Design an energy system. Optimise it properly. Free.
Levelised is a techno-economic optimiser that runs in your browser. Drag generators, storage, loads and links onto a canvas (electricity, heat, hydrogen, water, any energy or mass flow) and solve a full year at hourly resolution with a real optimisation engine, built on the open-source PyPSA framework.
Built for the decisions in your sector
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Data centres
Time-to-power, hourly carbon-free energy commitments, and what a grid, on-site or hybrid power strategy actually costs per MWh.
Explore data centres → -
Mining & metals
Off-grid and remote power, diesel displacement, hybrid plant design, and process heat and water in the same optimisation.
Explore mining & metals → -
Renewable energy
Storage sizing, hybrid plant design, co-location with large loads, and what a plant can credibly commit to under a PPA.
Explore renewable energy → -
Renewable fuels
Green hydrogen, ammonia and methanol chains: electrolyser utilisation, storage buffers, and the real cost per tonne.
Explore renewable fuels →
How it works
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Build
Lay out your system on the canvas: generators, storage, loads and the links between them. Any carrier (power, heat, hydrogen, water) in one connected model.
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Solve
Optimise capacity and dispatch over 8,760 hourly snapshots, a full year, using the open-source PyPSA framework and the HiGHS solver. Least-cost sizing and operation, not a spreadsheet approximation.
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Download
Create a free account to save your work and download the project file, a PyPSA netCDF, or results as CSV. Your model is never locked in: a runnable Python script export is available on the paid tier.
Free today. More for teams that need it.
Building and solving is free, with no account needed until you want to save or download. The advanced layers below are the paid tier (see what the paid features do), and if they matter to you, tell us and we'll be in touch.
| Capability | Free | Paid |
|---|---|---|
| Canvas modelling: generators, storage, loads, links, any carrier | Included | Included |
| Hourly optimisation over a full year (8,760 snapshots) | Included | Included |
| Components per model | Up to 20 | Up to 500 |
| Snapshots per solve | 8,760 (one hourly year) | Up to 175,200 (multi-period) |
| Solves per day | 10 | 100 |
| Solve time limit | 5 minutes | 15 minutes |
| Downloads: project file, PyPSA netCDF, results CSV | With a free account | Included |
| Cloud saves of solved results | Statistics level | Full hourly time series |
| Runnable Python script export | — | Included |
| Scenario management | — | Included |
| Multi-period analysis | — | Included |
| Custom optimisation constraints and objectives | — | Included |
| Linked cash-flow / finance model | — | Included |