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chore: eosdash improve plan display (#739)
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* chore: improve plan solution display

Add genetic optimization results to general solution provided by EOSdash plan display.

Add total results.

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>

* fix: genetic battery and home appliance device simulation

Fix genetic solution to make ac_charge, dc_charge, discharge, ev_charge or
home appliance start time reflect what the simulation was doing. Sometimes
the simulation decided to charge less or to start the appliance at another
time and this was not brought back to e.g. ac_charge.

Make home appliance simulation activate time window for the next day if it can not be
run today.

Improve simulation speed.

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>

---------

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
This commit is contained in:
Bobby Noelte
2025-11-08 15:42:18 +01:00
committed by GitHub
parent c50cdd95cb
commit 3599088dce
18 changed files with 1769 additions and 1345 deletions
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66
tests/test_geneticsimulation2.py
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@@ -65,7 +65,6 @@ def genetic_simulation_2(config_eos) -> GeneticSimulation:
optimization_hours = config_eos.optimization.horizon_hours,
prediction_hours = config_eos.prediction.hours,
)
home_appliance.set_starting_time(2)
# Example initialization of electric car battery
eauto = Battery(
@@ -158,10 +157,11 @@ def genetic_simulation_2(config_eos) -> GeneticSimulation:
ac = np.full(config_eos.prediction.hours, 0.0)
ac[20] = 1
simulation.set_akku_ac_charge_hours(ac)
simulation.ac_charge_hours = ac
dc = np.full(config_eos.prediction.hours, 0.0)
dc[11] = 1
simulation.set_akku_dc_charge_hours(dc)
simulation.dc_charge_hours = dc
simulation.home_appliance_start_hour = 2
return simulation
@@ -242,26 +242,26 @@ def test_simulation(genetic_simulation_2):
)
# Verfify DC and AC Charge Bins
assert abs(result["akku_soc_pro_stunde"][2] - 44.70681818181818) < 1e-5, (
"'akku_soc_pro_stunde[2]' should be 44.70681818181818."
assert abs(result["akku_soc_pro_stunde"][2] - 80.0) < 1e-5, (
"'akku_soc_pro_stunde[2]' should be 80.0."
)
assert abs(result["akku_soc_pro_stunde"][10] - 10.0) < 1e-5, (
"'akku_soc_pro_stunde[10]' should be 10."
assert abs(result["akku_soc_pro_stunde"][10] - 80.0) < 1e-5, (
"'akku_soc_pro_stunde[10]' should be 80."
)
assert abs(result["Netzeinspeisung_Wh_pro_Stunde"][10] - 3946.93) < 1e-3, (
"'Netzeinspeisung_Wh_pro_Stunde[11]' should be 3946.93."
)
assert abs(result["Netzeinspeisung_Wh_pro_Stunde"][11] - 0.0) < 1e-3, (
"'Netzeinspeisung_Wh_pro_Stunde[11]' should be 0.0."
assert abs(result["Netzeinspeisung_Wh_pro_Stunde"][11] - 2799.7263636361786) < 1e-3, (
"'Netzeinspeisung_Wh_pro_Stunde[11]' should be 2799.7263636361786."
)
assert abs(result["akku_soc_pro_stunde"][20] - 10) < 1e-5, (
"'akku_soc_pro_stunde[20]' should be 10."
assert abs(result["akku_soc_pro_stunde"][20] - 100) < 1e-5, (
"'akku_soc_pro_stunde[20]' should be 100."
)
assert abs(result["Last_Wh_pro_Stunde"][20] - 6050.98) < 1e-3, (
"'Last_Wh_pro_Stunde[20]' should be 6050.98."
assert abs(result["Last_Wh_pro_Stunde"][20] - 1050.98) < 1e-3, (
"'Last_Wh_pro_Stunde[20]' should be 1050.98."
)
print("All tests passed successfully.")
@@ -280,46 +280,6 @@ def test_set_parameters(genetic_simulation_2):
)
def test_set_akku_discharge_hours(genetic_simulation_2):
"""Test the set_akku_discharge_hours method of EnergyManagement."""
simulation = genetic_simulation_2
discharge_hours = np.full(simulation.prediction_hours, 1.0)
simulation.set_akku_discharge_hours(discharge_hours)
assert np.array_equal(simulation.battery.discharge_array, discharge_hours), (
"Discharge hours should be set correctly"
)
def test_set_akku_ac_charge_hours(genetic_simulation_2):
"""Test the set_akku_ac_charge_hours method of EnergyManagement."""
simulation = genetic_simulation_2
ac_charge_hours = np.full(simulation.prediction_hours, 1.0)
simulation.set_akku_ac_charge_hours(ac_charge_hours)
assert np.array_equal(simulation.ac_charge_hours, ac_charge_hours), (
"AC charge hours should be set correctly"
)
def test_set_akku_dc_charge_hours(genetic_simulation_2):
"""Test the set_akku_dc_charge_hours method of EnergyManagement."""
simulation = genetic_simulation_2
dc_charge_hours = np.full(simulation.prediction_hours, 1.0)
simulation.set_akku_dc_charge_hours(dc_charge_hours)
assert np.array_equal(simulation.dc_charge_hours, dc_charge_hours), (
"DC charge hours should be set correctly"
)
def test_set_ev_charge_hours(genetic_simulation_2):
"""Test the set_ev_charge_hours method of EnergyManagement."""
simulation = genetic_simulation_2
ev_charge_hours = np.full(simulation.prediction_hours, 1.0)
simulation.set_ev_charge_hours(ev_charge_hours)
assert np.array_equal(simulation.ev_charge_hours, ev_charge_hours), (
"EV charge hours should be set correctly"
)
def test_reset(genetic_simulation_2):
"""Test the reset method of EnergyManagement."""
simulation = genetic_simulation_2