failure there's anomaly on
the on the right top right I'm also
storing some data at the same time here
in in fluxdb as an action which is
action agent and on the right hand side
we then run a recommendation which is
also there are different variations all
blocks that I can drag on so this is a
visual way to build and then the data
flows based on the frequency that I'm
specifying for this as well what we've
added to this now is the ability to
bring in jupyter Notebook so we have our
AI designer which is
embedded in the product as well so I can
run some of that logic Advanced logic
correct models simulations all of that
running jupyter notebooks as part of
that data stream which is a key part of
bringing intelligence to data to to
digital twins
the next part is to make it look pretty
so the visualizations as I mentioned you
can bring in objects from external
things like Gia systems example of
Israel and also recommendations from the
recommendation engine showing me where
they are they are potential challenges
this is outcomes Focus so you can see
call metrics I'll be doing better I'll
be getting worse what's my current view
on open work orders you know and I can
see the health and across my my
different assets pretty easily if I get
into the asset itself
I can start looking at the time profile
some of the calculations around
effective utilization the power that
it's in current real-time yo and pitch
and all that I can see some of the other
live metrics the recommendations
specifically for this one
um and I this could be a 2d graph or it
could be a Unity model it could be an
Omnibus visualization and
I also have my maintenance records from
my work order history and everything as
a again as a common operating picture
for someone who makes the needs to make
a decision right now I may want to do
further analysis on this compare
different turbines in the same Wind Farm
to each other or I need to have
contextual information around what's
happening right now on in the
environment I may need to speak to
someone
from the supplier of these or someone in
our operation centers around some issues
that I'm seeing there and I have to get
some documentation and supporting
information around this
and where this is all heading as you've
seen with things like chat GPT and what
we biking in as well as the ability to
now use that and interrogate inside for
example what are the failure modes and
whatever it causes potentially for what
I'm saying here so that's where this is
heading and this is all as part of the
visualization part in the middle the
next part is being able to create these
recommendations and in this instance I
can just see some of the real-time data
around what happened
and then I can create a work order in
this instance so this will automatically
then create the work order back into my
existing system that I have like sap or
Maxima or whatever it may be
and I can do some analysis on how many
times we've seen this across this
equipment so a lot more to this I'm just
skimming over this pretty quick but
that's kind of the other core element of
an interactive digital twin which leads
me to where is this all going so what is
the future and um again I had the
opportunity to work with Dr Michael
Greaves
um and uh at the digital tone Consortium
and he's got this view of intelligent
digital twins for me it is it is a
integrated intelligent interactive
composable environment that we need so
we need to make sure that at standard
space API models as I showed at the past
need to make sure and what we're seeing
is executable AI as I've shown you where
we've got the Jupiter notebooks and
those embedded python running inside so
I can get the smarts of my Engineers
into those data streams Innovation AI
being able to run things like front
running simulation similar to what we
have in Formula One where I can speed up
the environment and kind of see what's
what's likely to happen again this is
all possible right now and then
augmenting or augmented AI for making
the digital twins smarter so taking
putting AI over the data that we're
collecting and see how can we improve
and make them smarter so we can get some
machine intelligence
um out of this from an interactive point
of view looking at making it more
um AI enabled so that they recommend for
recommendations and prescriptive
analytics creating multi-user
experiences that are that are more
collaborative generative and then also
we don't know where the industrial
minivers is going to end up or what it's
going to look like
um but the digital twins will be the
core building blocks for the industrial
metavers
and all of this in a composable way so
we can reuse
um what we're doing
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