Digitalization, a key Enabler for Energy Transition

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Digitalization is paramount to the success of energy transition with context-specific data – how data is used to reach the goals of each aspect of energy transition is what drives its value. This blog will describe – by no means exhaustively though – ways in which digital technologies can enable energy transition.

Digital technologies and digitalization help reduce carbon emissions by:

  • Improving energy efficiency
  • Optimizing energy management
  • Coordinating supply and demand in an increasingly decentralized electricity distribution network
  • Improving operational process efficiency across industry sectors

Moreover, digital technologies will be essential for the management of carbon capture and storage (CCS) and the conversion of fossil fuel-based transportation towards electrified and automated transportation.

The specific drivers for different aspects of the energy transition are diverse in nature and the use of digital technologies and the digital transformation will therefore vary. The generic imperatives are – trusted data, digital workflows and IT/OT connectedness to ensure flexible, digital-assisted or automated decision-making and coordination of activities.

This is important for e.g. oil and gas operations, utility operations, electricity exchange and transactions in decentralized power markets and energy management at private or industrial scale. In particular, a decentralized renewable energy supply, which is a key pillar of the energy transition, would be highly dependent on digitalization. As levelized cost of energy (LCOE) is constantly reducing for renewables, dealing with the characteristics of the power generation and electricity storage will be critical.

Digitalization will be critical for operational and commercial success hereof.

By means of monitoring, exception-based surveillance, predictive analytics, (un)supervised machine learning and AI-assisted decision-making digital technologies will be essential for the energy transition. It will become central for:

  • Energy management: Monitoring and optimizing energy usage based on demand, time-of-day, weather, usage patterns, peak demand, demand fluctuations, etc.
  • Energy mix optimization: Optimizing energy mix based on pre-defined targets and demand/supply patterns and switching accordingly between electricity from source-specific power supplies. Digitally-enabled demand forecasting and supply planning for coordinating supply and energy storage and discharging in a decentralized renewable-based power system will be a huge help in this.
  • Smart grids: AI-assisted operation of grids, predictive maintenance, exception-based surveillance, remote control, automated electricity trading and transactions, etc. will be core features of the future smart grids.
  • Smart building and installations: Use of mobility sensors, electricity usage patterns, peak demands, time-of-day algorithms to optimize energy spending and savings, etc. will lead to improve energy efficiency and usage. Digitalization will be a key driver in making a range of technologies, processes and transportation more energy efficient.
  • Smart metering: Devices recording information on consumption of electric energy to be shared with suppliers and prosumers for monitoring, to inform about demand and as basis for billing and electricity transactions.
  • Smart energy storage: Autonomous charging and discharging of batteries linked to renewables power installations/plants for energy management and energy mix optimization.
  • EV and smart transportation: Prediction of transportation patterns and peak demand as well as App-and IoT-based supply/demand balancing from communication between transport vehicles and suppliers/grid/EV power stations will lead to an operation and energy efficient electricity-based transportation system.
  • Automation and RPA in all sectors: Digital-enabled automation processes, transport and operations will lead to energy (and cost) saving and energy efficient solutions. This could be e.g. in the O&G, manufacturing, chemical, mining and transport sector.
  • Transactions and cybersecurity: Digital technologies such as Block-chain will be important to ensure regulatory compliance, data privacy and cybersecurity in the new decentralized network of energy trading among several entities, including private and industrial prosumers and utilities.

Digitized CCS operations in O&G

Digital oilfield methods help real-time production optimization based on production system network models and integrated asset management models to boost hydrocarbon productivity. Predictive maintenance and exception-based surveillance based on operating envelopes for wells, pipes and facilities have been improved by means of digital technologies. Computer-assisted workflows have reduced costs, improved safety and enhanced productivity and operational efficiency1.

Digital technologies will be important for carbon capture and storage (CCS) operations including planning, process automation, predictive maintenance, flow surveillance (anomaly detection) and control systems for operational efficiency, safety and profitability. For example, digital twin representation of installations and the associated power system and grid as well as monitoring of flow of liquidified CO2 in pipelines using exception-based surveillance (e.g. leak detection, pressure/temperature tracking) can be used to ensure operational efficiency, reliability and transparency. Moreover, digital solutions can also be applied to do computer-assisted CO2 injection modelling and potentially link it to CO2-based enhanced oil recovery (EOR) operations, including complex thermodynamic equations (PVT and MMP CO2 phase physics) and dynamic flow simulations.

CCS operations will involve different entities along the value chain and hence communication and logistics planning are key which can be done using digital technologies. At these interfaces digital technologies can also ease transactional aspects of CCS (cashflow, CO2 volume exchange etc.) along the value chain. Finally, graphical services can be used to broadcast operational, financial and environmental KPIs and time series hereof linked to the CCS operation.

It is foreseeable, a cloud system architecture with IT/OT interfaces to integrate different data sources (including sensor data) and to facilitate descriptive and predictive analytics based on machine learning and AI will be essential for the CCS operation.

Using data to transition to renewables

In the energy sector digital technologies are used to communicate and analyze data of the flow of power as measured from sensors. These data can be used to monitor, control and optimize electricity distribution and balance supply and demand. A key challenge in the global energy transition is management of intermittent renewable power. Weather-dependent solar and wind-based power plants and installations will increasingly replace conventional power plants and take bigger share of the power mix to be delivered in central and decentral grids. Digital technologies will be essential for matching supply and demand while being independent to highest possible degree on other conventional power sources such as coal and nuclear. Renewable power systems depend on wind and sun and cannot be conveniently switched on/off on a short notice depending on demand – which is the case for conventional coal plants. Digital technologies can be used to predict electricity demand patterns and allow information exchange between power suppliers and EVs, households and industrial building in order to optimally coordinate when electricity should come from renewables and when excess electricity is needed from conventional power plants (e.g. coal and natural gas).

With the ever decreasing LCOE of renewables, it is evident that renewables will – also for economic and commercial reasons – have a continuously increasing share of the energy mix. As mentioned, digitalization will be a key enabler to balance supply and demand and coordinate source-specific energy supply and artificial intelligence (AI) is likely to be important2. It could be AI-assisted optimization of heaters, EV charging, AC, manufacturing processes etc. Moreover, cloud-based systems for automated or digital-assisted charging and discharging of decentralized batteries to renewable power installations will be important for smart distribution and trading electricity as well as integration of decentralized renewable power sources into existing central power systems.

On a final note, digital technologies will be important for the regulatory and transactional aspects; So, it will be essential to address digital risks of hacking etc. and data privacy security as the decentralized power network will rely on automated information exchange, share of electricity and transactions between several entities in and a several interfaces throughout the power network.

A decentralized renewable supply, which is a key pillar in energy transitions depends on digitalization from a technical, operational, regulatory and security point of view!


Martin V Bennetzen

Martin is director and part of the Energy, Utility and Chemicals core team in Capgemini Norway. Martin has a background with oil and gas operations, petroleum economics, big data analytics and digitalization and has earned his PhD degree from University of Southern Denmark. Martin has worked in an oil operator company in the Qatar and Denmark and an oil service company in Norway prior to going into consultancy as has experience from day2day production optimization, master development planning and economic investment evaluation and technical/commercial due diligence. Martin is leveraging his background from oil and gas in his work on technical and economic aspects of sustainability and energy transition including renewable energy, carbon capture and storage, electrification and digitalization.

Martin has been awarded “Top 100 Business Talent” in Denmark in 2016 by the Danish Newspaper ‘Berlingske Business’ and received the EliteResearch Award from the Danish Ministry of Science, Technology and Innovation in 2010.

Reference Link

[1] – and Society of Petroleum Engineers, paper 128245 ( )

[2] –

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