Open, 16 days to go
Estimate the sun
Given the weather that happened, how much solar power came onto Great Britain's grid in each half-hour? The grid balances on this number.
- Scored by
- MAE
- Lower is better
- Score to beat
- 700.405
- Train-period mean capacity factor for that month and half-hour × installed capacity
- Entrants
- 9
- 5 uploads a day
- Closes
- 29 Nov
- 23:59 UTC
Cash prizes for the top three. Amounts are announced on Monday 2 November 2026 and paid after the audit. Prizes need a beaten baseline, a filed solution report and a reproducible pipeline, see the rules and terms.
Overview
The problem. Great Britain has more than 20 GW of solar panels and almost none of them are metered by the grid. Every half-hour the system operator balances supply against a national estimate of solar output; the better the estimate, the less gas is burned holding reserve. PV_Live, from Sheffield Solar, is that estimate. Your job is the same one: given the weather that happened at twelve points across the country and the installed capacity at the time, estimate national solar generation in megawatts for every half-hour of the test year.
The data. Train: January 2022 to June 2025, 61,296 half-hours. Test: July 2025 to June 2026, 17,520 half-hours. Each row has the timestamp, PV_Live's installed capacity at the time, and NASA POWER hourly weather at twelve points: all-sky and clear-sky irradiance, temperature, cloud amount, wind and humidity. The target is PV_Live's national generation figure. Compute the sun's position from the timestamp yourself.
Scoring. Mean absolute error in megawatts, lower is better. Whole days of the test year are public (30%) or private (70%) so both splits cover every season; your standing is the private split.
Baselines (private split). Predicting the train-period mean capacity factor for that month and half-hour, times the day's capacity: 700 MW. A default gradient-boosted tree on the shipped columns: 279 MW. Beat the first for the badge; beat the second to be in the game.
Why it matters. Every megawatt the estimate misses is a megawatt of reserve someone pays for or a curtailment someone loses. The same skill runs solar forecasting, battery dispatch and grid planning everywhere in the world.
Marking rubric
Exactly how your points are worked out. Mark your own work against it before you file.
Out of 100 final points, 70 come from your score on the hidden test rows and 30 from your solution report, marked against the rubric below.
The metric
70 points
Scored with MAE (lower is better) on the private 70% of the test rows, which nobody sees until results. Your rank there becomes your points: first place earns the full 70, last place earns 0, and everyone between is spaced evenly by rank.
A score that does not beat the train-period mean capacity factor for that month and half-hour × installed capacity earns 0, whatever its rank. Ranks, not raw scores, so one runaway entry cannot squash the rest of the field.
points = 70 × (1 − (rank − 1) ÷ (entrants − 1))For example, 3rd of 21: 70 × (1 − 2 ÷ 20) = 63 points.
The report
30 points, 6 per criterion
Five criteria, equal weight. Each is marked at one of four levels, and every level is defined below, so you can mark your own draft before you file it. Three judges mark blind and independently; each criterion takes the middle mark of the three.
-
Problem framing and impact
6 pointsWho uses this estimate, what decision changes if it is better, and what an error costs them.
- 0 · Absent0 pts
- No statement of who uses the estimate or why.
- 1 · Developing2 pts
- Names the use but not the decision it changes.
- 2 · Solid4 pts
- States the decision, the user and what a given error costs them.
- 3 · Exemplary6 pts
- As 2, and quantifies the value of the improvement over the baseline in the user’s terms.
-
Data understanding and validation
6 pointsA validation design that mirrors the test split, with leakage risks named and handled.
- 0 · Absent0 pts
- No validation design, or validates on the public leaderboard.
- 1 · Developing2 pts
- Holds out data but the split can leak: random rows in a time series, or the same entity on both sides.
- 2 · Solid4 pts
- A split that mirrors the test split; leakage risks named and handled.
- 3 · Exemplary6 pts
- As 2, with evidence the local validation tracks the public score, and a data finding that changed the approach.
-
Method and rigour
6 pointsChoices justified, compared against both pinned baselines, failures reported honestly.
- 0 · Absent0 pts
- No description, or a method with no justification.
- 1 · Developing2 pts
- A reasonable method described, no comparison.
- 2 · Solid4 pts
- Choices justified, compared against both pinned baselines, at least one thing that failed reported honestly.
- 3 · Exemplary6 pts
- As 2, with an ablation or sensitivity check that shows which parts matter.
-
Error analysis and limitations
6 pointsWhere the model is wrong and why, and what would go wrong if someone deployed it.
- 0 · Absent0 pts
- No error analysis at all.
- 1 · Developing2 pts
- Says errors exist, no pattern.
- 2 · Solid4 pts
- Shows where the model fails (segments, conditions) and gives a plausible reason.
- 3 · Exemplary6 pts
- As 2, and states the deployment risks: who is harmed if it is over-trusted, what would have to be monitored.
-
Reproducibility and clarity
6 pointsCode, environment and steps a reader could run; prose that is clear and within length.
- 0 · Absent0 pts
- No code, or steps that cannot be followed.
- 1 · Developing2 pts
- Code linked but steps incomplete or environment unstated.
- 2 · Solid4 pts
- Code, environment and steps that a reader could run; prose is clear and within length.
- 3 · Exemplary6 pts
- As 2, with fixed seeds, a one-command run, and results that match the report.
If two judges are more than one level apart on a criterion, a person marks it instead. Judge prompts, model ids and calibration figures are published with the results.
Medals and prizes
- Final rank is by total points. Ties go to the better metric rank, then to whoever reached their score first.
- With five or more entrants: gold for the top 10%, silver for the next 20%, bronze for the next 30%.
- Every medal and prize needs a score that beats the baseline and a filed report.
- At least the top ten are audited: we re-run your code from train.csv and the result has to match.
The full rules and terms apply to every entry.
Submission format
Two things to hand in: a predictions file, scored automatically, and a report, marked against the rubric.
Your predictions, as a CSV
- Header
id,generation_mw. Column order does not matter; extra columns are ignored.- Rows
- 17,520 rows, one per id in test.csv. A missing id rejects the file and tells you which.
- generation_mw
- A number. Decimals are fine; no units, no thousands separators.
- File
- UTF-8, comma separated, up to 10 MB. sample_submission.csv is a valid starting point.
- Limits
- 5 scored uploads a day (resets 00:00 UTC). A file that fails these checks is rejected with the reason and does not use one. Pick up to 2 for final scoring; pick none and your best public score is used.
Your solution report
Written in the editor on this page, in Markdown, 600 to 1,500 words. Use these five headings, in this order; each one maps to a rubric criterion.
- 1
## The problem and who it serves
What decision changes if this estimate is better, for whom, and what an error costs them.
- 2
## Data and validation
What you found in the data, how you built your own validation, what could leak and how you avoided it.
- 3
## Method
What you built and why, what you tried that did not work, how it compares with the two pinned baselines.
- 4
## Error analysis and limitations
Where the model is wrong and why; the risks if someone deployed it: fairness, safety, over-trust.
- 5
## Reproducibility
Link to the code, the environment, the exact steps to regenerate your predictions from train.csv.
Code link, required
A public repository or notebook URL. The audit runs it from train.csv to regenerate your predictions.
AI use, declared
- Human: no AI assistance
- AI-assisted: I used AI tools and made the decisions
- Autonomous: an agent produced the submission
Save a draft as often as you like. The panel marks what is there at close; a report counts as filed once it is submitted or reaches 600 words.
Leaderboard
9 entrants, best public score each. The baseline and our reference model are pinned where their scores fall.
| Rank | Entrant | Uploads | Best score |
|---|---|---|---|
| 1 | dhruval | 8 | 134.313 |
| 2 | Jiahao Cao | 7 | 135.288 |
| 3 | bruno | 11 | 137.404 |
| 4 | MoFarina | 6 | 139.875 |
| 5 | Joty | 2 | 142.075 |
| 6 | ShinjiNakasaki | 1 | 147.062 |
| 7 | DanielSolaris | 1 | 174.031 |
| 8 | AlexCChristou | 1 | 175.570 |
| Default gradient-boosted tree on the shipped weather, capacity and the calendarour reference model | 279.183 | ||
| Train-period mean capacity factor for that month and half-hour × installed capacitybaseline to beat | 700.405 |
Scored on the public 30% of the test rows while the competition runs. Final standings use the other 70%, so a public lead is not a final one. The two reference rows are scored on those final rows.
Data
| Column | What it holds |
|---|---|
id | Row id (one per half-hour). Use it in your submission. |
datetime_utc | Start of the half-hour, UTC. Derive hour, day of year, sun position and daylight-saving from it yourself. |
installed_capacity_mwp | GB installed PV capacity in MWp at that time (PV_Live's estimate). It grows through the window. |
<point>_ghi | All-sky surface shortwave downward irradiance for that hour at the point, Wh/m² (NASA POWER). Twelve points: london, birmingham, manchester, leeds, bristol, norwich, southampton, plymouth, cardiff, newcastle, glasgow, edinburgh. |
<point>_clearsky | Clear-sky irradiance for the same hour, Wh/m², what the sun would give with no cloud. |
<point>_temp_c | Air temperature at 2 m, °C. |
<point>_cloud_pct | Cloud amount, %. |
<point>_wind_ms | Wind speed at 10 m, m/s. |
<point>_rh_pct | Relative humidity at 2 m, %. |
generation_mw predict this | Target. GB solar generation in MW for the half-hour, PV_Live's national estimate (train only). |
Sign in to download train.csv, test.csv and sample_submission.csv.
Sources and licences
- PV_Live, Sheffield Solar, GB national half-hourly PV outturn (pes 0) with installed capacity, Creative Commons Attribution 4.0 International (CC BY 4.0), retrieved 2026-09-21
PV_Live by Sheffield Solar, University of Sheffield, CC BY 4.0. https://www.solar.sheffield.ac.uk/pvlive/
- NASA POWER hourly meteorology and solar irradiance at twelve GB points (MERRA-2 / CERES SYN1deg), NASA Earth-science data: full and open sharing, no restrictions on use (US government work), retrieved 2026-09-21
Data obtained from the NASA Langley Research Center POWER Project, funded through the NASA Earth Science Directorate Applied Science Program.
Split. January 2022 to June 2025 is train; July 2025 to June 2026 is test. Within the test year, whole days are public (30%) or private (70%) by a hash of the date, so both splits cover every season and no half-hour has a neighbour in the other split.
Changes made. PV_Live half-hours joined to the NASA POWER hour that contains them (both half-hours of an hour carry that hour's weather); NASA missing values (-999) blanked; rows shuffled and given opaque ids; the target removed from the test file.
Withheld. Nothing beyond the target for the test year.
Rows: train 61,296, test 17,520 (public 5,280, private 12,240).
Artefact audit passed
- No duplicate rows across train and test. 0 of 17520 test rows have an identical feature row in train
- 1-NN does not beat the honest model. 1-NN mae 483.8332 vs honest 282.4693
- No single feature encodes the target. strongest |corr| 0.954 (birmingham_ghi)
- Row order is uncorrelated with the target. spearman(row index, target) = 0.006
- The id does not encode the target. spearman(id number, target) = 0.004
Half-hourly weather does not exist in NASA POWER; the hourly value is repeated for both half-hours. The datetime is the feature the sun's position hangs on, compute solar elevation from it.
Timeline
OpensMon, 5 Oct 2026(done)
Data released; uploads accepted.
Mid-pointMon, 2 Nov 2026(done)
Prize pool announced.
ClosesSun, 29 Nov 2026
Reports and selections are frozen. The last 48 hours are a quiet period.
ResultsMon, 7 Dec 2026
Private standings, medals and the marking pack. Seven days to appeal.
Rules
- One entry per person; your handle is fixed once you join. Entering means you accept the competition rules and terms.
- Up to 5 submissions a day (resets 00:00 UTC). Select up to 2 for final scoring; if you select none, your best public score's file is used.
- Train on the shipped data only. No external data beyond what the data card lists, and never the withheld targets from any source, looking them up is disqualification.
- Your solution report (30% of your points) is written on this page and graded as it stands at close. Medals and prizes need a filed report and a beaten baseline; the top ten are audited by re-running their code from train.csv.
- Sharing code or ideas publicly is fine; sharing a submission file is not (identical files are detected). One account per person. Text aimed at the grader scores zero.
- The final 48 hours are the quiet period: the public board freezes for viewers while you still see your own scores. Results are published once, after the audit, and are final subject to appeal.
The full competition terms apply to every entry.
Read the brief, then enter.
Free with a student account. The brief and the public leaderboard need no account.