No room for blind spots: Why Europe needs smarter energy modeling now

From the war in Ukraine to climate extremes, Europe's energy future depends on more than new infrastructure: it needs smarter, open and shared tools to simulate uncertainty, coordinate responses, and avoid costly mistakes. "If we want a common future, we need a common modeling infrastructure," experts warn.

When Russia invaded Ukraine and gas supplies were suddenly cut off, Europe scrambled to respond. Emergency plans were triggered, older energy infrastructure was brought back online, and energy prices soared. But every rushed decision exposed a deeper problem: most energy planning tools weren't designed to handle such disruption.

"We have recently been exposed to unexpected turnarounds, such as the 2022 full-scale Russian invasion into Ukraine and the turmoil over gas imports. Such events show that short-term changes have to be reflected last but not least in very fast modeling too, and not only mid- and long-term planning," notes Susanne Nies, Project Lead Green Deal Ukraїna at Helmholtz Zentrum Berlin.

"Besides Ukraine—she adds—there are factors such as climate change, decentralization and electrification that require a different type of modeling." In an increasingly volatile world—from climate extremes to geopolitical ruptures—resilience starts with one often overlooked ingredient: data. Data accessibility, and data quality. Or rather, how we simulate and understand it.

"That's been the real battle in recent years," Nies continues. "People and countries need to have access to data, and to open-source models, so that they can develop and play around with their own scenarios."

Behind every national plan, grid forecast or hydrogen strategy lies a simulation—a model trying to predict what might happen under different futures. But too often, these models are like black boxes: complex systems with hidden assumptions, inaccessible code, and unclear limitations. And yet, they form the backbone of energy policy.

A lot has been done at the EU level to strengthen long-term planning—for example, through the governance regulation and the obligation to develop National Energy and Climate Plans (NECPs, which outline how each country intends to meet EU climate targets) or the better and better consultation of the Ten-Year Network Development Plan (TYNDP, a long-term scenario-based planning tool developed by ENTSO-E, the European Network of Electricity Transmission Operators).

But these efforts still rely on heterogeneous national models—and more can be done to harmonize approaches and improve cross-border integration.

"There are great opportunities today, such as AI, big data, and new ways of gathering data and modeling. We need a pan-European approach for near to real-time availability of energy and climate data. And possibly a European Energy Agency that owns such data and provides access to them," continues Nies.

Wolfram Sparber, director at Eurac Research's Institute for Renewable Energy, adds, "In many cases, decisions are still based on outdated scenarios or siloed models. That may work locally, but it's dangerous when applied to interconnected systems."

"Add to this the rise of distributed renewables, electric vehicles and flexible demand—and it's clear why legacy tools are no longer enough. We need modeling tools that can handle multiple systems at once, with high temporal resolution and the ability to simulate uncertainty," Sparber says. "Only then can we see the full picture and understand the real impact of our choices."

That's where initiatives like Mopo come in. Coordinated by the VTT Technical Research Center of Finland, the project aims to change how we build, use and share energy models.

"The war in Ukraine—as well as events like the 2025 Iberian Peninsula blackout—highlighted the need for comprehensive and flexible modeling tools," says its coordinator, Niina Helistö. "We started with one clear goal: to make modeling more open, modular and user-friendly."

Instead of a single monolithic tool, the consortium is assembling an open-source framework composed of three main elements: data processing, workflow management, and energy system planning tools—all designed to interact, adapt, and evolve. From grid flexibility to building retrofits, users can create customized simulations based on transparent assumptions.

"It's compatible with other models and tools, and it features a graphical user interface where people can build workflows and link models in a very intuitive way," adds Helistö. "We co-design with real users—engineers, planners, researchers, local authorities—and incorporate stochastic approaches to address uncertainty."

This vision aligns with a wider movement for open science and digital sovereignty. As Wolfram Sparber explains, "Models should not be the privilege of a few institutions. They are critical infrastructure—like maps or weather forecasts."

Why does this matter? Because behind the numbers lie real investments, real risks, and real communities. "If your model underestimates a heat wave or overestimates storage capacity, you might end up with power outages or stranded assets," explains Helistö.

"It's not an academic problem—it's a governance one." By focusing on open source and usability, Mopo sets a new standard: transparent, replicable, and adaptable across scales—from local to continental.

This approach is currently being tested through three demonstration case studies. One of them focuses on an industrial cluster located between Belgium and the Netherlands, where Mopo's tools are used to simulate complex regional decarbonization strategies.

Other applications include scenarios at pan-European scale and regional planning in the Baltic countries, showing how integrated modeling can support both system-wide coordination and local decision-making.

Susanne Nies explains that "Weak modeling capacity can delay renewable deployment, misguide funding, or deepen regional inequalities. It's a silent bottleneck in the energy transition." This is also true for other sectors, like electric mobility.

"EVs are not just cars—they form part of a broader system involving charging networks, demand peaks and battery reuse," says Sparber. "Modeling can help us see synergies, but only if we simulate across sectors and scales."

In the past 20 years, the European Commission has improved the governance regulation (2019 Clean Energy Package) in line with Green Deal objectives. But if the EU truly wants to reshape the landscape—turn energy modeling into a shared, accessible and future-proof infrastructure—the shift is not just technical, it's political.

First is transparency. "The European Commission needs to provide the highest possible data quality, data availability (close to real time), as well as data accessibility, to ensure the modeling of multiple plausible futures is based on high quality information," says Susanne Nies. "Innovative ways of data gathering, such as behavioral should be added, at least for cross-checking."

Second: access and skills. "Tools should be usable by more than just elite institutions—adds Wolfram Sparber—at least in a simplified version. That means better interfaces, better documentation and training programs for public bodies." It's just as Mopo's kit: "The whole framework is compatible with other models and tools," confirms Niina Helistö.

"And offers tutorials, webinars and course material that make it even easier to use the tools." Finally, governance and funding. "We need EU-level initiatives that treat modeling as a shared digital infrastructure, ensuring public long-term support and funding for this open-source tool maintenance," warns Helistö. "This requires real funding and consistent work."

And there's another dimension: international solidarity. "Ukraine is a test case," says Nies. "They're rebuilding their energy system while under attack. But they lack access to many of the tools used in the EU. That's why interoperability and openness matter. If we want a common future, we need a common modeling infrastructure."

In a time of war, climate urgency and global shifts, knowing where we're going—and how—is no longer just a strategy. It's essential. Blind spots are simply not an option: our tools must be robust, inclusive, and shared.

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