SoC Schätzung / Gaussprozess hinzugefügt

flask_server.py

@@ -9,6 +9,7 @@ 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
@@ -27,6 +28,33 @@ 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'])
@@ -45,21 +73,6 @@ def flask_optimize():
         
         return jsonify(ergebnis)
 
-@app.route('/optimize_worst_case', methods=['POST'])
-def flask_optimize_worst_case():
-    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, worst_case=True)
-        
-        return jsonify(ergebnis)
 
 @app.route('/visualisierungsergebnisse.pdf')
 def get_pdf():