tasks.task_safe_zone_load_demo

tasks.task_safe_zone_load_demo

Task demo: four-zone bottom-up total-load forecast vs. a direct aggregate.

This task demonstrates the four-German-TSO-zone forecasting design: fit one model per control-zone load series (Amprion, TenneT, TransnetBW, 50Hertz) and sum the four forecasts into the total-German-load forecast (bottom-up aggregation), then compare it against a single model trained on the aggregate load directly. The bottom-up combination reuses the existing multi-target machinery – the four zones become ConfigMulti.targets and the per-target forecasts are summed via the MultiTask aggregation with agg_weights=[1.0, ...].

Data source. With data_path pointing at the assembled four-column interim file (see spotforecast2_safe.downloader.entsoe.assemble_zone_loads), the task runs on real ENTSO-E control-zone load. With data_path=None (the default) it builds a deterministic, seeded synthetic four-zone dataset so the demo and its smoke test run offline without an ENTSO-E API key.

The comparison uses the project’s own backtesting engine (backtesting_forecaster + TimeSeriesFold) over a 24-hour horizon and reports MAE / RMSE / MAPE for both methods.

Examples

# Shell commands; they cannot run inside a Python kernel.
# Synthetic offline demo (no API key needed):
#   uv run spotforecast-safe-zone-load-demo
# Run on assembled real ENTSO-E zone data:
#   uv run spotforecast-safe-zone-load-demo     #       --data_path ~/spotforecast2_data/interim/energy_load_zones.csv

Functions

Name	Description
main	Run the four-zone bottom-up load demo. Returns 0 on success, 1 on failure.

main

tasks.task_safe_zone_load_demo.main(
    synthetic=True,
    data_path=None,
    predict_size=24,
    history_hours=24 * 100,
    random_seed=314159,
    logging_enabled=False,
)

Run the four-zone bottom-up load demo. Returns 0 on success, 1 on failure.

Parameters

Name	Type	Description	Default
synthetic	bool	If True (and `data_path` is None), use seeded synthetic data. Ignored when `data_path` is provided.	`True`
data_path	Optional[Path]	Path to an assembled four-column zone-load CSV. When given, real data is used and `synthetic` is ignored.	`None`
predict_size	int	Forecast horizon in hours (also the backtest fold size).	`24`
history_hours	int	Length of the synthetic series in hours.	`24 * 100`
random_seed	int	Seed for the synthetic data and the estimators.	`314159`
logging_enabled	bool	If True, attach the dual console/file handlers.	`False`

Examples

from spotforecast2_safe.tasks.task_safe_zone_load_demo import main

# Fail-fast: a non-existent data_path returns 1 without computing.
from pathlib import Path
rc = main(data_path=Path("/nonexistent/zones.csv"))
print(f"Return code (missing data): {rc}")
assert rc == 1

Return code (missing data): 1