feat(optimization): schedule any number of flexible consumers

Replace the single hourly "dishwasher" home appliance with a list of
flexible consumers (home_appliances). Each consumer defines its load
either as an explicit power profile (energy-preservingly resampled onto
the optimization slot grid, incl. 15-min and non-integer interval ratios)
or the flat consumption_wh/duration_h fallback, and runs ONCE or DAILY
within its time windows and the optimization horizon.

- ConsumerScheduleMode + shared load-definition validation (XOR of
  profile/fallback, reject negative/NaN/inf, unique device_id)
- ApplianceGeneLayout: variable appliance gene block (index into
  allowed_start_slots), ONCE/DAILY calendar-day based, no snapping
- per-device output: result.home_appliance_energy_wh, appliance_starts
  (absolute local times), per-device solution columns and DDBC RUN/OFF
  instructions on state transitions only
- deprecate dishwasher/washingstart/Home_appliance_wh_per_hour with
  backward-compatible mapping and explicit conflict rejection
- max_home_appliances is now an upper bound only; no demo appliance and
  no on/off behaviour
- docs, openapi.json, CHANGELOG and optimize_result_2* fixtures updated;
  new tests/test_homeappliance.py covers the mandatory test matrix

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tests/test_geneticsimulation2.py

@@ -50,7 +50,7 @@ def genetic_simulation_2(config_eos) -> GeneticSimulation:
         battery = akku,
     )
 
-    # Household device (currently not used, set to None)
+    # Flexible consumer (fixed start at slot 2 for this deterministic test)
     home_appliance = HomeAppliance(
         HomeApplianceParameters(
             device_id="dishwasher1",
@@ -61,6 +61,7 @@ def genetic_simulation_2(config_eos) -> GeneticSimulation:
         optimization_hours = config_eos.optimization.horizon_hours,
         prediction_hours = config_eos.prediction.hours,
     )
+    home_appliance.build_load_curve([2])
 
     # Example initialization of electric car battery
     eauto = Battery(
@@ -148,7 +149,7 @@ def genetic_simulation_2(config_eos) -> GeneticSimulation:
         prediction_hours = config_eos.prediction.hours,
         inverter=inverter,
         ev=eauto,
-        home_appliance=home_appliance,
+        home_appliances=[home_appliance],
     )
 
     ac = np.full(config_eos.prediction.hours, 0.0)
@@ -157,7 +158,6 @@ def genetic_simulation_2(config_eos) -> GeneticSimulation:
     dc = np.full(config_eos.prediction.hours, 0.0)
     dc[11] = 1
     simulation.dc_charge_hours = dc
-    simulation.home_appliance_start_hour = 2
 
     return simulation