How the REFORMERS Digital Twin is being developed to make energy flows visible, support smarter control and help explore future energy choices
Renewable Energy Valleys are built in the physical world: with solar panels, wind turbines, batteries, cables, homes, companies and substations. But once these elements start interacting, another layer becomes essential: a digital twin.
An energy valley is not just a collection of renewable technologies. It is a complex local energy system in which production, storage, demand, flexibility and grid capacity all influence each other. A battery may be useful for one company, but even more valuable if it is coordinated with nearby renewable generation. One neighbourhood may benefit from home batteries, but only if they are used in a way that also supports the local grid. A municipality may want to stimulate electrification, but needs to understand where this creates opportunities and where it may increase congestion or costs.
This is where the Digital Twin comes in.
Within REFORMERS, TU Delft, AIT, and partners are developing a Digital Twin blueprint for Renewable Energy Valleys. The goal is not to create a single dashboard or one fixed software tool. Instead, the Digital Twin is being developed as a flexible digital environment that can bring together data, models and services to support both daily operation and longer-term decision-making. Work Package 5 specifically focuses on Digital Twin technology for reliable and cost-effective operation of energy valleys, combining data-related functions, model-based support and operational decision-support services.
As Jort Groen, REFORMERS Work Package leader at TU Delft, explains:
“The Digital Twin is an extension of reality. It shows energy flows and system states that are otherwise invisible, it allows us to look ahead, and it helps us compare different possible futures before decisions are made in the physical system.”
Making the invisible visible
In a traditional energy system, much of what matters is hard to see. Electricity flows through cables. Batteries charge and discharge. Companies shift demand. Households install new technologies. Weather conditions change renewable production. Prices change over time. Grid capacity can become constrained in one place while there is still flexibility somewhere else.
A Digital Twin helps organise this complexity.
It can combine information from the physical energy valley with models that forecast, optimise or simulate. This makes it possible to understand not only what is happening now, but also what may happen next. For example: how much wind power might be available tomorrow? What happens if several companies increase their demand at the same time? How could a battery be used to reduce peaks? What would a new policy mean for the grid, for households and for affordability?
The Digital Twin does not replace human decision-making. It supports it. It helps people ask better questions, compare options and make trade-offs more visible.
The REFORMERS Digital Twin as an extension of the physical energy valley
Data from physical assets such as renewable generation, batteries, homes, companies and grid infrastructure is organised into a shared digital environment. Models and services then use this information to support forecasts, optimisation, scenario analysis and decision-making.
What sits underneath a Digital Twin?
For a user, a Digital Twin may appear as a map, dashboard, recommendation or scenario comparison. But underneath that visible layer, several parts need to work together.
First, there is the physical layer: the actual energy valley, including batteries, renewable generation, buildings, homes and grid infrastructure. Then there is the data and knowledge layer, where information about these assets is organised in a shared digital language. This matters because different contributors, models and services need to understand the same system in the same way.
Monitoring and forecasting
On top of this, models can forecast renewable generation, estimate demand, simulate scenarios or optimise the use of flexible assets. These models need to be connected, updated and reused in a reliable way. Finally, the service and interface layers translate the results into something useful for people: an advised operating point, a visualisation, a policy scenario or a planning insight.
As Edmund Widl, Digital Twin expert at AIT, puts it:
“A good model on its own is not enough. To become useful in a Digital Twin, it needs to be connected to live data, deployed reliably and monitored over time. The real challenge is turning a standalone model into a robust service that behaves well in the messy reality of live energy systems.”
adaptability to different environments
This is why interoperability is so important. A Digital Twin for Renewable Energy Valleys cannot be a rigid, one-size-fits-all tool. The mix of technologies, companies, households, local policies and grid constraints will differ from one region to another. The Digital Twin therefore needs to be modular: different parts should be able to connect, evolve and be reused without rebuilding the whole system.
That is also why REFORMERS is developing a blueprint. The ambition is to create an approach that can be reused beyond the Alkmaar flagship valley and support future energy valleys across Europe. The REFORMERS project aims not only to develop the Boekelermeer/Alkmaar flagship, but also to support deployment of multiple self-sufficient energy valleys through a roll-out blueprint and replication toolbox.
Energy Management Systems as one Digital Twin service
One of the most concrete uses of the Digital Twin is energy management.
An Energy Management System helps monitor, coordinate and optimise energy assets. In the REFORMERS context, energy management is not separate from the Digital Twin. It is one of the services that it can support.
A good example is the InVesta energy hub in the Boekelermeer region, Alkmaar. At this site, industrial start-ups working on green-molecule technologies operate alongside a 2 MWh battery and local wind generation – a combination that creates many opportunities, but also requires careful coordination.
For such a hub, energy management is not simply a matter of switching one asset on or off. The system needs to consider live data, forecasts, flexibility, battery state, local constraints and future scenarios. The Digital Twin is being developed to support this process by calculating an advised operating point for the hub. In this phase, that advice supports decision-making rather than directly taking over control.
This distinction matters. In complex local energy systems, trust comes step by step. Before automated control can be considered, companies and operators need to understand what a system recommends, why it recommends it and what the expected effects are.
From live data to energy management advice at the InVesta energy hub
The Digital Twin combines information such as wind forecasts, battery state, company flexibility and energy prices. These inputs can support optimisation and provide an advised operating point for the site, helping stakeholders coordinate flexible assets without directly taking over control.
A second example is Heiloo, where residents have been introduced to the idea of coordinated control of home batteries. Here, the Digital Twin perspective is different. Instead of an industrial energy hub, the focus is on households and many smaller assets. The question becomes: how can individual batteries support residents while also contributing to the wider energy valley?
Together, these examples show the diversity of Digital Twin applications. The same underlying approach can support both industrial coordination and residential flexibility, but the users, assets and questions are different.
Looking beyond operation: Digital Twins for policy
A Digital Twin is not only useful for live energy management. It can also help local policy makers explore future choices.
For municipalities, the question is often not “what should the battery do now?” but “what happens if this neighbourhood gets electrified?” or “where should we invest first if we want climate policy to be effective and fair?”
This is especially important when energy policy affects households differently. Renewable energy measures are often beneficial, but they do not automatically benefit everyone in the same way. A subsidy for solar panels, for example, may mainly reach households that already have the money, roof space and time to participate. Other households may remain dependent on more expensive energy sources and risk falling further behind.
Despoina Kassandra Georgiadi, energy poverty researcher at TU Delft, explains:
“There is often an assumption that every renewable energy decision is automatically beneficial for everyone. But that is not always the case. If only those who can afford to participate in the energy transition benefit from it, others may be left with higher costs and fewer options. Digital Twins can help policy makers see these dynamics, identify who needs support most, and design interventions that make the transition fairer.”
Imagine a municipality has funding for a local solar panel subsidy. The obvious question is: where should the subsidy go? A Digital Twin can help explore which homes have suitable roof space, which already have PV installed, which households are most in need of support and how additional solar generation could affect the local grid.
In this way, scenario analysis can turn a long list of possible measures into a clearer set of priorities. It can help compare technical, economic and social effects. It can also make policy discussions more transparent, because maps, dashboards and indicators provide a shared language for technical experts, municipalities, energy coaches and citizens.
The Digital Twin will not decide what is fair. That remains a political and social question. But it can help make the consequences of different choices visible earlier.
Scenario analysis for local energy policy
The Digital Twin can help municipalities compare possible policy choices, such as where to support solar PV adoption or neighbourhood electrification. Different scenarios can be assessed against grid impact, affordability, energy poverty and local energy goals, making trade-offs easier to discuss.
Building trust in a complex system
The vision is powerful, but the work is not simple. A Digital Twin is only as useful as the data, assumptions and models behind it.
In practice, this means dealing with incomplete data, different software systems, changing site conditions and the challenge of making model results understandable to people who are not modelling experts. It also means working with many different stakeholders: the Municipality of Alkmaar, industrial partners, citizens, researchers and technology developers.
Trust is therefore as important as technical performance. Users need to understand what the Digital Twin can and cannot do. They need to know when results are based on live data, when they are based on forecasts and when they come from scenario assumptions. They also need tools that are developed with them, not only for them.
This is why the REFORMERS approach emphasises openness, modularity and reuse. The tools developed in WP5 are intended to become publicly available and open-source, supporting not only the flagship valley but also future replication valleys.
Within Work Package 5, this work brings together expertise from TU Delft, AIT, VUB, TNO, CERTH, CIRCE, EMPA and the Municipality of Alkmaar.
From ambitious concept to understandable system
The promise of the REFORMERS Digital Twin is not that it will predict the future perfectly or automate every decision. Its value is more practical: it can make complex energy systems visible, testable and discussable.
For an industrial site, that may mean better advice on how to use a battery. For residents, it may mean understanding how home batteries can support the local system. And for municipalities, it may mean exploring the consequences of electrification, grid congestion and energy poverty before choices become irreversible.
In that sense, the Digital Twin is becoming one of the key tools for turning Renewable Energy Valleys from ambitious concepts into systems that can be understood, operated and replicated.
Further reading
REFORMERS D5.2 — Energy data space for digital twins
REFORMERS D5.3 — Model lifecycle for digital twins
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