Request QUARTER_HOURLY exchange prices from Tibber and store them at their
native resolution instead of pre-averaging to hourly values. EOS resamples the
stored records onto the optimization grid on demand (key_to_array), so keeping
the native step size lets both the hourly (interval=3600) and the 15-minute
(interval=900) optimizer be fed the correct grid automatically.
- GraphQL: priceInfoRange resolution HOURLY -> QUARTER_HOURLY (last 960).
- _hourly_series -> _normalize_series: dedupe by timestamp (mean) + sort, no
1h aggregation; add _resolution_seconds (median of timestamp diffs, fallback
3600s).
- Resolution-agnostic ETS extrapolation: seasonal windows and history
thresholds are scaled by slots_per_hour, needed forecast length and the
prediction index step are computed in slots. Hourly behaviour is unchanged
(slots_per_hour=1 -> 168/24 seasonal periods, hourly steps).
- Tests: replace the 1h-averaging test with resolution-preserving + dedup
tests, assert QUARTER_HOURLY in the query, add a 15-min end-to-end test
(native storage stays 15min, slot-based seasonal periods = 96, 15-min
forecast index). Hourly backward-compat tests stay green unchanged.
ChristinandAndreas