Providing a digital twin solution in the manufacturing environment is becoming a critical part of managing the complexity of those environments that many companies have to increasingly operate within.
As digital twins become critically important, entities are beginning to adopt this “twinning” concept dramatically, and within the Energy Transition we are undertaking, it will be no different.
A digital twin enables a Utility, for example, to visualize its assets, track the constant changes occurring consistently, and make better decisions on performance optimization.
Wikipedia offers a useful clarification of the Digital Twin.
“A digital twin is a digital replica of a living or non-living physical entity. By bridging the physical and the virtual world, data is transmitted seamlessly, allowing the virtual entity to exist simultaneously with the physical entity.
Digital twin refers to a digital replica of potential and actual physical assets (physical twin), processes, people, places, systems, and devices that can be used for various purposes.
The digital representation provides both the elements and the dynamics of how an Internet of things device operates and lives throughout its life cycle. Digital twins integrate the internet of things, artificial intelligence, machine learning, and software analytics with spatial network graphs to create living digital simulation models that update and change as their physical counterparts change.”
As the energy transition is presently undergoing such radical changes, the managing of energy and especially grid management is getting highly complex and the digitalization of this is becoming vital to manage differently. Why?
There are major shifts required from the Utilities.
These are from central one source energy systems to ones being based more on distributed energy. There is the influx of different energy sources for how electricity will be generated, mixing renewables (wind, solar) that have higher variance in supply, coupled with traditional energy resources (oil, gas, coal).
These energy alternatives are adding to the complexity of sourcing supply, pricing, and managing this mix as it enters and flows through the grid. The diversity of grid models, the ability to offer more attractive business models to enable the consumer to participate in managing their own energy, is also adding increased complexity.
Most utilities do not have one single data source domain.
Planning, operations, tracking and evaluating asset management performance, and knowing outage management, all increasingly in real-time, needs a significant re-think over any digitalization and data management as anything less than one source of data is going to be increasingly difficult to manage effectively, to operate in a changing energy market place.
Today, many utilities have real problems synchronizing data as the multiple systems that have evolved often have different data formats, are designed for specific needs, and have often separate teams to maintain the data. These are increasingly creating data silo’s and limited visibility within the total system and can have significant risks of inconsistencies within them. So many have legacy lag.
Often these (sub-optima)l systems cannot accommodate data exchanges, and a growing consequence is declining efficiency and effectiveness to manage the complete grid and potential data losses, vulnerability over data, and asset attack can build without some resolve to radically adopt a different approach.
The increasing need is to change the operating environment,
The electrical digital twin can be the solution to prove a migration of systems and move towards one single data source. Synchronizing data exchanges, being able to have scalable data collection and storage (most probably in the cloud) becomes the new base point of necessity.
Building a comprehensive exchange network data model, within and beyond one company, allows for growing intelligence and understanding.
The incentive to move towards one transmission network model management system offers integration cost reductions; it can eliminate duplicated modelling efforts and can open up the ability to plan for alternative scenarios for predictive maintenance, anticipated grid balancing, anticipating different demand options, etc.
Electricity Digital Twins to build are “no walk in the park.”
They have deployment challenges, addressing existing system complexity and require a very different level of skilled talent and workforce to manage any integration and harmonization of the current systems and manage these in the future in totally different ways.
If you can imagine bringing all assets into the digital twin of power plants, transmission and distribution lines, substations, and a growing end-use energy device network are incredibly complicated to transition.
So why do utilities need to undertake this radical overhaul of their existing systems?
When power systems are undergoing a transition from a centralized generation system to a new one that embraces new and emerging distributed ones, the data systems need equally revising. The significant shift in our energy system designs is placing demands on continually shifting between past-traditional energy sources into new decarbonized energy technologies.
The result is, of so much change occurring in the energy system there is a need for increased visibility in tracking, sourcing, adapting, and scaling, a constant ongoing ‘blending and adapting’ to keep pace with such dramatic changes being undertaken.
The digital twin, over time, will transform how and where energy is drawn down from; in options, availability, and requirements to optimize pricing. A digital twin can help determine how electricity is delivered in optimized ways and then offer variance on different business models and pricing packages to how energy can be consumed.
The aim is to increasingly provide reliable, affordable, and sustainable electric power to factories, businesses, communities. Equally to ensure the environment has clear visibility of where this energy derives from, how it is delivered in considering options and always dynamic in its attractiveness, to extract ‘best’ value for the Utility and the end-user.
These new market dynamics require a fully integrated system of physical and data operating in real-time to optimize this.
Different audiences, different needs
The Electrical Digital Twin needs to cater to the Engineer tasked with asset management, the Operations management to plan, schedule, and direct energy loads and to offer increased data understanding to all the suppliers and end-users for them to manage their part of the Network configuration.
A digital twin needs to offer increasingly immersive visualization, offer a three or four-D timeline of change occurring, account for building its history and tracking undertaking, contracts, and decision-making process for regulatory and performance evaluation.
A new digital system needs to offer analytics that enables different ‘what if’ views to be undertaken to anticipate and optimize decisions. Any digital system has to work towards constructing an end to end (E2E) of planning, simulation and engineering needs, the operations and control, and the understanding of consumption and usage.
Coming to grips with the workflows is essential
Any digital modelling system needs to accommodate a considerable design of workflows. Not just in asset performance, in providing risk-based reliability testing strategies, planning maintenance and shutdowns, as well as verify in simulations before actual execution to assess the impact and offer alternative options to consider. The ability to capture real-time data can test reality capture, site assessment needs, and grid resilience.
A robust digitalization structure can enable protection, understand power flows, provide predictive analysis as well as simulate logistics, progress, status checks, and offer stakeholder engagements in collaborations or inspection.
Suppliers of Digital Twin Solutions
Today, a number of the significant suppliers of energy solutions all working towards offering comprehensive electrical digital systems.
These included are GE, Siemens, ABB, Emerson, AVEVA, Bentley, and increasingly Autodesk, SAP, Microsoft, IBM, Oracle, and Schneider Electric, among others. Each is offering specific parts of a solution or full solutions with the future aim of these being aligned and integrated into other systems that might be legacy or through preferred suppliers.
The future digital system needs to be technology ready.
Having a system that can analyze, predict, optimize current and future demands on the networks is essential. Having one system-wide view of your assets and data will have a significant impact on the ability to gain from machine learning and AI in the future. The pressures are building on all utilities in deploying a fully integrated, connected-up network to offer reliable, low-cost, and sustainable energy in a rapidly transforming energy world.
The Electrical Digital Twin market will grow substantially in the next few years as Utilities recognize the absolute need to change their existing operating and system models. The shift is as dramatic as the one undertaken in transitioning in energy sourcing and in the implications of implementing the asset changes that this brings into the energy system.
Both the physical and digital system changes need to be undertaken without delay. Otherwise, the complexity within the energy transitions being initiated will overwhelm those that stay locked into the present of not managing their digital environment in leading ways to take on the complexities within the Energy Transition.
** Originally published on my site https://ecosystems4innovating.com/
