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Evolution of Digital Twin Technology in Energy – Geoffrey Cann

These translations are done via Google Translate

Evolution of Digital Twin Technology in Energy - Geoffrey Cann

By Geoffrey Cann

Digital twin technology for energy infrastructure is on the cusp of a dramatic transformation as we decarbonize energy supply. Here’s a snapshot of where this technology is headed.

An Upcoming Conference

In this cursed pandemic age, global conferences are still mostly virtual, and will be so for some time until we sort out general global immunity.

Our collective experience with early on-line events was that they were flat, two dimensional, simple and constricted to the limitations of screen share. Video quality was uneven, audio was worse, lighting was rubbish, and the slides were unreadable. Frankly, the conference experience has had to evolve to stay relevant and interesting.

And it has. Top-notch on-line conferences now have the feel of an immersive video game. You navigate your personal avatar through a virtual world of display booths, checking out the content, on your schedule. Magically, all the conference content is being created under pandemic conditions, which means everything is built virtually and remotely.

I’m chairing just such a conference later this month, Energy 4.0, and in my role, I have had the pleasure to interview a number of guest speakers about their work, their innovations, and their outlook for the global energy industry. Parts of these interviews will feature as snippets of content for the attendees at the conference.

Register for the conference here, just US$33. You won’t regret it.

One stand-out discussion was with Peter Lasch of The Simulation Center of KSG. Peter is the Department Manager and in his role has a keen perspective on the future of digital twin technology in energy. Here’s a snapshot of our conversation.

The Simulation Business

KSG came into being years ago to provide nuclear plant simulations for training workers on plant operations, principally for Germany’s nuclear sector, but also for other European nuclear plants. The simulation and training business is changing rapidly because of Germany’s energy transition plans, which include shutting down its nuclear fleet.

Nuclear power plants have had digital versions of their facilities for nearly four decades. After all, each nuclear plant, while sharing some common features, is unique to its local setting, and it’s not practical or safe to have a scaled down physical version of the same nuclear plant for training purposes.

Traditionally new operators spent time at the training facility to learn their new roles at the helm of a synthetic digital nuclear plant. However, the pandemic forced an immediate shift to provide operator training in a fully virtual way, a feature that has opened up training far beyond the physical constraints of a fixed facility.

Simulation and training on nuclear facilities will endure as a service beyond Germany’s plans as there are many such facilities around the world. But energy transition will also open up a huge new market for simulation services.


Power generation historically has been via large stable central plants providing base load into a one-way grid that changed only slowly and predictably. Sources of energy are becoming distributed, decentralized, more varied, and in some cases, more variable and unpredictable. The future will include new supply from on and off shore wind farms, small roof top solar to gigawatt solar farms, thermal heat wells, blue and green hydrogen plants, small modular nuclear reactors, seasonal sources such as hydropower, tidal, and new energy storage via batteries, pumped storage, compressed air, and many others. The dominance of large scale monolithic power utilities serving narrow geographies is potentially over.


The energy used for transportation and industrial thermal processes has historically been separate from the energy used to light and heat homes and small businesses. Demand is becoming more integrated and interconnected. Automakers are rapidly abandoning petroleum transportation in favor of electric motors and batteries, using the same electric supply network that powers our homes. Hydrogen looks to become the industrial fuel of choice for heat and energy at scale for cement and steel making, baseload power, shipping and as an alternative for transportation fuels.


The roles in our power value chain dates back over a century, to Thomas Edison (generate, transmit, distribute, consume). The roles are now morphing as tomorrow’s power consumer with a big battery in the car and a power collector on the roof is a generator, a distributor and a consumer. Power will no longer flow in just one direction, and nor will the money. Consumers will want some decision authority to store or wheel their power, on their terms.


This emerging mesh of new energy sources, energy demand, and roles creates an entirely new and more complex modelling and simulation requirement for operators. Imagine a future where an operator needs to make a decision about dispatching available in-bound wind power supply. Should the wind farm operator go off line for repairs since other farms are likely to be operating favorably? Should the resulting power be transformed into green hydrogen for storage, or wheeled directly to the grid to displace a more expensive source, or transformed into heat supply, or loaded into industrial batteries, or offered to consumers for vehicle energy at an attractive overnight rate?

Each option entails different economic outcomes and different effects on the grid. Operators need best-in-class tools and technologies to survive and thrive in this emerging world.

The Future of the Digital Twin

Needless to say, the digital twin technologies used to simulate nuclear plants and train operators are very handy in modelling this much more complex world. Here’s where digital twin toolsets are likely to go:


Instead of simply modeling and simulating specific assets in the value chain, digital twins will model out the entire value chain, including the many distributed sources of energy, transportation needs, battery storage, base load, hydrogen generators, the works. This will be necessary because we can’t build a small scale physical version of all this infrastructure. Modelers will rely on transfer modelling, a technique whereby a working model is transferred to a new context to minimise the amount of effort required to produce a new model. Simulation development is likely to accelerate.


Dynamic simulation, which entails using live operating data from real-world conditions, instead of static datasets, as inputs into the simulator, is now available, thanks to the dramatic leaps in computer technology we have seen deployed. Even very complex calculations, including fluid dynamics, can be incorporated live and in real time.


Simulations have always take into account commercial considerations, but the future will feature much more commercial variability. In addition to dynamic simulation, digital twins include dynamic integration with commercial power markets, including short, long and spot pricing, wholesale power contracting, long dated contracts, toll structures, and other commercial power market features.


Simulation models of nuclear plants are tightly coupled to the actual plant design, and nuclear asset owners are not keen that the simulation models be available outside of the plant fence. At the nuclear asset level, this has not been a cloud world. But the future models will be thoroughly cloud enabled so that trainee operators can access the simulators from anywhere. No more travel. Cloud also unlocks the capability to deliver high fidelity analytics, not just at the asset level, but to the asset cycle level, precise to a moment in time.


Digital twin technology has always been dependent on high quality data to feed the models and simulations, and in the future, yet more so. Data in the future will be a critical factor of success, both to train the simulators, and to train operators using the simulators.

Of particular concern are those obscure disruptive events that are not reflected in operating data sets. Digital twin solutions will need to ingest synthetic data—fabricated data that is not generated from the real world—to successfully capture these rare and unique scenarios.

It’s clear that those who best capture the benefits from this technology will be equally proficient on managing data assets.


One worry that today’s operators harbor is that their jobs are at risk as utilities and grid companies build the synthetic operator of the future, an AI enabled robot or algorithm that runs the value chain. Instead, the synthetic operator will take over increasing levels of routine and uninteresting work so that the human operator of the future has more time for more valuable activity. For example, a change in equipment introduces a variance in the digital twin from the operating reality. The human operator of the future will be tasked with creating the synthetic data to help retrain the synthetic operator.


Way off into the future lies fusion energy. Fusion used to be framed on a 50 year horizon but recent advances in technology have moved fusion’s potential impacts forward to 30 years. That’s the life of a traditional fossil fuel development.


This summary is from just one of 6 incredible interviews that the conference incorporates. The cost to take in the event is very reasonable, at just US$33. Paid admission includes your very own ebook copy of my first book about digital innovation in oil and gas, Bits, Bytes, and Barrels, which has a value of $8 alone.

Check out my book, ‘Bits, Bytes, and Barrels: The Digital Transformation of Oil and Gas’, coming soon in Russian, and available on Amazon and other on-line bookshops.

Look for my next book, ‘Carbon, Capital, and the Cloud: A Playbook for Digital Oil and Gas’, coming next year.

Take Digital Oil and Gas, the one-day on-line digital oil and gas awareness course.

Mobile: +1(587)830-6900
email: [email protected]

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