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

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from typing import Any, ClassVar, Dict, Optional, Union
import numpy as np
from numpydantic import NDArray, Shape
from pydantic import Field, computed_field
from akkudoktoreos.config.configabc import SettingsBaseModel
from akkudoktoreos.core.coreabc import SingletonMixin
from akkudoktoreos.devices.battery import PVAkku
from akkudoktoreos.devices.devicesabc import DevicesBase
from akkudoktoreos.devices.generic import HomeAppliance
from akkudoktoreos.devices.inverter import Wechselrichter
from akkudoktoreos.utils.datetimeutil import to_duration
from akkudoktoreos.utils.logutil import get_logger
logger = get_logger(__name__)
class DevicesCommonSettings(SettingsBaseModel):
"""Base configuration for devices simulation settings."""
# Battery
# -------
battery_provider: Optional[str] = Field(
default=None, description="Id of Battery simulation provider."
)
battery_capacity: Optional[int] = Field(default=None, description="Battery capacity [Wh].")
battery_soc_start: Optional[int] = Field(
default=None, description="Battery initial state of charge [%]."
)
battery_soc_min: Optional[int] = Field(
default=None, description="Battery minimum state of charge [%]."
)
battery_soc_max: Optional[int] = Field(
default=None, description="Battery maximum state of charge [%]."
)
battery_charge_efficiency: Optional[float] = Field(
default=None, description="Battery charging efficiency [%]."
)
battery_discharge_efficiency: Optional[float] = Field(
default=None, description="Battery discharging efficiency [%]."
)
battery_charge_power_max: Optional[int] = Field(
default=None, description="Battery maximum charge power [W]."
)
# Battery Electric Vehicle
# ------------------------
bev_provider: Optional[str] = Field(
default=None, description="Id of Battery Electric Vehicle simulation provider."
)
bev_capacity: Optional[int] = Field(
default=None, description="Battery Electric Vehicle capacity [Wh]."
)
bev_soc_start: Optional[int] = Field(
default=None, description="Battery Electric Vehicle initial state of charge [%]."
)
bev_soc_max: Optional[int] = Field(
default=None, description="Battery Electric Vehicle maximum state of charge [%]."
)
bev_charge_efficiency: Optional[float] = Field(
default=None, description="Battery Electric Vehicle charging efficiency [%]."
)
bev_discharge_efficiency: Optional[float] = Field(
default=None, description="Battery Electric Vehicle discharging efficiency [%]."
)
bev_charge_power_max: Optional[int] = Field(
default=None, description="Battery Electric Vehicle maximum charge power [W]."
)
# Home Appliance - Dish Washer
# ----------------------------
dishwasher_provider: Optional[str] = Field(
default=None, description="Id of Dish Washer simulation provider."
)
dishwasher_consumption: Optional[int] = Field(
default=None, description="Dish Washer energy consumption [Wh]."
)
dishwasher_duration: Optional[int] = Field(
default=None, description="Dish Washer usage duration [h]."
)
# PV Inverter
# -----------
inverter_provider: Optional[str] = Field(
default=None, description="Id of PV Inverter simulation provider."
)
inverter_power_max: Optional[float] = Field(
default=None, description="Inverter maximum power [W]."
)
class Devices(SingletonMixin, DevicesBase):
# Results of the devices simulation and
# insights into various parameters over the entire forecast period.
# -----------------------------------------------------------------
last_wh_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None, description="The load in watt-hours per hour."
)
eauto_soc_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None, description="The state of charge of the EV for each hour."
)
einnahmen_euro_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None,
description="The revenue from grid feed-in or other sources in euros per hour.",
)
home_appliance_wh_per_hour: Optional[NDArray[Shape["*"], float]] = Field(
default=None,
description="The energy consumption of a household appliance in watt-hours per hour.",
)
kosten_euro_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None, description="The costs in euros per hour."
)
netzbezug_wh_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None, description="The grid energy drawn in watt-hours per hour."
)
netzeinspeisung_wh_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None, description="The energy fed into the grid in watt-hours per hour."
)
verluste_wh_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None, description="The losses in watt-hours per hour."
)
akku_soc_pro_stunde: Optional[NDArray[Shape["*"], float]] = Field(
default=None,
description="The state of charge of the battery (not the EV) in percentage per hour.",
)
# Computed fields
@computed_field # type: ignore[prop-decorator]
@property
def total_balance_euro(self) -> float:
"""The total balance of revenues minus costs in euros."""
return self.total_revenues_euro - self.total_costs_euro
@computed_field # type: ignore[prop-decorator]
@property
def total_revenues_euro(self) -> float:
"""The total revenues in euros."""
if self.einnahmen_euro_pro_stunde is None:
return 0
return np.nansum(self.einnahmen_euro_pro_stunde)
@computed_field # type: ignore[prop-decorator]
@property
def total_costs_euro(self) -> float:
"""The total costs in euros."""
if self.kosten_euro_pro_stunde is None:
return 0
return np.nansum(self.kosten_euro_pro_stunde)
@computed_field # type: ignore[prop-decorator]
@property
def total_losses_wh(self) -> float:
"""The total losses in watt-hours over the entire period."""
if self.verluste_wh_pro_stunde is None:
return 0
return np.nansum(self.verluste_wh_pro_stunde)
# Devices
# TODO: Make devices class a container of device simulation providers.
# Device simulations to be used are then enabled in the configuration.
akku: ClassVar[PVAkku] = PVAkku(provider_id="GenericBattery")
eauto: ClassVar[PVAkku] = PVAkku(provider_id="GenericBEV")
home_appliance: ClassVar[HomeAppliance] = HomeAppliance(provider_id="GenericDishWasher")
wechselrichter: ClassVar[Wechselrichter] = Wechselrichter(
akku=akku, provider_id="GenericInverter"
)
def update_data(self) -> None:
"""Update device simulation data."""
# Assure devices are set up
self.akku.setup()
self.eauto.setup()
self.home_appliance.setup()
self.wechselrichter.setup()
# Pre-allocate arrays for the results, optimized for speed
self.last_wh_pro_stunde = np.full((self.total_hours), np.nan)
self.netzeinspeisung_wh_pro_stunde = np.full((self.total_hours), np.nan)
self.netzbezug_wh_pro_stunde = np.full((self.total_hours), np.nan)
self.kosten_euro_pro_stunde = np.full((self.total_hours), np.nan)
self.einnahmen_euro_pro_stunde = np.full((self.total_hours), np.nan)
self.akku_soc_pro_stunde = np.full((self.total_hours), np.nan)
self.eauto_soc_pro_stunde = np.full((self.total_hours), np.nan)
self.verluste_wh_pro_stunde = np.full((self.total_hours), np.nan)
self.home_appliance_wh_per_hour = np.full((self.total_hours), np.nan)
# Set initial state
simulation_step = to_duration("1 hour")
if self.akku:
self.akku_soc_pro_stunde[0] = self.akku.ladezustand_in_prozent()
if self.eauto:
self.eauto_soc_pro_stunde[0] = self.eauto.ladezustand_in_prozent()
# Get predictions for full device simulation time range
# gesamtlast[stunde]
load_total_mean = self.prediction.key_to_array(
"load_total_mean",
start_datetime=self.start_datetime,
end_datetime=self.end_datetime,
interval=simulation_step,
)
# pv_prognose_wh[stunde]
pvforecast_ac_power = self.prediction.key_to_array(
"pvforecast_ac_power",
start_datetime=self.start_datetime,
end_datetime=self.end_datetime,
interval=simulation_step,
)
# strompreis_euro_pro_wh[stunde]
elecprice_marketprice = self.prediction.key_to_array(
"elecprice_marketprice",
start_datetime=self.start_datetime,
end_datetime=self.end_datetime,
interval=simulation_step,
)
# einspeiseverguetung_euro_pro_wh_arr[stunde]
# TODO: Create prediction for einspeiseverguetung_euro_pro_wh_arr
einspeiseverguetung_euro_pro_wh_arr = np.full((self.total_hours), 0.078)
for stunde_since_now in range(0, self.total_hours):
stunde = self.start_datetime.hour + stunde_since_now
# Accumulate loads and PV generation
verbrauch = load_total_mean[stunde_since_now]
self.verluste_wh_pro_stunde[stunde_since_now] = 0.0
# Home appliances
if self.home_appliance:
ha_load = self.home_appliance.get_load_for_hour(stunde)
verbrauch += ha_load
self.home_appliance_wh_per_hour[stunde_since_now] = ha_load
# E-Auto handling
if self.eauto:
if self.ev_charge_hours[stunde] > 0:
geladene_menge_eauto, verluste_eauto = self.eauto.energie_laden(
None, stunde, relative_power=self.ev_charge_hours[stunde]
)
verbrauch += geladene_menge_eauto
self.verluste_wh_pro_stunde[stunde_since_now] += verluste_eauto
self.eauto_soc_pro_stunde[stunde_since_now] = self.eauto.ladezustand_in_prozent()
# Process inverter logic
netzeinspeisung, netzbezug, verluste, eigenverbrauch = (0.0, 0.0, 0.0, 0.0)
if self.akku:
self.akku.set_charge_allowed_for_hour(self.dc_charge_hours[stunde], stunde)
if self.wechselrichter:
erzeugung = pvforecast_ac_power[stunde]
netzeinspeisung, netzbezug, verluste, eigenverbrauch = (
self.wechselrichter.energie_verarbeiten(erzeugung, verbrauch, stunde)
)
# AC PV Battery Charge
if self.akku and self.ac_charge_hours[stunde] > 0.0:
self.akku.set_charge_allowed_for_hour(1, stunde)
geladene_menge, verluste_wh = self.akku.energie_laden(
None, stunde, relative_power=self.ac_charge_hours[stunde]
)
# print(stunde, " ", geladene_menge, " ",self.ac_charge_hours[stunde]," ",self.akku.ladezustand_in_prozent())
verbrauch += geladene_menge
netzbezug += geladene_menge
self.verluste_wh_pro_stunde[stunde_since_now] += verluste_wh
self.netzeinspeisung_wh_pro_stunde[stunde_since_now] = netzeinspeisung
self.netzbezug_wh_pro_stunde[stunde_since_now] = netzbezug
self.verluste_wh_pro_stunde[stunde_since_now] += verluste
self.last_wh_pro_stunde[stunde_since_now] = verbrauch
# Financial calculations
self.kosten_euro_pro_stunde[stunde_since_now] = (
netzbezug * self.strompreis_euro_pro_wh[stunde]
)
self.einnahmen_euro_pro_stunde[stunde_since_now] = (
netzeinspeisung * self.einspeiseverguetung_euro_pro_wh_arr[stunde]
)
# Akku SOC tracking
if self.akku:
self.akku_soc_pro_stunde[stunde_since_now] = self.akku.ladezustand_in_prozent()
else:
self.akku_soc_pro_stunde[stunde_since_now] = 0.0
def report_dict(self) -> Dict[str, Any]:
"""Provides devices simulation output as a dictionary."""
out: Dict[str, Optional[Union[np.ndarray, float]]] = {
"Last_Wh_pro_Stunde": self.last_wh_pro_stunde,
"Netzeinspeisung_Wh_pro_Stunde": self.netzeinspeisung_wh_pro_stunde,
"Netzbezug_Wh_pro_Stunde": self.netzbezug_wh_pro_stunde,
"Kosten_Euro_pro_Stunde": self.kosten_euro_pro_stunde,
"akku_soc_pro_stunde": self.akku_soc_pro_stunde,
"Einnahmen_Euro_pro_Stunde": self.einnahmen_euro_pro_stunde,
"Gesamtbilanz_Euro": self.total_balance_euro,
"EAuto_SoC_pro_Stunde": self.eauto_soc_pro_stunde,
"Gesamteinnahmen_Euro": self.total_revenues_euro,
"Gesamtkosten_Euro": self.total_costs_euro,
"Verluste_Pro_Stunde": self.verluste_wh_pro_stunde,
"Gesamt_Verluste": self.total_losses_wh,
"Home_appliance_wh_per_hour": self.home_appliance_wh_per_hour,
}
return out
# Initialize the Devices simulation, it is a singleton.
devices = Devices()
def get_devices() -> Devices:
"""Gets the EOS Devices simulation."""
return devices