Pre-FID financial model
The financial model that reads your cost and yield scenarios directly, so the business case moves when the engineering does.
What Pre-FID does
Pre-FID is a project finance model for unsanctioned wind farms. Each scenario maps the investment profile, from construction programmes to cash flow, covering planning, CAPEX, OPEX, revenue, and financing.
Unlike static spreadsheets, our model pulls data directly from your CAPEX, OPEX, and AEP scenarios. Updating a foundation type triggers automatic recalculations for capital costs, installation timelines, and revenue profiles, showing the immediate impact on project returns.
Assumptions are managed through version-controlled, named scenarios. You can duplicate and compare sensitivity or financing cases instantly, replacing fragmented, confusing files with a single, auditable record.
Each model stores its own outputs, preventing accidental data overwrites. This allows multiple users to work on Pre-FID and M&A cases for the same asset simultaneously without interference.
Live · Demonstration project
17.7%
Equity IRR, with the debt sculpted to it
Yield down the side, capital cost across — twenty-five runs, not one answer
What you get with Pre-FID
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Driven by the engineering scenarios
CAPEX, OPEX and AEP results flow into the model as the cost and production lines. The business case is a view of the technical case rather than separate documents.
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Construction and taking-over programme
Project timing, turbine taking-over and commissioning profile drive the drawdown, the revenue ramp and the interest during construction period.
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Scenario management for assumptions
The same scenario tooling as the cost models: alter assumptions, duplicate scenarios and compare scenarios with side-by-side results.
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Financing and accounting
Debt sizing, letters of credit, interest, depreciation and the accounting treatment carried through to the statements, to support any queries about the investment case.
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Metric-driven decisions
Levelised cost of energy, net present value, internal rate of return and cover ratios over the project life, each traceable back to the inputs that produced it.
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Results that stay honest
Results are stamped against the inputs that produced them and marked stale when an input changes, so nobody can present a result that no longer matches the base assumptions.
Pre-FID in use
Drawn in the product's own interface, and every figure is real: they come from our live Demonstration project — a 288.75 MW floating wind farm in the central North Sea — and its Default Scenario, so anything shown here can be reproduced in front of you. No client or commercial data appears on this page.
Assumptions that know where they came from
The capex chapter. Capital cost, operating cost and energy yield are read from the scenarios modelled next door, not retyped — so a turbine change in CAPEX moves the return here without anyone copying a number.
Capex
General
How the capital build-up is grouped
£m · sums to 828.82| Turbine package | 448.41 | |
| Offshore BoP and export system | 414.08 | |
| Development and consenting | 30.04 | |
| Construction management and owner's costs | 28.63 | |
| Contingency | 25.00 | |
| Insurance and financing costs | 14.89 | |
| Grid / onshore connection | 3.45 |
The grey wells are the mirrored ones — the capital cost and the energy yield are read from the scenarios modelled next door, so a turbine change in CAPEX moves the return here without anyone copying a number.
The cash flow the decision is taken on
Cash available for debt service against the debt service it has to cover, with the resulting cover ratio on its own axis. The sculpting solver sets the repayment profile, and the model reports the ratio it actually achieved rather than the one it was aiming at.
Cash flow and cover, first six years of operation
£m per yearThe same years as numbers
£m unless stated| Measure | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|
| Generation, GWh | 438 | 1,197 | 1,197 | 1,197 | 1,197 | 1,197 |
| Revenue | 56.93 | 148.16 | 148.17 | 148.18 | 143.90 | 143.91 |
| Operating cost | 10.58 | 26.03 | 26.33 | 27.54 | 28.52 | 33.03 |
| CFADS | 46.45 | 119.92 | 116.77 | 113.86 | 108.59 | 104.05 |
| Debt service | 8.92 | 68.80 | 70.67 | 68.90 | 65.72 | 62.97 |
| Distributions to equity | 0.00 | 83.66 | 47.03 | 46.59 | 44.30 | 42.37 |
The two variables the committee will actually push on
Equity return across energy yield and capital cost together, both moved in the same run. The sequential tint encodes the value — the reserved red, amber and green are never used as decoration, because they mean something specific everywhere else in the product.
Equity IRR sensitivity
| Energy yield ↓ · Capital cost → | CAPEX −20% | CAPEX −10% | Base case | CAPEX +10% | CAPEX +20% |
|---|---|---|---|---|---|
| AEP +10% | 56.0% | 32.9% | 22.7% | 16.9% | 13.2% |
| AEP +5% | 52.1% | 29.9% | 20.3% | 15.0% | 11.5% |
| Base case | 48.0% | 26.7% | 17.8% | 12.9% | 9.7% |
| AEP −5% | 43.5% | 23.3% | 15.2% | 10.7% | 7.8% |
| AEP −10% | 38.4% | 19.7% | 12.4% | 8.4% | 5.8% |
The centre cell reads 17.8% against the run's own 17.66%. The grid shifts the base cash flow by the capital cost and revenue deltas with the debt schedule held where the base case put it, so it answers "what if this project cost more" rather than "what if we had financed a different project" — and the small gap at the centre is the price of that being an honest approximation rather than a hidden re-solve.
What the LCoE is made of
Present values at 6.0%| PV of capital cost | £757.03m |
| PV of operating cost | £384.62m |
| PV of decommissioning | £12.63m |
| PV of production | 13,254 GWh |
| Levelised cost of energy | £87.09 / MWh |
What the run told us about itself
3 notes returnedA model that knows which of its own simplifications are still in place is worth more than one that presents every number with the same confidence. These notes come back with the results and travel with the export.
See it on your own project
Book a demo and we will walk through the module with your numbers, not ours.
More of the toolkit
M&A
Value an operating or consented asset properly: transaction structure, debt, tax, allowances and sensitivities in one model.
Turbine Technical Due Diligence
Ten structured tools for turbine diligence, each answer tied to the document it came from.
Custom data sources
One library of reference data behind every model, so two scenarios can never mistakenly use different vessel day rates.