feat(optimization): support a 15-minute optimization interval

The genetic optimizer was hard-wired to an hourly grid and forced
optimization.interval to 3600 s. Generalize it to a configurable slot grid
of length prediction.hours * (3600 / interval), accepting 900 (15 min) in
addition to the default 3600 (1 hour) so the optimizer can schedule on a
quarter-hour grid for 15-minute dynamic electricity tariffs.

- genetic.py: slot_duration_h / slots_per_hour / total_slots helpers; all GA
  vectors sized by total_slots; simulate()/evaluate() indexed by start slot.
- geneticparams.py: allow {900, 3600}; scale the load power series to per-slot
  energy, mirroring the PV series.
- battery.py / inverter.py: scale power caps to per-slot energy caps via
  slot_duration_h; homeappliance.py carries the hook.
- geneticsolution.py: serialize solution and plan on the slot grid (interval
  freq, start-slot offset, second-based instruction instants).

The default 3600 s interval keeps the previous hourly behaviour; the genetic
regression suite is unchanged. Adds tests for the 15-minute slot grid.

src/akkudoktoreos/optimization/optimization.py

@@ -72,7 +72,11 @@ class OptimizationCommonSettings(SettingsBaseModel):
         ge=15 * 60,
         le=60 * 60,
         json_schema_extra={
-            "description": "The optimization interval [sec]. Defaults to 3600 seconds (1 hour)",
+            "description": (
+                "The optimization interval (slot length) [sec]. The genetic "
+                "optimizer supports 3600 (1 hour) and 900 (15 min); other values "
+                "fall back to 3600. Defaults to 3600 seconds (1 hour)."
+            ),
             "examples": [60 * 60, 15 * 60],
         },
     )