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Energy Company

Production-ising a Digital Model for Financial Analysis of Hydrogen Plants.

Energy
TagsEnergyAI Factories
Energy
TagsEnergyAI Factories

This client is racing to scale the green molecules that will power tomorrow's grid. Their next big bet: a large-scale green hydrogen plant. Before a single foundation was poured, they needed to know if the numbers would hold up over decades of market swings. So ML6 built a digital twin that turns a high-stakes "build or no-build" call into a data-backed decision.

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Catch up’ quickly

How do you commit hundreds of millions to a green hydrogen plant when renewable power is intermittent, supply chains are complex, and regulation keeps shifting? This client partnered with ML6 to build a Proof of Value (PoV), a financial simulation engine that models the plant's entire value chain, from power purchase agreements to electrolyser degradation, and stress-tests it against decades of possible futures. The result: a well-substantiated CAPEX, OPEX and ROI forecast that gave leadership the confidence to move from blueprint to build.

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About the Company

This client is a major player in the transition to sustainable energy, with green molecules such as hydrogen at the center of its growth strategy. Large-scale green hydrogen production is still a young, capital-intensive frontier: plants take years to plan and decades to pay back, and few organisations have built one at this scale before. That's exactly why leadership wanted more than a spreadsheet before committing; they wanted a rigorous, data-driven view of how the plant would actually perform once it was running.

Impact

We simulated decades of scenarios before a single euro of CAPEX would be committed. Financial blind spots eliminated across the full hydrogen value chain.

  • A green light on a green molecule

    The simulation gave leadership the confidence to move forward with construction of the plant.

  • Risk made visible, not just felt

    Energy volatility and supply chain costs, previously gut-feel risks, became quantified, modellable variables.

  • A shared source of truth

    The engine gave finance, engineering and leadership one model to align around, instead of competing spreadsheets and assumptions.

green hydrogen

Challenge

This client was standing at one of the biggest crossroads in its growth strategy, and it needed to get the call right.

  • Capital at risk, patience required

    A green hydrogen plant demands massive upfront investment with a payback horizon measured in decades, leaving little room for a wrong call.

  • A complex, moving supply chain

    Getting hydrogen to end consumers involves logistics and market dynamics that are far from settled, adding another layer of uncertainty to any forecast.

  • Regulatory shifts on the horizon

    Policy and subsidy regimes for green hydrogen are still evolving, and any credible model has to flex with them.

  • No margin for financial blind spots

    Before breaking ground on a pioneering asset, this client needed certainty that its business case would hold up, not just in the best-case scenario, but across the plausible range of futures.

Solution

ML6 built a simulation engine designed to be the definitive decision-support tool for the plant's business case. Rather than a static spreadsheet, it is a living digital twin of the plant's financial future.

Our simulation engine models the parts of the hydrogen value chain that matter most to the investment case, from Power Purchase Agreements to electrolyser degradation over time.

The technology behind project

While the conversation with leadership stayed grounded in euros and risk, the engine underneath is built for rigour.

  • Value-chain modelling

    Purpose-built financial and physical models covering PPAs, electrolyser performance and degradation, and downstream logistics.

  • Scenario and sensitivity simulation

    The engine runs the plant's economics across many market and regulatory scenarios rather than a single forecast line.

  • Data-grounded assumptions

    Every input was validated against this client's own operational data and domain experts, not industry rules of thumb.

  • Built for a Proof of Value

    The engine was scoped and delivered as a focused PoV, fast enough to inform a real, time-bound investment decision.

Results

  • A defensible business case

    This client could finally put numbers, not assumptions, behind the plant's CAPEX, OPEX and ROI.

  • Uncertainty, quantified

    The interplay between energy volatility and supply chain costs, previously two separate risks, was modelled together for the first time.

  • A decision, enabled

    Armed with the simulation's insights, this client was enabled to make the investment decision and proceed.

The Collaboration

The simulation engine was never going to be built from the outside looking in. ML6's engineers worked hand in hand with this client's own domain experts throughout, pairing deep modelling expertise with the operational knowledge only the client's team had. This client's experts validated every assumption that went into the engine, while ML6 focused on turning that knowledge into a rigorous, decision-ready simulation. What came out of that collaboration wasn't just a model; it was a shared, defensible view of the plant's future that leadership could act on with confidence.

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Benjamin Praats 1-1
Benjamin PraatsClient Executive

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Benjamin Praats 1-1
Benjamin PraatsClient Executive