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AC /DC / Discharge optimzation - First try (not finished yet)

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Andreas 2024-10-17 10:32:24 +02:00 committed by Andreas
parent 87ec02a90e
commit 7adf3d336a
4 changed files with 32 additions and 22 deletions
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9
src/akkudoktoreos/class_ems.py
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@ -25,6 +25,7 @@ class EnergieManagementSystem:
self.wechselrichter = wechselrichter
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)
def set_akku_discharge_hours(self, ds: List[int]) -> None:
self.akku.set_discharge_per_hour(ds)
@ -35,8 +36,8 @@ class EnergieManagementSystem:
def set_akku_dc_charge_hours(self, ds: np.ndarray) -> None:
self.dc_charge_hours = ds
def set_eauto_charge_hours(self, ds: List[int]) -> None:
self.eauto.set_charge_per_hour(ds)
def set_ev_charge_hours(self, ds: List[int]) -> None:
self.ev_charge_hours = ds
def set_haushaltsgeraet_start(self, ds: List[int], global_start_hour: int = 0) -> None:
self.haushaltsgeraet.set_startzeitpunkt(ds, global_start_hour=global_start_hour)
@ -95,7 +96,9 @@ class EnergieManagementSystem:
# E-Auto handling
if self.eauto:
geladene_menge_eauto, verluste_eauto = self.eauto.energie_laden(None, stunde)
geladene_menge_eauto, verluste_eauto = self.eauto.energie_laden(None, stunde, relative_power=self.ev_charge_hours[stunde])
# if self.ev_charge_hours[stunde] > 0.0:
# print(self.ev_charge_hours[stunde], " ", geladene_menge_eauto," ", self.eauto.ladezustand_in_prozent())
verbrauch += geladene_menge_eauto
verluste_wh_pro_stunde[stunde_since_now] += verluste_eauto
eauto_soc_pro_stunde[stunde_since_now] = self.eauto.ladezustand_in_prozent()

29
src/akkudoktoreos/class_optimize.py
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@ -241,8 +241,9 @@ class optimization_problem:
eautocharge_hours_float = [
possible_ev_charge_currents[i] for i in eautocharge_hours_index
]
ems.set_eauto_charge_hours(eautocharge_hours_float)
ems.set_ev_charge_hours(eautocharge_hours_float)
#else:
# ems.set_ev_charge_hours(np.full(self.prediction_hours, 0 ))
return ems.simuliere(start_hour)
def evaluate(
@ -271,10 +272,10 @@ class optimization_problem:
)
# Penalty for not meeting the minimum SOC (State of Charge) requirement
if parameter["eauto_min_soc"] - ems.eauto.ladezustand_in_prozent() <= 0.0:
gesamtbilanz += sum(
self.strafe for ladeleistung in eautocharge_hours_float if ladeleistung != 0.0
)
# if parameter["eauto_min_soc"] - ems.eauto.ladezustand_in_prozent() <= 0.0 and self.optimize_ev:
# gesamtbilanz += sum(
# self.strafe for ladeleistung in eautocharge_hours_float if ladeleistung != 0.0
# )
individual.extra_data = (
o["Gesamtbilanz_Euro"],
@ -284,13 +285,13 @@ class optimization_problem:
# Adjust total balance with battery value and penalties for unmet SOC
restwert_akku = ems.akku.aktueller_energieinhalt() * parameter["preis_euro_pro_wh_akku"]
gesamtbilanz += (
max(
0,
(parameter["eauto_min_soc"] - ems.eauto.ladezustand_in_prozent()) * self.strafe,
)
- restwert_akku
)
gesamtbilanz += -restwert_akku
if self.optimize_ev:
gesamtbilanz += max(
0,
(parameter["eauto_min_soc"] - ems.eauto.ladezustand_in_prozent()) * self.strafe,
)
return (gesamtbilanz,)
@ -342,7 +343,7 @@ class optimization_problem:
worst_case: bool = False,
startdate: Optional[Any] = None, # startdate is not used!
*,
ngen: int = 400,
ngen: int = 600,
) -> Dict[str, Any]:
"""
Perform EMS (Energy Management System) optimization and visualize results.

9
src/akkudoktoreos/visualize.py
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@ -164,9 +164,11 @@ def visualisiere_ergebnisse(
plt.legend(loc="upper left", bbox_to_anchor=(1, 1)) # Place legend outside the plot
plt.grid(True, which="both", axis="x") # Grid for every hour
# Plot for AC, DC charging, and Discharge status using bar charts
ax1 = plt.subplot(3, 2, 5)
hours = np.arange(0, prediction_hours)
# Plot AC charging as bars (relative values between 0 and 1)
plt.bar(hours, ac, width=0.4, label="AC Charging (relative)", color="blue", alpha=0.6)
@ -185,7 +187,10 @@ def visualisiere_ergebnisse(
ax1.grid(True)
if ist_dst_wechsel(datetime.datetime.now()):
hours = np.arange(start_hour, prediction_hours - 1)
else:
hours = np.arange(start_hour, prediction_hours)
pdf.savefig() # Save the current figure state to the PDF

7
src/akkudoktoreosserver/flask_server.py
View File

@ -17,6 +17,7 @@ from akkudoktoreos.class_load_container import Gesamtlast
from akkudoktoreos.class_load_corrector import LoadPredictionAdjuster
from akkudoktoreos.class_optimize import optimization_problem
from akkudoktoreos.class_pv_forecast import PVForecast
from akkudoktoreos.class_numpy_encoder import *
from akkudoktoreos.class_strompreis import HourlyElectricityPriceForecast
from akkudoktoreos.config import (
get_start_enddate,
@ -28,7 +29,7 @@ from akkudoktoreos.config import (
app = Flask(__name__)
opt_class = optimization_problem(
prediction_hours=prediction_hours, strafe=10, optimization_hours=optimization_hours
prediction_hours=prediction_hours, strafe=10, optimization_hours=optimization_hours, verbose=True
)
@ -248,9 +249,9 @@ def flask_optimize():
# Perform optimization simulation
result = opt_class.optimierung_ems(parameter=parameter, start_hour=datetime.now().hour)
print(result)
#print(result)
# convert to JSON (None accepted by dumps)
return jsonify(result)
return NumpyEncoder.dumps(result)
@app.route("/visualization_results.pdf")