Improve Configuration and Prediction Usability (#220)

* 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>
This commit is contained in:
Bobby Noelte
2024-12-15 14:40:03 +01:00
committed by GitHub
parent a5e637ab4c
commit aa334d0b61
80 changed files with 29048 additions and 2451 deletions

View File

@@ -1,28 +1,32 @@
import numpy as np
import pytest
from akkudoktoreos.config import AppConfig
from akkudoktoreos.config.config import get_config
from akkudoktoreos.core.ems import (
EnergieManagementSystem,
EnergieManagementSystemParameters,
get_ems,
)
from akkudoktoreos.devices.battery import EAutoParameters, PVAkku, PVAkkuParameters
from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
from akkudoktoreos.devices.inverter import Wechselrichter, WechselrichterParameters
from akkudoktoreos.prediction.ems import (
EnergieManagementSystem,
EnergieManagementSystemParameters,
)
prediction_hours = 48
optimization_hours = 24
start_hour = 0
# Example initialization of necessary components
@pytest.fixture
def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
def create_ems_instance() -> EnergieManagementSystem:
"""Fixture to create an EnergieManagementSystem instance with given test parameters."""
# Assure configuration holds the correct values
config_eos = get_config()
config_eos.merge_settings_from_dict({"prediction_hours": 48, "optimization_hours": 24})
assert config_eos.prediction_hours is not None
# Initialize the battery and the inverter
akku = PVAkku(
PVAkkuParameters(kapazitaet_wh=5000, start_soc_prozent=80, min_soc_prozent=10),
hours=prediction_hours,
hours=config_eos.prediction_hours,
)
akku.reset()
wechselrichter = Wechselrichter(WechselrichterParameters(max_leistung_wh=10000), akku)
@@ -33,27 +37,28 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
consumption_wh=2000,
duration_h=2,
),
hours=prediction_hours,
hours=config_eos.prediction_hours,
)
home_appliance.set_starting_time(2)
# Example initialization of electric car battery
eauto = PVAkku(
EAutoParameters(kapazitaet_wh=26400, start_soc_prozent=100, min_soc_prozent=100),
hours=prediction_hours,
hours=config_eos.prediction_hours,
)
# Parameters based on previous example data
pv_prognose_wh = [0.0] * prediction_hours
pv_prognose_wh = [0.0] * config_eos.prediction_hours
pv_prognose_wh[10] = 5000.0
pv_prognose_wh[11] = 5000.0
strompreis_euro_pro_wh = [0.001] * prediction_hours
strompreis_euro_pro_wh = [0.001] * config_eos.prediction_hours
strompreis_euro_pro_wh[0:10] = [0.00001] * 10
strompreis_euro_pro_wh[11:15] = [0.00005] * 4
strompreis_euro_pro_wh[20] = 0.00001
einspeiseverguetung_euro_pro_wh = [0.00007] * len(strompreis_euro_pro_wh)
preis_euro_pro_wh_akku = 0.0001
gesamtlast = [
676.71,
@@ -107,13 +112,13 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
]
# Initialize the energy management system with the respective parameters
ems = EnergieManagementSystem(
tmp_config.eos,
ems = get_ems()
ems.set_parameters(
EnergieManagementSystemParameters(
pv_prognose_wh=pv_prognose_wh,
strompreis_euro_pro_wh=strompreis_euro_pro_wh,
einspeiseverguetung_euro_pro_wh=einspeiseverguetung_euro_pro_wh,
preis_euro_pro_wh_akku=0,
preis_euro_pro_wh_akku=preis_euro_pro_wh_akku,
gesamtlast=gesamtlast,
),
wechselrichter=wechselrichter,
@@ -121,10 +126,10 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
home_appliance=home_appliance,
)
ac = np.full(prediction_hours, 0)
ac = np.full(config_eos.prediction_hours, 0.0)
ac[20] = 1
ems.set_akku_ac_charge_hours(ac)
dc = np.full(prediction_hours, 0)
dc = np.full(config_eos.prediction_hours, 0.0)
dc[11] = 1
ems.set_akku_dc_charge_hours(dc)