mirror of
https://github.com/Akkudoktor-EOS/EOS.git
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aa334d0b61
* Update utilities in utils submodule. * Add base configuration modules. * Add server base configuration modules. * Add devices base configuration modules. * Add optimization base configuration modules. * Add utils base configuration modules. * Add prediction abstract and base classes plus tests. * Add PV forecast to prediction submodule. The PV forecast modules are adapted from the class_pvforecast module and replace it. * Add weather forecast to prediction submodule. The modules provide classes and methods to retrieve, manage, and process weather forecast data from various sources. Includes are structured representations of weather data and utilities for fetching forecasts for specific locations and time ranges. BrightSky and ClearOutside are currently supported. * Add electricity price forecast to prediction submodule. * Adapt fastapi server to base config and add fasthtml server. * Add ems to core submodule. * Adapt genetic to config. * Adapt visualize to config. * Adapt common test fixtures to config. * Add load forecast to prediction submodule. * Add core abstract and base classes. * Adapt single test optimization to config. * Adapt devices to config. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
342 lines
9.0 KiB
Python
342 lines
9.0 KiB
Python
import numpy as np
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import pytest
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from akkudoktoreos.config.config import get_config
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from akkudoktoreos.core.ems import (
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EnergieManagementSystem,
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EnergieManagementSystemParameters,
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SimulationResult,
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get_ems,
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)
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from akkudoktoreos.devices.battery import EAutoParameters, PVAkku, PVAkkuParameters
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from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
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from akkudoktoreos.devices.inverter import Wechselrichter, WechselrichterParameters
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start_hour = 1
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# Example initialization of necessary components
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@pytest.fixture
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def create_ems_instance() -> 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 = get_config()
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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 = PVAkku(
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PVAkkuParameters(kapazitaet_wh=5000, start_soc_prozent=80, min_soc_prozent=10),
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hours=config_eos.prediction_hours,
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)
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akku.reset()
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wechselrichter = Wechselrichter(WechselrichterParameters(max_leistung_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 = PVAkku(
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EAutoParameters(kapazitaet_wh=26400, start_soc_prozent=10, min_soc_prozent=10),
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hours=config_eos.prediction_hours,
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)
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eauto.set_charge_per_hour(np.full(config_eos.prediction_hours, 1))
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# Parameters based on previous example data
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pv_prognose_wh = [
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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8.05,
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352.91,
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728.51,
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930.28,
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1043.25,
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1106.74,
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1161.69,
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6018.82,
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5519.07,
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3969.88,
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3017.96,
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1943.07,
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1007.17,
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319.67,
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7.88,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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5.04,
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335.59,
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705.32,
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1121.12,
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1604.79,
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2157.38,
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1433.25,
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5718.49,
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4553.96,
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3027.55,
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2574.46,
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1720.4,
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963.4,
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383.3,
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0,
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0,
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0,
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]
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strompreis_euro_pro_wh = [
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0.0003384,
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0.0003318,
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0.0003284,
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0.0003283,
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0.0003289,
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0.0003334,
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0.0003290,
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0.0003302,
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0.0003042,
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0.0002430,
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0.0002280,
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0.0002212,
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0.0002093,
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0.0001879,
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0.0001838,
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0.0002004,
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0.0002198,
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0.0002270,
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0.0002997,
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0.0003195,
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0.0003081,
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0.0002969,
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0.0002921,
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0.0002780,
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0.0003384,
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0.0003318,
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0.0003284,
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0.0003283,
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0.0003289,
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0.0003334,
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0.0003290,
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0.0003302,
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0.0003042,
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0.0002430,
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0.0002280,
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0.0002212,
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0.0002093,
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0.0001879,
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0.0001838,
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0.0002004,
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0.0002198,
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0.0002270,
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0.0002997,
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0.0003195,
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0.0003081,
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0.0002969,
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0.0002921,
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0.0002780,
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]
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einspeiseverguetung_euro_pro_wh = 0.00007
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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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wechselrichter=wechselrichter,
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eauto=eauto,
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home_appliance=home_appliance,
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)
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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 1 (this value can be adjusted)
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result = ems.simuliere(start_stunde=start_hour)
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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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assert SimulationResult(**result) is not None
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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"]) == 47
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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"]) == 47
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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"]) == 47
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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"]) == 47
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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"]) == 47
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), "The length of 'akku_soc_pro_stunde' should be 48."
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# Verify specific values in the 'Last_Wh_pro_Stunde' array
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assert (
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result["Last_Wh_pro_Stunde"][1] == 1527.13
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), "The value at index 1 of 'Last_Wh_pro_Stunde' should be 1527.13."
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assert (
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result["Last_Wh_pro_Stunde"][2] == 1468.88
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), "The value at index 2 of 'Last_Wh_pro_Stunde' should be 1468.88."
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assert (
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result["Last_Wh_pro_Stunde"][12] == 1132.03
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), "The value at index 12 of 'Last_Wh_pro_Stunde' should be 1132.03."
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# Verify that the value at index 0 is 'None'
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# Check that 'Netzeinspeisung_Wh_pro_Stunde' and 'Netzbezug_Wh_pro_Stunde' are consistent
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assert (
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result["Netzbezug_Wh_pro_Stunde"][1] == 0
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), "The value at index 1 of 'Netzbezug_Wh_pro_Stunde' should be 0."
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# Verify the total balance
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assert (
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abs(result["Gesamtbilanz_Euro"] - 1.7880374129090917) < 1e-5
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), "Total balance should be 1.7880374129090917."
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# Check total revenue and total costs
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assert (
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abs(result["Gesamteinnahmen_Euro"] - 1.3169784090909087) < 1e-5
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), "Total revenue should be 1.3169784090909087."
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assert (
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abs(result["Gesamtkosten_Euro"] - 3.1050158220000004) < 1e-5
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), "Total costs should be 3.1050158220000004 ."
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# Check the losses
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assert (
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abs(result["Gesamt_Verluste"] - 2615.222727272727) < 1e-5
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), "Total losses should be 2615.222727272727 ."
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# Check the values in 'akku_soc_pro_stunde'
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assert (
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result["akku_soc_pro_stunde"][-1] == 28.675
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), "The value at index -1 of 'akku_soc_pro_stunde' should be 28.675."
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assert (
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result["akku_soc_pro_stunde"][1] == 25.379090909090905
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), "The value at index 1 of 'akku_soc_pro_stunde' should be 25.379090909090905."
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# Check home appliances
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assert (
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sum(ems.home_appliance.get_load_curve()) == 2000
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), "The sum of 'ems.home_appliance.get_load_curve()' should be 2000."
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assert (
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np.nansum(
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np.where(
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result["Home_appliance_wh_per_hour"] is None,
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np.nan,
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np.array(result["Home_appliance_wh_per_hour"]),
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)
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)
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== 2000
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), "The sum of 'Home_appliance_wh_per_hour' should be 2000."
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print("All tests passed successfully.")
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