In light of recent reports of the growing cyber security risks to windfarms, RenewableUK is pleased to be holding our first cyber security seminar. With new cyber security policies in the UK and EU, Graham Faiz, Head of Growth and Innovation at DNV gives a deep dive on how digitalisation role in energy security, what this is and how best to protect your business.
For many years our industry has faced the energy trilemma, implying a need to prioritize between secure, clean, and affordable energy. The geopolitical situation since the war in Ukraine has forced the world to prioritize energy security, balancing the provision of clean and affordable energy whilst drastically reducing emissions of greenhouse gases into the atmosphere. Decarbonizing and – in many cases – electrifying the UK's energy systems requires increased interaction and cooperation between all energy stakeholders. Digitalization is central to dealing with these challenges and is a key enabler for a pathway towards net zero in an affordable way against a backdrop of volatility, unpredictability, and complexity.
Energy Industry Insights a recent DNV survey of the energy industry has indicated that it is becoming more sophisticated with respect to data driven strategies. For instance, power grid operators are at the forefront of adopting digitalization in the industry through the introduction of complex production systems,or data standards using common information models. In the world of molecules,a number of successful innovation projects across the UK funded by Ofgem have seen gas networks develop digital twin concepts linked to hydrogen, aimed at uniting data, processes, engineering systems and people. Ultimately for all, the goal must be to develop a smart energy production, transmission and distribution system that can aggregate data from disparate energy systems and share it in a secure, systematic way.
Conceptually, one could say that a “digitalized energy system” is still in the process of evolution. In effect, this could also be labelled a digital twin – or more accurately: a system of connected digital twins, where data is stored, captured, processed, modelled and – in many cases – used to support and then automate decision making. As energy value chains become increasingly connected, secure and trusted connectivity is key and one that will increase in focus over the coming year as investment in digital technologies increase.
The value of digital twins
We define a digital twin as a virtual representation of a system or asset, that calculates system states and makes system information available, through integrated models and data, with the purpose of providing decision support over its lifecycle.
Digital twins have historically been met with a mixed response. A lack of trust in their potential is possibly due to incorrect specification, where investment has been driven by the promise of technological capabilities rather than real and well-defined business needs.
However, implemented correctly, a digital twin holds incredible potential for helping organizations in the renewable energy industry to reduce costs and risks – and extend operational life. They can become a platform where real-time simulations, advanced artificial intelligence and machine learning combine to collate, analyse, and generate data that supports strategic planning and effective decision-making.
Asking the “right questions” and defining appropriate business cases is as critical for the renewables industry as it is for others. This does, though, need to happen in a secure way.
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
Standardization across the industry comes from increased interaction and cooperation. This implies open data and data sharing, and the need for information to be in an agreed common format to facilitate data exchange across the supply chain. Building models on standardized libraries is the required foundation of having safe, effective, and efficient digital twins.
In the renewable energy industry, we are seeing an increase in the uptake of digital twins as the benefits case starts to be built through strategic initiatives, such as lifetime optimization and extension – alongside an increased awareness of the role they can play in those increasingly connected supply chains.For example, digital twins can help detect structural issues, such as rotor imbalance and foundation degradation, which can be mitigated to reduce operating costs, increase energy capture, and extend turbine life. Combining physics-based simulation models, which can calculate fatigue accumulation on the main structural components and provide an estimate of the remaining life of a turbine, will identify opportunities to extend life and prioritize inspections and maintenance.
Emerging technologies, such as wind farm control which uses numerical models that incorporate wake and electrical interactions between turbines alongside ML/AI, could also underpin future digital twin use cases.Emerging technologies will increase the need for validated data to ensure maximum accuracy. SCADA data from wind farms – when combined with other data sources as part of a digital twin ecosystem – can estimate the contribution of windiness, turbine availability and performance to any difference between actual production and operating budgets.
Fundamentally, digital twin projects are increasingly seen by organizations as integration projects, uniting some of the concepts identified above alongside organizational capability, maturity, and processes. Digital twins representing systems, products, processes, or assets can significantly help in resolving the trilemma. However, building robust and trustworthy digital twins and keeping a digital twin “sharp” and valid over time is emerging as a key industry challenge.
Even with correctly specified digital twins, problems can arise in operation, as physical assets undergo changes during their lifecycles. This means companies must also be able to trust that a digital twin will remain fit-for-purpose long after being approved and deployed. Change can come to an asset through degradation and aging, maintenance activities, larger modifications, and from other sources. And, of course, Operators need to be confident that a digital twin is secure and protected against risk (both technical and supply-side) with an emphasis on remaining cyber-secure whilst accurately and reliably monitoring any changes.
Creating safe, trusted, and structured transactions
In March 2023, the UK Government – through its new Department of Science, Innovation and Technology – published a response to its Cyber-Physical Infrastructure (CPI) consultation. It acknowledged that an ecosystem of networked systems could be an infrastructure on which future products, services and decision-making processes are built, highlighting that those interconnected systems and the architectures, tools, platforms, and data that underpin them would drive faster and cheaper innovation.
Understanding the potential economic impact in terms of market uptake, consumer demand, and future infrastructure investment in energy related initiatives, such as power generation and distribution, requires establishing trust in data and specifically data that is derived from source. We expect to see greater focus on validating and assuring the provenance and veracity of derived data in the energy system over the coming years –particularly where human operatives are replaced or augmented by machine learning algorithms baked into digital twins.
Gathering data along the entire supply chain is seen as a vital step in the future energy data mix – and a key contributor to the energy transition process.Building upon the characteristics in data and providing evidence gathered from the supply chain will help to build trust and confidence among partners and consumers. Facilitating that exchange of data through an ecosystem of connected digital twins – enabled through a defined set of semantic data models– will be critical.
In the UK, the Future System Operator will have a remit to operate a decarbonized energy system that is reliable, affordable, and fair for consumers against a backdrop of unprecedented challenges. Projects,such as the Virtual Energy System of Connected Digital Twins introduced by National Grid ESO, will provide such a framework for digital twins to connect and share data.However, the challenge of integrating digital twins from all parties into this system will be challenging and complex. Being aware of all associated risks – cyber, physical, data or organizational – is key to ensuring security of supply and resilient operation is not impacted due to malicious intentions unleashed through cyber-attacks.
At DNV, we are supporting digital and data maturity in the energy sector. Our overarching purpose, to safeguard life, property, and the environment, is what’s driving us to play our part in the global energy transition. Here in the UK, we’re already working alongside energy networks in programmes funded by DESNZ and Ofgem to understand and overcome the digitalization challenges that exist in the energy industry.We believe secure, connected, and trustworthy digital twins with quality assured data value chains will have a crucial role to play within the renewable energy industry and beyond.