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>
This commit is contained in:
Andreas
2026-07-15 14:19:46 +02:00
co-authored by Claude Opus 4.8
parent c59bf1b486
commit 67cf6f7d8a
21 changed files with 2505 additions and 1094 deletions
+5 -5
View File
@@ -54,7 +54,7 @@ def genetic_simulation(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",
@@ -65,6 +65,7 @@ def genetic_simulation(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(
@@ -246,7 +247,7 @@ def genetic_simulation(config_eos) -> GeneticSimulation:
prediction_hours=config_eos.prediction.hours,
inverter=inverter,
ev=eauto,
home_appliance=home_appliance,
home_appliances=[home_appliance],
)
# Init for test
@@ -259,7 +260,6 @@ def genetic_simulation(config_eos) -> GeneticSimulation:
simulation.dc_charge_hours[start_hour] = 1.0
simulation.bat_discharge_hours[start_hour] = 1.0
simulation.ev_charge_hours[start_hour] = 1.0
simulation.home_appliance_start_hour = 2
return simulation
@@ -362,8 +362,8 @@ def test_simulation(genetic_simulation):
# Check home appliances
assert (
sum(simulation.home_appliance.get_load_curve()) == 2000
), "The sum of 'simulation.home_appliance.get_load_curve()' should be 2000."
sum(simulation.home_appliances[0].get_load_curve()) == 2000
), "The sum of 'simulation.home_appliances[0].get_load_curve()' should be 2000."
assert (
np.nansum(