An independent public score for green heavy-asset projects, derived from public evidence by a published method. Not advice. Not a credit rating.
Edition 0 · fictional projects and companies · method on public review| # | Project & developer | Technology | Capacity | Country | Assay | Band | Weakest public signal |
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A band is a statement about likelihood, not quality. A Band E project is not a bad project — it is an early one, and should be valued as an option rather than an asset.
Ten levels decide whether a green heavy asset ever gets built. The Index scores the five that can be observed from public evidence — grid queue positions, consent decisions, auction and tender results, land and seabed awards, and announced financing. The other five require the developer's own data.
Grid and consent together carry 58% of the public score. That is deliberate. Interconnection delay and permitting are what actually kill projects — median time from grid request to operation in the United States has risen from under two years in 2008 to nearly five years in 2023, and only around 19% of projects that entered the queue between 2000 and 2018 had reached commercial operation by the end of 2023.
Public evidence can show that a project has a grid offer. It cannot show whether the energy yield assessment is sound, whether the cost estimate has been tested, or whether the execution plan survives contact with a vessel market. Five of the ten levels are invisible from outside.
A project therefore cannot be rated Band A from public data alone. The highest attainable public score is 72 — upper Band B. A full score requires the developer to submit evidence against all ten levels.
Public evidence is thin, and the method scores only what it can see. If an input is wrong or out of date, the correction is evidence. Submissions are reviewed, factual inputs corrected within ten working days, and the correction logged.
Submit evidence by email Or write directly: gt7753@gmail.com · First full assessment free · Method published in full aboveEdition 0 is a methodology demonstration. Every project, developer and score on this page is fictional. The companies named do not exist. Any resemblance to a real organisation or project is coincidental and unintended. The scores describe nothing real. This edition exists to publish the method in full and invite scrutiny of it before any real data is scored.
Nothing on this page is advice, a recommendation, or an assessment of creditworthiness. Scores are not credit ratings and are not prepared for the purpose of any investment, lending or procurement decision. No duty of care is assumed to any reader. Anyone making a decision about a project must rely on their own enquiries and professional advisers, not on this index.
A score is an opinion, produced by the published method on this page, from facts in the public record. Every score shows the inputs it was derived from. Where an input is drawn from a third-party dataset, that dataset's own limitations apply: the NESO TEC register, for example, is published "as is" and NESO notes that capacity is presented in aggregate across stages and technology types, which may result in duplicate entries.
Any organisation whose project appears in a future real-data edition may submit evidence that an input is wrong or out of date. Corrections to factual inputs are made within ten working days of receipt, the score is recomputed, and the correction is recorded in the edition log. Disputes about the method itself are published with the method.
Evidence submissions, corrections and general enquiries: gt7753@gmail.com. Replies within two working days.
Supported by National Energy SO Open Data. This index is not official, is not produced by or in association with NESO or any regulator, and is not endorsed by any of them. Industry statistics quoted on this page — queue completion rates and connection timelines — are drawn from Lawrence Berkeley National Laboratory's Queued Up research. The band-to-probability mapping is calibrated against illustrative stage-conversion figures, not a published dataset, and is labelled as such.