| { |
| "tag": "real-weather-forecasts-aug10", |
| "goal": "Recover the perfect-foresight gap using REAL archived day-ahead weather forecasts as a causal future covariate. Honest RTO-7 test MASE is 0.572; the oracle (perfect weather + renewables) ceiling is 0.468. Close at least half that gap without leakage and without degrading held-out BAs.", |
| "metric": "mase", |
| "metric_direction": "lower", |
| "baseline": { |
| "note": "7 RTOs, 2025 test split, causal covariates, deduplicated store.", |
| "no_future_weather": 0.5937, |
| "plus_peer_covariates": 0.5804, |
| "plus_causal_readaptation": 0.572, |
| "chronos2_zeroshot_plus_peers": 0.5908, |
| "oracle_ceiling_not_a_forecast": 0.4683 |
| }, |
| "target": 0.52, |
| "success": { |
| "primary": "RTO-7 test MASE <= 0.52 (>= 50% of the 0.572 -> 0.468 gap closed)", |
| "stretch": "<= 0.50", |
| "must_not_regress": "holdout_gap worse by more than 0.02; cov_pi80 below 0.75", |
| "must_beat": "Chronos-2 zero-shot given the SAME forecast covariates \u2014 otherwise the gain belongs to the covariate, not to surge." |
| }, |
| "run_command": "bash scripts/run_remote_experiment.sh $EXP_NAME $CONFIG_JSON", |
| "eval_contract": { |
| "entrypoint": "experiments.research_eval", |
| "split": "validation (calendar 2024). Test (2025) is reserved for a single final confirmation via {\"confirm\": true}.", |
| "objective_field": "mase", |
| "generalisation_field": "holdout_gap", |
| "rejects": "future_mode='oracle', and any setup whose future covariates change when post-origin actuals are perturbed" |
| }, |
| "modifiable_files": [ |
| "experiments/features.py", |
| "experiments/eval_c2.py", |
| "experiments/models.py", |
| "experiments/finetune_c2.py", |
| "experiments/ensemble.py" |
| ], |
| "readonly_files": [ |
| "experiments/causal_guard.py", |
| "experiments/research_eval.py", |
| "src/surge/store.py", |
| "src/surge/scrapers/eia.py", |
| "src/surge/scrapers/asos.py" |
| ], |
| "hard_constraints": [ |
| "The forecast covariate at hour t must be the value forecast at or before t-horizon. Never substitute the observed series or the reanalysis - that is the oracle leak.", |
| "Train and serve on the SAME covariate kind. Training on observed temperature and serving a forecast is the train/serve mismatch that made every causal proxy lose to withholding temperature entirely.", |
| "Because the forecast archive starts 2021-03, retrain on 2021-2023 and keep val=2024 and test=2025 unchanged so results stay comparable to results.tsv.", |
| "Never score on test during search. Validation only; one final confirmation.", |
| "Always report Chronos-2 zero-shot with the same covariates as the control." |
| ], |
| "ideas": [ |
| { |
| "id": "forecast_temp_covariate", |
| "priority": 1, |
| "rationale": "Day-ahead forecast temp has MAE ~1.3C and corr ~0.99 against the analysis, so it should capture most of the 0.084 MASE that oracle temperature was worth. This is the single largest measured lever.", |
| "try": "ingest temperature_2m_previous_day1 for the 7 RTO centroids 2021-03..2026-04; declare it known-future; retrain so the model learns to trust it appropriately." |
| }, |
| { |
| "id": "forecast_renewables", |
| "priority": 2, |
| "rationale": "Oracle wind/solar was worth a further 0.043 MASE. Open-Meteo exposes shortwave radiation and 100m wind speed as forecast variables, which proxy solar and wind output causally.", |
| "try": "add shortwave_radiation_previous_day1 and wind_speed_100m_previous_day1." |
| }, |
| { |
| "id": "asos_backfill_46", |
| "priority": 2, |
| "rationale": "46 of 53 BAs have zero-filled weather. Forecast covariates can cover all 53 from Open-Meteo centroids without needing the ASOS backfill at all.", |
| "try": "fetch forecast temp for all 53 BA centroids, not just the RTOs." |
| }, |
| { |
| "id": "continuous_retraining", |
| "priority": 3, |
| "rationale": "Measured 8% degradation from Jan-Apr 2025 to Jan-Apr 2026 for both surge and zero-shot. Literature (arXiv 2607.15705) finds continuous retraining materially important and commonly overlooked.", |
| "try": "rolling monthly LoRA re-adaptation; 37s per run makes this nearly free." |
| }, |
| { |
| "id": "tabpfn_ts", |
| "priority": 3, |
| "rationale": "TabPFN-TS (11M params) claims SOTA on covariate-informed forecasting on GIFT-Eval and fev-bench, and reportedly captures simple covariate-target relations better than Chronos-2 at short horizons.", |
| "try": "evaluate with identical covariates; consider cross-family output ensembling." |
| }, |
| { |
| "id": "public_benchmark", |
| "priority": 3, |
| "rationale": "SOTA cannot be claimed on a self-defined BA set with a self-computed denominator. Needs a benchmark with published numbers.", |
| "try": "GEFCom2014-L (probabilistic, pinball loss), fev-bench/GIFT-Eval covariate tracks, or the frozen German live-challenge leaderboard (arXiv 2608.05018)." |
| } |
| ], |
| "timeout_seconds": 1800, |
| "no_new_dependencies": false, |
| "stop_conditions": { |
| "wall_clock_minutes": 360, |
| "no_improvement_streak": 6 |
| }, |
| "measured_inputs": { |
| "weather_forecast_source": "Open-Meteo Previous Runs API, temperature_2m_previous_day1 (GFS seamless) \u2014 the forecast issued ~24h before valid time", |
| "archive_start": "2021-03 for GFS 2m temperature; ~2024-01 for most other models", |
| "day_ahead_forecast_skill_2025": { |
| "mae_degC": { |
| "PJM": 1.3, |
| "CISO": 1.06, |
| "ERCO": 1.25, |
| "MISO": 1.38, |
| "NYIS": 1.31, |
| "ISNE": 1.55, |
| "SWPP": 1.22 |
| }, |
| "corr": "0.983 - 0.990", |
| "bias_degC": "-0.40 .. +0.20" |
| } |
| } |
| } |
|
|
