Most price-curve providers hand you an output and ask you to trust it. PowerLens is built the other way round: an open model, assumptions you set yourself, public data cited source by source, and the model's own weaknesses stated up front. If a number surprises you, you should be able to find out why.
The PyPSA-Eur dispatch formulation used across European system planning, reimplemented in NumPy/SciPy and solved with the open-source HiGHS solver — not an engine you have to take on faith.
Commodity prices, demand, capacity and per-technology build-out are all live controls. You set them, you change them, the curve recomputes — nothing is hard-wired out of reach.
Calibrated only on public datasets — ENTSO-E, IRENA, Ember, Eurostat, TYNDP. No proprietary feed sits between you and the result, and every source is named below.
Where the model is weak — its ten-zone wholesale-only scope, its known biases, its in-sample calibration — is written down and handed to you, not discovered in month three.
Everything the model is calibrated on is public and traceable. Here are the sources, with no hidden dataset and nothing you cannot go and check yourself.
The complete methodology note and the assumptions-and-sources register — the dispatch formulation, the marginal-cost stack, the 2024 backtest against ENTSO-E, every calibration choice and every data point — ship with every engagement and are available inside the app. We will walk you through any number that matters to your decision.
Book a 30-minute demo and we'll run your market live — assumptions visible, sources cited, limitations included.