mirror of
https://github.com/Akkudoktor-EOS/EOS.git
synced 2025-04-19 00:45:22 +00:00
change default port to 3000
This commit is contained in:
Dominik Siebel
Daniel Molkentin
parent
a977f3cfd0
commit
eaa23e6824
2
.env
2
.env
@ -1,5 +1,5 @@
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EOS_VERSION=latest
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EOS_PORT=8000
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EOS_PORT=3000
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MARIADB_VERSION=11.1.6
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PYTHON_VERSION=3.12.6
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@ -6,8 +6,8 @@ from modules.class_ems import *
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from modules.class_pv_forecast import *
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from modules.class_akku import *
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from modules.class_strompreis import *
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from modules.class_heatpump import *
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from modules.class_load_container import *
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from modules.class_heatpump import *
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from modules.class_load_container import *
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from modules.class_sommerzeit import *
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from modules.class_soc_calc import *
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from modules.visualize import *
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@ -44,9 +44,9 @@ opt_class = optimization_problem(prediction_hours=prediction_hours, strafe=10, o
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# ###############
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# lf = LoadForecast(filepath=r'load_profiles.npz', year_energy=year_energy)
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# #leistung_haushalt = lf.get_daily_stats(date)[0,...] # Datum anpassen
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# leistung_haushalt = lf.get_stats_for_date_range(date_now,date)[0] # Nur Erwartungswert!
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# gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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# leistung_haushalt = lf.get_stats_for_date_range(date_now,date)[0] # Nur Erwartungswert!
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# gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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# gesamtlast.hinzufuegen("Haushalt", leistung_haushalt)
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# # ###############
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@ -54,7 +54,7 @@ opt_class = optimization_problem(prediction_hours=prediction_hours, strafe=10, o
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# # ##############
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# # leistung_wp = wp.simulate_24h(temperature_forecast)
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# # gesamtlast.hinzufuegen("Heatpump", leistung_wp)
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# last = gesamtlast.gesamtlast_berechnen()
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# print(last)
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# #print(specific_date_prices)
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@ -72,7 +72,7 @@ def flask_soc():
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voltage_low_threshold = 46.5 # 0% SoC
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current_low_threshold = 2 # Niedriger Strom für beide Zustände
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gap = 30 # Zeitlücke in Minuten zum Gruppieren von Maxima/Minima
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bat_capacity = 33 * 1000 / 48
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bat_capacity = 33 * 1000 / 48
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# Zeitpunkt X definieren
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zeitpunkt_x = (datetime.now() - timedelta(weeks=3)).strftime('%Y-%m-%d %H:%M:%S')
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@ -89,7 +89,7 @@ def flask_soc():
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processor.update_database_with_soc(soc_df)
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#processor.plot_data(last_points_100_df, last_points_0_df, soc_df)
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processor.disconnect_db()
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return jsonify("Done")
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@ -110,7 +110,7 @@ def flask_strompreis():
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# Die letzten X gemessenen Daten + gesamtlast Simple oder eine andere Schätung als Input
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# Daraus wird dann eine neuen Lastprognose erstellt welche korrigiert ist.
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# Input:
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# Input:
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@app.route('/gesamtlast', methods=['POST'])
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def flask_gesamtlast():
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# Daten aus dem JSON-Body abrufen
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@ -138,7 +138,7 @@ def flask_gesamtlast():
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# Remove timezone info after conversion
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measured_data['time'] = measured_data['time'].dt.tz_localize(None)
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# Instantiate LoadForecast and generate forecast data
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lf = LoadForecast(filepath=r'load_profiles.npz', year_energy=year_energy)
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@ -169,7 +169,7 @@ def flask_gesamtlast():
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leistung_haushalt = future_predictions['Adjusted Pred'].values
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# Instantiate Gesamtlast and add household power predictions
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gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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gesamtlast.hinzufuegen("Haushalt", leistung_haushalt)
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# ###############
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@ -177,7 +177,7 @@ def flask_gesamtlast():
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# ###############
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# leistung_wp = wp.simulate_24h(temperature_forecast)
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# gesamtlast.hinzufuegen("Heatpump", leistung_wp)
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# Calculate the total load
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last = gesamtlast.gesamtlast_berechnen()
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@ -235,7 +235,7 @@ def flask_gesamtlast():
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# leistung_haushalt = future_predictions['Adjusted Pred'].values
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# gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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# gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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# gesamtlast.hinzufuegen("Haushalt", leistung_haushalt)
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# # ###############
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@ -243,12 +243,12 @@ def flask_gesamtlast():
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# # ##############
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# # leistung_wp = wp.simulate_24h(temperature_forecast)
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# # gesamtlast.hinzufuegen("Heatpump", leistung_wp)
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# last = gesamtlast.gesamtlast_berechnen()
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# print(last)
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# return jsonify(last.tolist())
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@app.route('/gesamtlast_simple', methods=['GET'])
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def flask_gesamtlast_simple():
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if request.method == 'GET':
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@ -259,9 +259,9 @@ def flask_gesamtlast_simple():
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###############
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lf = LoadForecast(filepath=r'load_profiles.npz', year_energy=year_energy)
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#leistung_haushalt = lf.get_daily_stats(date)[0,...] # Datum anpassen
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leistung_haushalt = lf.get_stats_for_date_range(date_now,date)[0] # Nur Erwartungswert!
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gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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leistung_haushalt = lf.get_stats_for_date_range(date_now,date)[0] # Nur Erwartungswert!
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gesamtlast = Gesamtlast(prediction_hours=prediction_hours)
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gesamtlast.hinzufuegen("Haushalt", leistung_haushalt)
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# ###############
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@ -269,7 +269,7 @@ def flask_gesamtlast_simple():
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# ##############
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# leistung_wp = wp.simulate_24h(temperature_forecast)
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# gesamtlast.hinzufuegen("Heatpump", leistung_wp)
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last = gesamtlast.gesamtlast_berechnen()
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print(last)
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#print(specific_date_prices)
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@ -281,7 +281,7 @@ def flask_pvprognose():
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url = request.args.get("url")
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ac_power_measurement = request.args.get("ac_power_measurement")
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date_now,date = get_start_enddate(prediction_hours,startdate=datetime.now().date())
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###############
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# PV Forecast
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###############
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@ -290,7 +290,7 @@ def flask_pvprognose():
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if isfloat(ac_power_measurement):
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PVforecast.update_ac_power_measurement(date_time=datetime.now(), ac_power_measurement=float(ac_power_measurement) )
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#PVforecast.print_ac_power_and_measurement()
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pv_forecast = PVforecast.get_pv_forecast_for_date_range(date_now,date) #get_forecast_for_date(date)
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temperature_forecast = PVforecast.get_temperature_for_date_range(date_now,date)
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@ -303,7 +303,7 @@ def flask_pvprognose():
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def flask_optimize():
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if request.method == 'POST':
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parameter = request.json
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# Erforderliche Parameter prüfen
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erforderliche_parameter = [ 'preis_euro_pro_wh_akku','strompreis_euro_pro_wh', "gesamtlast",'pv_akku_cap', "einspeiseverguetung_euro_pro_wh", 'pv_forecast','temperature_forecast', 'eauto_min_soc', "eauto_cap","eauto_charge_efficiency","eauto_charge_power","eauto_soc","pv_soc","start_solution","haushaltsgeraet_dauer","haushaltsgeraet_wh"]
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for p in erforderliche_parameter:
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@ -312,7 +312,7 @@ def flask_optimize():
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# Simulation durchführen
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ergebnis = opt_class.optimierung_ems(parameter=parameter, start_hour=datetime.now().hour) # , startdate = datetime.now().date() - timedelta(days = 1)
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return jsonify(ergebnis)
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@ -350,7 +350,7 @@ def root():
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if __name__ == '__main__':
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try:
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host= os.getenv("FLASK_RUN_HOST", "0.0.0.0")
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port = os.getenv("FLASK_RUN_PORT", 5000)
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port = os.getenv("FLASK_RUN_PORT", 3000)
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app.run(debug=True, host=host, port=port)
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except:
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print(f"Coud not bind to host {host}:{port}, set FLASK_RUN_HOST and/or FLASK_RUN_PORT.")
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