EOS/src/akkudoktoreos/class_ems.py

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from datetime import datetime
from typing import Dict, List, Optional, Union
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import numpy as np
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from akkudoktoreos.config import prediction_hours
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class EnergieManagementSystem:
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def __init__(
self,
pv_prognose_wh: Optional[np.ndarray] = None,
strompreis_euro_pro_wh: Optional[np.ndarray] = None,
einspeiseverguetung_euro_pro_wh: Optional[np.ndarray] = None,
eauto: Optional[object] = None,
gesamtlast: Optional[np.ndarray] = None,
haushaltsgeraet: Optional[object] = None,
wechselrichter: Optional[object] = None,
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):
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self.akku = wechselrichter.akku
self.gesamtlast = gesamtlast
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self.pv_prognose_wh = pv_prognose_wh
self.strompreis_euro_pro_wh = strompreis_euro_pro_wh
self.einspeiseverguetung_euro_pro_wh = einspeiseverguetung_euro_pro_wh
self.eauto = eauto
self.haushaltsgeraet = haushaltsgeraet
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self.wechselrichter = wechselrichter
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self.ac_charge_hours = np.full(prediction_hours, 0)
self.dc_charge_hours = np.full(prediction_hours, 1)
self.ev_charge_hours = np.full(prediction_hours, 0)
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def set_akku_discharge_hours(self, ds: List[int]) -> None:
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self.akku.set_discharge_per_hour(ds)
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def set_akku_ac_charge_hours(self, ds: np.ndarray) -> None:
self.ac_charge_hours = ds
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def set_akku_dc_charge_hours(self, ds: np.ndarray) -> None:
self.dc_charge_hours = ds
def set_ev_charge_hours(self, ds: List[int]) -> None:
self.ev_charge_hours = ds
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def set_haushaltsgeraet_start(self, ds: List[int], global_start_hour: int = 0) -> None:
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self.haushaltsgeraet.set_startzeitpunkt(ds, global_start_hour=global_start_hour)
def reset(self) -> None:
self.eauto.reset()
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self.akku.reset()
def simuliere_ab_jetzt(self) -> dict:
jetzt = datetime.now()
start_stunde = jetzt.hour
return self.simuliere(start_stunde)
def simuliere(self, start_stunde: int) -> dict:
"""hour.
akku_soc_pro_stunde begin of the hour, initial hour state!
last_wh_pro_stunde integral of last hour (end state)
"""
lastkurve_wh = self.gesamtlast
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assert (
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len(lastkurve_wh) == len(self.pv_prognose_wh) == len(self.strompreis_euro_pro_wh)
), f"Array sizes do not match: Load Curve = {len(lastkurve_wh)}, PV Forecast = {len(self.pv_prognose_wh)}, Electricity Price = {len(self.strompreis_euro_pro_wh)}"
# Optimized total hours calculation
ende = len(lastkurve_wh)
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total_hours = ende - start_stunde
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# Pre-allocate arrays for the results, optimized for speed
last_wh_pro_stunde = np.full((total_hours), np.nan)
netzeinspeisung_wh_pro_stunde = np.full((total_hours), np.nan)
netzbezug_wh_pro_stunde = np.full((total_hours), np.nan)
kosten_euro_pro_stunde = np.full((total_hours), np.nan)
einnahmen_euro_pro_stunde = np.full((total_hours), np.nan)
akku_soc_pro_stunde = np.full((total_hours), np.nan)
eauto_soc_pro_stunde = np.full((total_hours), np.nan)
verluste_wh_pro_stunde = np.full((total_hours), np.nan)
haushaltsgeraet_wh_pro_stunde = np.full((total_hours), np.nan)
# Set initial state
akku_soc_pro_stunde[0] = self.akku.ladezustand_in_prozent()
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if self.eauto:
eauto_soc_pro_stunde[0] = self.eauto.ladezustand_in_prozent()
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for stunde in range(start_stunde, ende):
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stunde_since_now = stunde - start_stunde
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# Accumulate loads and PV generation
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verbrauch = self.gesamtlast[stunde]
verluste_wh_pro_stunde[stunde_since_now] = 0.0
if self.haushaltsgeraet:
ha_load = self.haushaltsgeraet.get_last_fuer_stunde(stunde)
verbrauch += ha_load
haushaltsgeraet_wh_pro_stunde[stunde_since_now] = ha_load
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# E-Auto handling
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if self.eauto and self.ev_charge_hours[stunde] > 0:
geladene_menge_eauto, verluste_eauto = self.eauto.energie_laden(
None, stunde, relative_power=self.ev_charge_hours[stunde]
)
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verbrauch += geladene_menge_eauto
verluste_wh_pro_stunde[stunde_since_now] += verluste_eauto
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if self.eauto:
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eauto_soc_pro_stunde[stunde_since_now] = self.eauto.ladezustand_in_prozent()
# Process inverter logic
erzeugung = self.pv_prognose_wh[stunde]
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self.akku.set_charge_allowed_for_hour(self.dc_charge_hours[stunde], stunde)
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netzeinspeisung, netzbezug, verluste, eigenverbrauch = (
self.wechselrichter.energie_verarbeiten(erzeugung, verbrauch, stunde)
)
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# AC PV Battery Charge
if self.ac_charge_hours[stunde] > 0.0:
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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())
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verbrauch += geladene_menge
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netzbezug += geladene_menge
verluste_wh_pro_stunde[stunde_since_now] += verluste_wh
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netzeinspeisung_wh_pro_stunde[stunde_since_now] = netzeinspeisung
netzbezug_wh_pro_stunde[stunde_since_now] = netzbezug
verluste_wh_pro_stunde[stunde_since_now] += verluste
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last_wh_pro_stunde[stunde_since_now] = verbrauch
# Financial calculations
kosten_euro_pro_stunde[stunde_since_now] = (
netzbezug * self.strompreis_euro_pro_wh[stunde]
)
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einnahmen_euro_pro_stunde[stunde_since_now] = (
netzeinspeisung * self.einspeiseverguetung_euro_pro_wh[stunde]
)
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# Akku SOC tracking
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akku_soc_pro_stunde[stunde_since_now] = self.akku.ladezustand_in_prozent()
# Total cost and return
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gesamtkosten_euro = np.nansum(kosten_euro_pro_stunde) - np.nansum(einnahmen_euro_pro_stunde)
# Prepare output dictionary
out: Dict[str, Union[np.ndarray, float]] = {
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"Last_Wh_pro_Stunde": last_wh_pro_stunde,
"Netzeinspeisung_Wh_pro_Stunde": netzeinspeisung_wh_pro_stunde,
"Netzbezug_Wh_pro_Stunde": netzbezug_wh_pro_stunde,
"Kosten_Euro_pro_Stunde": kosten_euro_pro_stunde,
"akku_soc_pro_stunde": akku_soc_pro_stunde,
"Einnahmen_Euro_pro_Stunde": einnahmen_euro_pro_stunde,
"Gesamtbilanz_Euro": gesamtkosten_euro,
"E-Auto_SoC_pro_Stunde": eauto_soc_pro_stunde,
"Gesamteinnahmen_Euro": np.nansum(einnahmen_euro_pro_stunde),
"Gesamtkosten_Euro": np.nansum(kosten_euro_pro_stunde),
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"Verluste_Pro_Stunde": verluste_wh_pro_stunde,
"Gesamt_Verluste": np.nansum(verluste_wh_pro_stunde),
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"Haushaltsgeraet_wh_pro_stunde": haushaltsgeraet_wh_pro_stunde,
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}
return out