mirror of
https://github.com/Akkudoktor-EOS/EOS.git
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75987db9e1
* Add EOS_CONFIG_DIR to set config dir (relative path to EOS_DIR or
absolute path).
- config_folder_path read-only
- config_file_path read-only
* Default values to support app start with empty config:
- latitude/longitude (Berlin)
- optimization_ev_available_charge_rates_percent (null, so model
default value is used)
- Enable Akkudoktor electricity price forecast (docker-compose).
* Fix some endpoints (empty data, remove unused params, fix types).
* cacheutil: Use cache dir. Closes #240
* Support EOS_LOGGING_LEVEL environment variable to set log level.
* tests: All tests use separate temporary config
- Add pytest switch --check-config-side-effect to check user
config file existence after each test. Will also fail if user config
existed before test execution (but will only check after the test has
run).
Enable flag in github workflow.
- Globally mock platformdirs in config module. Now no longer required
to patch individually.
Function calls to config instance (e.g. merge_settings_from_dict)
were unaffected previously.
* Set Berlin as default location (default config/docker-compose).
257 lines
7.5 KiB
Python
257 lines
7.5 KiB
Python
from pathlib import Path
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import numpy as np
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import pytest
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from akkudoktoreos.core.ems import (
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EnergieManagementSystem,
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EnergieManagementSystemParameters,
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get_ems,
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)
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from akkudoktoreos.devices.battery import (
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Battery,
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ElectricVehicleParameters,
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SolarPanelBatteryParameters,
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)
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from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
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from akkudoktoreos.devices.inverter import Inverter, InverterParameters
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from akkudoktoreos.prediction.interpolator import SelfConsumptionPropabilityInterpolator
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start_hour = 0
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# Example initialization of necessary components
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@pytest.fixture
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def create_ems_instance(config_eos) -> EnergieManagementSystem:
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"""Fixture to create an EnergieManagementSystem instance with given test parameters."""
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# Assure configuration holds the correct values
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config_eos.merge_settings_from_dict({"prediction_hours": 48, "optimization_hours": 24})
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assert config_eos.prediction_hours is not None
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# Initialize the battery and the inverter
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akku = Battery(
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SolarPanelBatteryParameters(
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capacity_wh=5000, initial_soc_percentage=80, min_soc_percentage=10
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),
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hours=config_eos.prediction_hours,
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)
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# 1h Load to Sub 1h Load Distribution -> SelfConsumptionRate
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sc = SelfConsumptionPropabilityInterpolator(
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Path(__file__).parent.resolve()
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/ ".."
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/ "src"
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/ "akkudoktoreos"
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/ "data"
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/ "regular_grid_interpolator.pkl"
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)
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akku.reset()
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inverter = Inverter(sc, InverterParameters(max_power_wh=10000), akku)
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# Household device (currently not used, set to None)
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home_appliance = HomeAppliance(
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HomeApplianceParameters(
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consumption_wh=2000,
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duration_h=2,
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),
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hours=config_eos.prediction_hours,
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)
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home_appliance.set_starting_time(2)
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# Example initialization of electric car battery
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eauto = Battery(
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ElectricVehicleParameters(
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capacity_wh=26400, initial_soc_percentage=100, min_soc_percentage=100
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),
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hours=config_eos.prediction_hours,
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)
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# Parameters based on previous example data
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pv_prognose_wh = [0.0] * config_eos.prediction_hours
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pv_prognose_wh[10] = 5000.0
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pv_prognose_wh[11] = 5000.0
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strompreis_euro_pro_wh = [0.001] * config_eos.prediction_hours
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strompreis_euro_pro_wh[0:10] = [0.00001] * 10
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strompreis_euro_pro_wh[11:15] = [0.00005] * 4
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strompreis_euro_pro_wh[20] = 0.00001
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einspeiseverguetung_euro_pro_wh = [0.00007] * len(strompreis_euro_pro_wh)
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preis_euro_pro_wh_akku = 0.0001
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gesamtlast = [
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676.71,
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876.19,
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527.13,
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468.88,
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531.38,
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517.95,
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483.15,
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472.28,
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1011.68,
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995.00,
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1053.07,
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1063.91,
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1320.56,
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1132.03,
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1163.67,
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1176.82,
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1216.22,
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1103.78,
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1129.12,
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1178.71,
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1050.98,
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988.56,
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912.38,
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704.61,
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516.37,
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868.05,
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694.34,
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608.79,
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556.31,
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488.89,
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506.91,
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804.89,
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1141.98,
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1056.97,
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992.46,
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1155.99,
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827.01,
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1257.98,
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1232.67,
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871.26,
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860.88,
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1158.03,
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1222.72,
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1221.04,
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949.99,
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987.01,
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733.99,
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592.97,
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]
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# Initialize the energy management system with the respective parameters
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ems = get_ems()
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ems.set_parameters(
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EnergieManagementSystemParameters(
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pv_prognose_wh=pv_prognose_wh,
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strompreis_euro_pro_wh=strompreis_euro_pro_wh,
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einspeiseverguetung_euro_pro_wh=einspeiseverguetung_euro_pro_wh,
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preis_euro_pro_wh_akku=preis_euro_pro_wh_akku,
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gesamtlast=gesamtlast,
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),
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inverter=inverter,
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ev=eauto,
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home_appliance=home_appliance,
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)
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ac = np.full(config_eos.prediction_hours, 0.0)
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ac[20] = 1
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ems.set_akku_ac_charge_hours(ac)
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dc = np.full(config_eos.prediction_hours, 0.0)
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dc[11] = 1
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ems.set_akku_dc_charge_hours(dc)
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return ems
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def test_simulation(create_ems_instance):
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"""Test the EnergieManagementSystem simulation method."""
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ems = create_ems_instance
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# Simulate starting from hour 0 (this value can be adjusted)
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result = ems.simulate(start_hour=start_hour)
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# --- Pls do not remove! ---
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# visualisiere_ergebnisse(
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# ems.gesamtlast,
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# ems.pv_prognose_wh,
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# ems.strompreis_euro_pro_wh,
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# result,
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# ems.akku.discharge_array+ems.akku.charge_array,
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# None,
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# ems.pv_prognose_wh,
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# start_hour,
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# 48,
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# np.full(48, 0.0),
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# filename="visualization_results.pdf",
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# extra_data=None,
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# )
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# Assertions to validate results
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assert result is not None, "Result should not be None"
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assert isinstance(result, dict), "Result should be a dictionary"
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assert "Last_Wh_pro_Stunde" in result, "Result should contain 'Last_Wh_pro_Stunde'"
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"""
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Check the result of the simulation based on expected values.
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"""
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# Example result returned from the simulation (used for assertions)
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assert result is not None, "Result should not be None."
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# Check that the result is a dictionary
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assert isinstance(result, dict), "Result should be a dictionary."
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# Verify that the expected keys are present in the result
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expected_keys = [
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"Last_Wh_pro_Stunde",
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"Netzeinspeisung_Wh_pro_Stunde",
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"Netzbezug_Wh_pro_Stunde",
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"Kosten_Euro_pro_Stunde",
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"akku_soc_pro_stunde",
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"Einnahmen_Euro_pro_Stunde",
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"Gesamtbilanz_Euro",
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"EAuto_SoC_pro_Stunde",
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"Gesamteinnahmen_Euro",
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"Gesamtkosten_Euro",
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"Verluste_Pro_Stunde",
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"Gesamt_Verluste",
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"Home_appliance_wh_per_hour",
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]
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for key in expected_keys:
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assert key in result, f"The key '{key}' should be present in the result."
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# Check the length of the main arrays
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assert (
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len(result["Last_Wh_pro_Stunde"]) == 48
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), "The length of 'Last_Wh_pro_Stunde' should be 48."
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assert (
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len(result["Netzeinspeisung_Wh_pro_Stunde"]) == 48
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), "The length of 'Netzeinspeisung_Wh_pro_Stunde' should be 48."
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assert (
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len(result["Netzbezug_Wh_pro_Stunde"]) == 48
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), "The length of 'Netzbezug_Wh_pro_Stunde' should be 48."
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assert (
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len(result["Kosten_Euro_pro_Stunde"]) == 48
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), "The length of 'Kosten_Euro_pro_Stunde' should be 48."
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assert (
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len(result["akku_soc_pro_stunde"]) == 48
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), "The length of 'akku_soc_pro_stunde' should be 48."
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# Verfify DC and AC Charge Bins
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assert (
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abs(result["akku_soc_pro_stunde"][2] - 44.70681818181818) < 1e-5
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), "'akku_soc_pro_stunde[2]' should be 44.70681818181818."
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assert (
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abs(result["akku_soc_pro_stunde"][10] - 10.0) < 1e-5
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), "'akku_soc_pro_stunde[10]' should be 10."
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assert (
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abs(result["Netzeinspeisung_Wh_pro_Stunde"][10] - 3946.93) < 1e-3
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), "'Netzeinspeisung_Wh_pro_Stunde[11]' should be 4000."
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assert (
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abs(result["Netzeinspeisung_Wh_pro_Stunde"][11] - 0.0) < 1e-3
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), "'Netzeinspeisung_Wh_pro_Stunde[11]' should be 0.0."
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assert (
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abs(result["akku_soc_pro_stunde"][20] - 10) < 1e-5
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), "'akku_soc_pro_stunde[20]' should be 10."
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assert (
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abs(result["Last_Wh_pro_Stunde"][20] - 6050.98) < 1e-3
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), "'Netzeinspeisung_Wh_pro_Stunde[11]' should be 0.0."
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print("All tests passed successfully.")
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