EOS/flask_server.py
2024-05-01 10:02:16 +02:00

90 lines
2.8 KiB
Python

from flask import Flask, jsonify, request
import numpy as np
from modules.class_load import *
from modules.class_ems import *
from modules.class_pv_forecast import *
from modules.class_akku import *
from modules.class_strompreis import *
from modules.class_heatpump import *
from modules.class_load_container import *
from modules.class_sommerzeit import *
from modules.visualize import *
from modules.class_battery_soc_predictor import *
import os
from flask import Flask, send_from_directory
from pprint import pprint
import matplotlib
matplotlib.use('Agg') # Setzt das Backend auf Agg
import matplotlib.pyplot as plt
import string
from datetime import datetime
from deap import base, creator, tools, algorithms
from modules.class_optimize import *
import numpy as np
import random
import os
app = Flask(__name__)
opt_class = optimization_problem(prediction_hours=24, strafe=10)
soc_predictor = BatterySocPredictor.load_model('battery_model.pkl')
@app.route('/soc', methods=['GET'])
def flask_soc():
if request.method == 'GET':
# URL-Parameter lesen
voltage = request.args.get('voltage')
current = request.args.get('current')
# Erforderliche Parameter prüfen
if voltage is None or current is None:
missing_params = []
if voltage is None:
missing_params.append('voltage')
if current is None:
missing_params.append('current')
return jsonify({"error": f"Fehlende Parameter: {', '.join(missing_params)}"}), 400
# Werte in ein numpy Array umwandeln
x = np.array( [[float(voltage), float(current)]] )
# Simulation durchführen
ergebnis = soc_predictor.predict(x)
print(ergebnis)
return jsonify(ergebnis)
@app.route('/optimize', methods=['POST'])
def flask_optimize():
if request.method == 'POST':
parameter = request.json
# Erforderliche Parameter prüfen
erforderliche_parameter = [ 'pv_akku_cap', 'year_energy',"einspeiseverguetung_euro_pro_wh", 'max_heizleistung', 'pv_forecast_url', 'eauto_min_soc', "eauto_cap","eauto_charge_efficiency","eauto_charge_power","eauto_soc","pv_soc","start_solution","pvpowernow","haushaltsgeraet_dauer","haushaltsgeraet_wh"]
for p in erforderliche_parameter:
if p not in parameter:
return jsonify({"error": f"Fehlender Parameter: {p}"}), 400
# Simulation durchführen
ergebnis = opt_class.optimierung_ems(parameter=parameter, start_hour=datetime.now().hour)
return jsonify(ergebnis)
@app.route('/visualisierungsergebnisse.pdf')
def get_pdf():
return send_from_directory('', 'visualisierungsergebnisse.pdf')
if __name__ == '__main__':
app.run(debug=True, host="0.0.0.0")