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Can digitalisation and AI accelerate the energy transition?

We now know that the energy system will need to change substantially in the coming decades. But what role will digital technology and AI play? And how do we get there faster?

Dan Jeavons, Vice President for Digital Innovation and Computational Science

By Dan Jeavons, Vice President for Digital Innovation and Computational Science on Jun 23, 2021

I believe that the next 10 years will be shaped by two mega trends 鈥搕he energy transition and digitalisation.

The world faces an urgent challenge. How does it tackle climate change and move to a net-zero emissions energy system while also meeting the growing demand for energy? Fifty-one billion tonnes of greenhouse gas are added to the atmosphere each year. Climate science is clear that in order to stabilise climate change, CO2 emissions need to fall to zero by 2050.

Digital technologies can make it possible to design and operate entirely new energy systems at the device, plant and regional scales 鈥 transforming the way we manage the carbon footprint of industrial processes; digital technologies can provide the tools and mechanisms for optimising the energy efficiency of operations and enabling the sharing economy; they can enable more accurate greenhouse gas emissions tracking and transparent reporting across supply chains and can also enable more effective monitoring of carbon offsets. 

I believe the next wave of digital technology will be even more disruptive than what we have seen so far:

  • Sensor based technology is generating vast data sets which can now be processed in real-time using the ever-growing cloud capabilities. This is enabling us to observe and understand the physical world in new ways.
  • The development of augmented and virtual reality technology is allowing us to visually represent these vast datasets in the context of the physical reality that is being observed 鈥 creating digital twins of physical objects.
  • The development of AI technology allows us to interrogate these data sets, to simulate previously unforeseeable scenarios, to optimise processes, predict anomalies, identify objects and draw meaning from disparate data sources. Increasingly these models, rather than being purely data driven, are infused with scientific constraints. All of this enables us to enrich the digital twin.
  • Furthermore, the ability to provide verification and trust through distributed ledgers is making new collaborations possible.

Let me share a few examples of how these technologies are already making an impact for Shell and our customers.

Over decades we have built up deep knowledge of our industrial processes. We have aggregated our process data sets into cloud-based data stores 鈥 enabling us to use this data to develop solutions which optimise these processes. In our own plants, we have shown that optimisation technology can reduce the CO2 emissions of one of our LNG facilities by as much as 130 kilotons per year 鈥 the equivalent of taking 28,000 US cars off the road1 for a year.

We are also using these optimisation capabilities to accelerate research in clean energy technology. For example, in research into low carbon fuels we are using data-driven simulation effort combined with physics-based models to optimise efficiency and yields, reduce capital expenditure, and reduce time to market. We used this approach to demonstrate that sustainable aviation fuel concepts would work at scale. In 2020 we produced 500 litres of synthetic kerosene from carbon dioxide, water and renewable energy to replace conventional hydrocarbon feedstock. In a world first, .

We are working with companies, sector by sector to cut carbon emissions together. For example, we are working with Dalmia Cement in India, to identify and optimise pathways to reach net-zero emissions at one of their cement plants. With data-driven simulations, we can replicate current plant conditions to analyse the systemic impact of changes in technology, fuels or input materials. This was instrumental in quantifying the technological and financial impacts of each emissions mitigation option for their plant.

Digital and AI can also reduce emissions in the way we move around. Shell is working with customers and partners in the shipping industry to help accelerate decarbonisation towards a net-zero emissions future for shipping. In collaboration with the University of Southampton in the 麻豆传媒, we have developed a low cost, quick to deploy optimisation software that reduces greenhouse gas emissions and fuel costs for marine vessels: Shell鈥檚 Just Add Water System. It has been deployed on more than 50 of our ships so far, yielding up to a 7% reduction in emissions per ship. We are now .

The same principles can be applied to electric vehicles. Smart charging refers to the monitoring, management and control of electric vehicle charging stations with the goal of optimising energy consumption. We are bringing charging data together, to better understand user charging profiles, essentially helping us understand how customers charge their vehicles. Our smart charging algorithm helps to maintain a stable and balanced power grid by spreading charging demand, also enabling customers to charge at a lower cost when energy demand is lower. This aggregation of power demand enables the system to maximise the use of renewable energies when they are available. Today we are already deploying these smart charging capabilities for our customers in North America.

To do all this requires a different mindset and culture. To accelerate collaboration open source, standards and interfaces are becoming increasingly important. Too often in the energy industry, proprietary systems are the norm and data sharing is rare, this reduces the opportunities for smaller start-ups to participate in the ecosystem and also limits the ability of partners to collaborate easily across organisational boundaries. It is for this reason that Shell has pushed so hard 鈥 leading the industry in developing common data standards and platforms such as , and the . Using open data standards mean that businesses can reduce the time and effort required to collect and store their data. Instead, they can focus on analysing the data and developing new solutions, including to reduce their overall environmental footprint.

Shell鈥檚 deep knowledge of the energy system combined with some of the technology we are already developing gives me confidence that we are only scratching the surface of what is possible. I am excited by the impact our projects are already having. And most of all, I am excited about what comes next鈥

To hear more watch this keynote and interview below of Dan Jeavons with Bernard Marr, CEO & Co-Founder, Bernard Marr & Co at CogX 2021.

1 This is an illustrative conversion based on the conversion rate of the US Environmental Protection Agency.

The Planet & Smart Cities: Can digitalisation and AI accelerate the energy transition?

The Planet & Smart Cities: Can digitalisation and AI accelerate the energy transition?

is the Vice-President for Digitalisation and Computational Science. He has been a key contributor to Shell鈥檚 digitalisation transformation. 

In 2020 he was listed in the Constellation Research #BT150 and Truata鈥檚 Top 100 Data Visionaries.

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From machine learning to computer vision, deep learning to virtual assistants and autonomous vehicles to robotics, Shell has been focused on a range of technologies that have supported advances in AI.

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