Leveraging a network of safe, integrated digital twins to address the energy challenge
The challenge of the energy trilemma – balancing security, sustainability and affordability – is not a new one facing the industry. However, recent events have exacerbated the challenge. The world has had to focus on energy security since the conflict in Ukraine, while also providing clean and affordable energy and cutting down the emissions of greenhouse gases into the air. To reduce the carbon intensity of the UK's energy system and increase electrification, we need more interaction and cooperation among all energy stakeholders. Digitalization is essential for addressing these issues and is a key tool for achieving net zero in a cost-effective way amid uncertainty, variability, and complexity.
A recent DNV survey of senior executives in the energy industry has revealed that it is advancing in its use of data driven strategies. For example, power grid operators are leading the way in digitalization in the industry by adopting complex production systems, or data standards based on common information models. In the molecular domain, several Ofgem Strategic Innovation Fund innovation projects in the UK have enabled gas networks to create digital twin concepts related to hydrogen, which are designed to connect data, processes, engineering systems and people. The ultimate aim for all should be to create a smart energy production, transmission and distribution system that can collect data from different energy systems and share it securely and systematically.
One way to think of a “digitalized energy system” is as an evolving system of connected digital twins, where data is collected, stored, processed, modelled and – often – used to help and automate decision making. As energy value chains get more connected, secure and trusted connectivity is essential and will get more attention in the next year as investment in digital technologies grows.
The value of digital twins
A digital twin is a simulation of a system or asset, that computes and reveals system information, using combined models and data, with the goal of helping decision making throughout its lifecycle.
Some people are sceptical about digital twins. This may be because they are not well specified, and people invest in them based on their technical features rather than their actual business benefits.
However, if done well, a digital twin can offer great benefits for energy sector organizations to lower costs and risks – and prolong operational life. They can be an integration platform where real-time simulations, advanced artificial intelligence, and machine learning work together to collect, analyse, and produce data that helps strategic planning and effective decision-making.
It is crucial to ask the “right questions” and set suitable business cases. This must be done safely, though.
To cite an example, in the renewable energy industry those key questions could include:
- Can a digital twin help to drive down costs through smarter operations?
- Can the production of energy be predicted, taking environmental, operational and performance data into account?
- Can a digital twin help estimate the remaining life of a turbine (i.e., fatigue monitoring) which can be used to identify opportunities to extend life and prioritize inspections and maintenance?
- Can a digital twin support a whole-systems approach when linked with low-carbon hydrogen production?
Anchoring technology investments to real-world challenges and aligning engineering, IT, data, and operational teams in that decision making process is vital. That applies to the organizational setup within each corporate boundary – and increasingly in a world of connected supply chains, outside of that ecosystem with partners, collaborators and suppliers securely connected too.
Digital twins in practice
More interaction and cooperation in the industry leads to standardization. This means data is open and shared, and information is in a common format to make data exchange easier across the supply chain. Building models on standardized libraries is essential for having digital twins that are safe, effective, and efficient.
The energy industry is witnessing a growing adoption of digital twins as strategic initiatives, such as optimizing and extending the lifetime of assets, start to demonstrate their value – along with an increased understanding of how they can support the more connected supply chains.
In wind energy generation, new technology, such as wind farm control which uses mathematical models that account for wake and electrical interactions between turbines along with ML/AI, could also support future digital twin use cases. But these new technologies will require more verified data to ensure optimal accuracy. SCADA data from wind farms - when merged with other data sources as part of a digital twin ecosystem - can assess the impact of windiness, turbine availability and performance on any deviation between actual production and operating budgets.
Essentially, digital twin projects are regarded by organizations as integration projects, combining some of the concepts mentioned above with organizational ability, maturity, and processes. Digital twins that model systems, products, processes, or assets can greatly assist in addressing the trilemma. However, creating and maintaining reliable and trustworthy digital twins and ensuring a digital twin remains "accurate" and valid over time is becoming a major industry challenge.
Digital twins with correct specifications can still face challenges in operation, as physical assets change over their lifecycles. This means companies must also ensure that a digital twin will stay suitable for its purpose long after being validated and deployed. Changes can affect an asset due to wear and tear, maintenance activities, larger modifications, and other factors. And, of course, operators need to be sure that a digital twin is secure and safeguarded against risk (both technical and supply-side) with a focus on remaining cyber-secure while accurately and reliably tracking any changes.
Creating safe, trusted, and structured transactions
The UK Government's Department of Science, Innovation and Technology released a report in March 2023 that responded to its Cyber-Physical Infrastructure (CPI) consultation. It recognized that a network of interconnected systems could form an infrastructure that supports the development of future products, services and decisions, emphasizing that the key components of those systems and their interconnection would enable more efficient and cost-effective innovation.
To assess the possible economic impact of energy-related initiatives, such as power production and delivery, we need to trust the data and especially the data that comes from the source. We anticipate more attention on verifying and ensuring the origin and accuracy of the data that is derived from the energy system in the future - especially where machine learning algorithms embedded in digital twins can substitute or supplement human workers.
Collecting data from the whole supply chain is considered a crucial step in the future energy data mix - and a key factor for the energy transition process. Using the features of data and providing proof collected from the supply chain will help to establish trust and confidence among partners and consumers. Enabling that data sharing through an ecosystem of linked digital twins - supported by a specified set of semantic data models - will be essential.
The National Energy System Operator (NESO) in the UK will have the responsibility of running a low-carbon energy system that is secure, affordable, and fair for consumers in the face of unprecedented difficulties. Projects like the Virtual Energy System of Connected Digital Twins will create a framework for energy sector digital twins to exchange data. However, it will be challenging and complex to integrate digital twins from all actors into this system. Being aware of all relevant risks – cyber, physical, data or organizational – is essential to ensure that security of supply and resilient operation are not affected by malicious actions through cyber-attacks.
At DNV, we are supporting the energy sector to become more digitally and data savvy. Trust in digital systems is paramount to achieving that. We call this Digital Trust. Our overarching purpose, to protect life, property, and the environment, motivates us to contribute to the global energy transition.
DNV’s new report – Connected Digital Twin Insights: Rising to the challenge across the UK energy sector – highlights the collective belief that achieving net-zero emissions by 2050 is only possible through digitalizing and connecting the UK’s energy system via smart data-driven systems.