Documentation
Everything you need to go from a blank canvas to a solved, downloadable model. Docs are the support channel: if something here is unclear or missing, that's a bug; tell us via the contact form.
Quickstart
Build a minimal system and solve it in under ten minutes.
- Open the app. Launch Levelised, no account needed to build and solve.
- Add components. Drag a generator, a load and a bus onto the canvas and connect them.
- Set the load and costs. Give the load a demand profile (or a flat MW figure) and the generator a capital and operating cost.
- Solve. Hit Solve, and the optimiser sizes and dispatches the system across 8,760 hourly snapshots.
- Read the results. Costs, energy balances and the Sankey view.
- Save and download. Create a free account to save your project and export it: project file, PyPSA netCDF, or results CSV. A runnable Python script export is available on the paid tier.
Video walkthrough
Two minutes through the example microgrid, covering the same ground as the in-app guided tour: buses, weather-driven renewables, links, solving, and the levelised cost of electricity.
Worked examples
One complete, solved model for each sector we serve. Each link opens the example straight in the app, no account needed. If it's your first visit you'll be offered a short guided tour first to get oriented; the tour is also in the app's main menu whenever you want it later.
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Renewable Energy
A small wind + solar + battery microgrid with gas backup: the example the guided tour walks through.
Open in the app → -
Data Centre
A grid-connected data centre: buy from a bid-stack grid or build on-site wind, solar, battery and gas.
Open in the app → -
Mining & Metal Processing
An off-grid mine with electricity and process steam: gas cogeneration, a boiler and a heat pump.
Open in the app → -
Renewable Fuels
An islanded green-methanol plant: electrolysis, direct air capture and methanolisation, with storage at every stage.
Open in the app →
Reference
Levelised is built on PyPSA and uses the same component terminology throughout (Buses, Generators, Links, Stores, Loads), so if you want to go deeper on how a component behaves or how the optimisation is formulated, the PyPSA documentation is a useful companion to what's here.