Decision-making toolkit

Annual energy production

Energy yield that shares its inputs with CAPEX and OPEX, so revenue, production and losses are deterministically linked.

Overview

What AEP does

AEP is calculated using the same scenario as your cost models. By linking the turbine, layout, and resource inputs directly to CAPEX, we eliminate discrepancies between financial and yield projections. You never need to re-key data, removing a major source of human error.

Gross yield derived directly from the site's ERA5 wind record and turbine power curve. Every variable, including air density and distribution parameters, is fully visible. Results include the expected capacity factor.

Losses are applied through a transparent chain of wake, electrical, availability, environmental, and curtailment factors. Every parameter is visible and adjustable and the resulting yield is a clear gross and net GWh per year.

Live · Demonstration project

1,317GWh/yr

Net energy yield, P50

The library's power curve against this site's own wind — gross, then twenty named losses

Top features

What you get with AEP

  1. Yield linked to project scenarios

    The turbine, layout and site conditions form the basis of the energy yield calculation. There is no need to manually shift data; the energy yield is calculated instantly, on platform.

  2. Gross yield from the wind record

    Computed from the Project ERA5 node's wind distribution and turbine power curve. Air density, distribution parameters and the curve itself are all inputs you can inspect.

  3. Power curves from the library

    Turbine power and thrust curves come from the shared custom data source library, with provenance attached, so every scenario uses a shared, customisable data set.

  4. A visible loss chain

    Wake, electrical, availability, environmental and curtailment losses are all applied and can be customised to your project and scenarios.

  5. Data is checked on input

    Capacity factor is bounded by a ceiling derived from rated power and hours in the year, so an implausible yield is flagged when data is entered, to ensure calculation validity.

  6. Feeds revenue directly

    Net yield flows into the OPEX, Pre-FID and M&A financial models, so a change in the yield case automatically moves into the OPEX calculations and the financial models.

Illustrative examples

AEP 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.

Illustrative

The landing page is one number and what produced it

AEP opens on its Lite view: the handful of inputs that actually move the answer on the left, the answer on the right. The values that belong to the capital model are shown locked with a link back to it, so the yield case and the cost case cannot quietly disagree about how many turbines there are.

Project Demonstration project Scenario Default Scenario Project team
Wind turbine Losses and availability Wind farm Wind loader Energy yield

Core Inputs

Turbine

WTG Model Generic Direct Drive 11.55MW

Update via CAPEX

Rated Power 11.55 MW

Update via CAPEX

Wind farm

No of WTGs 25

Update via CAPEX

Total Installed Capacity 288.75 MW

Update via CAPEX

Wind loader

Year Start 2001

Year End 2025

Energy yield / wake analysis

Use Global Wind Atlas Scaling (GB only)
Run Blockage Model
Run Time-Series Model
Export PyWake wake maps

Headline Results

Completed: 20/09/2026, 15:52:23

P50 (net AEP)

1,317

GWh/yr

Gross energy yield 1,485 GWh

Capacity factor, net P50 52.1%

Internal wake loss 4.07%

Engine and method PyWake 2.6.20 · frequency_noj

▸ Energy breakdown

Illustrative

The power curve and the wind, on one chart

The Generic Direct Drive 11.55MW curve comes from the shared library with its provenance attached; the distribution is the twelve-sector Weibull fitted to this site's own ERA5 record. Gross yield is computed from the two — never inherited from somebody else's assessment.

Project Demonstration project Scenario Default Scenario Project team
Wind turbine Losses and availability Wind farm Wind loader Energy yield

Power curve and wind speed distribution

From library · Turbines (WTG) PyWake 2.6.20 · frequency_noj
Power curve and wind speed distribution 0 3 6 9 12 Rated, 16 m/s Cut-out, 28 m/s 0510152025 m/s
Power curve, Generic Direct Drive 11.55MW — 11.55 MW, 236 m rotor Wind speed frequency — 12 sectors, mean 10.4 m/s at hub height

Sector wind climate

Weibull k and A per 30° sector
Sector 30°60°90°120°150°180°210°240°270°300°330°
Frequency, % 7.93.83.04.27.88.910.612.011.39.510.010.8
Scale A, m/s 10.18.17.910.513.012.212.112.812.812.211.411.5
Shape k 2.181.991.851.922.172.282.282.262.242.122.102.18

The prevailing sector is 210°, which is also the direction the array is oriented on — that relationship is what the wake model is resolving.

Illustrative

Every loss between gross and net, in the open

The energy breakdown behind the headline. Twenty loss steps applied in order, each one an input you can see, challenge and change, with the energy remaining after each step beside it. The steps set to 1.000 are not hidden — they are there, answered, and currently costing nothing.

Project Demonstration project Scenario Default Scenario Project team
CAPEX OPEX AEP M&A Pre-FID WOMBAT

AEP Results

View a single scenario or compare up to 3 scenarios side-by-side.

Default Scenario Energy yield breakdown

12 further steps at 1.000

Gross yield

1,485

Net P50

1,317

Capacity factor

52.1%

Total losses

11.35%

Step Factor Energy remaining, GWh Share of gross
Gross energy yield 1,485.3
1a Turbine availability 0.96000 1,425.9
1b BoP availability 0.99500 1,418.7
1c Grid availability 0.99700 1,414.5
2a Internal wake 0.95931 1,356.9
3a Electrical efficiency 0.98500 1,336.6
4a Sub-optimal performance 0.99500 1,329.9
4c Site-specific power curve adjustment 0.99500 1,323.2
6b Degradation 0.99500 1,316.6
Net energy yield (P50) 0.88645 1,316.6
Layout 25 WTGs · 6 rows · 11.25 RD downwind, 7.5 RD crosswind · 210°

Wake maps exported for inspection 8 directions at 9 m/s

Input fingerprint, so a rerun can be proved identical SHA-256 5ab4399d…95ab20b4

See it on your own project

Book a demo and we will walk through the module with your numbers, not ours.

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