class_ems: AC / DC Charging

class_optimize: Timing Bugs fixed
class_numpy_encoder: JSON Encoder with Numpy support
visualize: AC / DC / Discharge
test_class_ems_2: New Test for AC / DC charging decision

src/akkudoktoreos/visualize.py

@@ -18,8 +18,9 @@ def visualisiere_ergebnisse(
     pv_forecast,
     strompreise,
     ergebnisse,
-    discharge_hours,
-    laden_moeglich,
+    ac,  # AC charging allowed
+    dc,  # DC charging allowed
+    discharge,  # Discharge allowed
     temperature,
     start_hour,
     prediction_hours,
@@ -58,21 +59,7 @@ def visualisiere_ergebnisse(
         plt.grid(True)
         plt.legend()
 
-        # Electricity prices
-        hours_p = np.arange(0, len(strompreise))
-        plt.subplot(3, 2, 2)
-        plt.plot(
-            hours_p,
-            strompreise,
-            label="Electricity Price (€/Wh)",
-            color="purple",
-            marker="s",
-        )
-        plt.title("Electricity Prices")
-        plt.xlabel("Hour of the Day")
-        plt.ylabel("Price (€/Wh)")
-        plt.legend()
-        plt.grid(True)
+
 
         # PV forecast
         plt.subplot(3, 2, 3)
@@ -122,30 +109,48 @@ def visualisiere_ergebnisse(
 
         # Energy flow, grid feed-in, and grid consumption
         plt.subplot(3, 2, 1)
-        plt.plot(hours, ergebnisse["Last_Wh_pro_Stunde"], label="Load (Wh)", marker="o")
+        # Plot with transparency (alpha) and different linestyles
         plt.plot(
-            hours,
-            ergebnisse["Haushaltsgeraet_wh_pro_stunde"],
-            label="Household Device (Wh)",
-            marker="o",
+            hours, ergebnisse["Last_Wh_pro_Stunde"], label="Load (Wh)", marker="o", linestyle="-", alpha=0.8
         )
         plt.plot(
-            hours,
-            ergebnisse["Netzeinspeisung_Wh_pro_Stunde"],
-            label="Grid Feed-in (Wh)",
-            marker="x",
+            hours, ergebnisse["Haushaltsgeraet_wh_pro_stunde"], label="Household Device (Wh)", marker="o", linestyle="--", alpha=0.8
         )
         plt.plot(
-            hours,
-            ergebnisse["Netzbezug_Wh_pro_Stunde"],
-            label="Grid Consumption (Wh)",
-            marker="^",
+            hours, ergebnisse["Netzeinspeisung_Wh_pro_Stunde"], label="Grid Feed-in (Wh)", marker="x", linestyle=":", alpha=0.8
         )
-        plt.plot(hours, ergebnisse["Verluste_Pro_Stunde"], label="Losses (Wh)", marker="^")
+        plt.plot(
+            hours, ergebnisse["Netzbezug_Wh_pro_Stunde"], label="Grid Consumption (Wh)", marker="^", linestyle="-.", alpha=0.8
+        )
+        plt.plot(
+            hours, ergebnisse["Verluste_Pro_Stunde"], label="Losses (Wh)", marker="^", linestyle="-", alpha=0.8
+        )
+
+        # Title and labels
         plt.title("Energy Flow per Hour")
         plt.xlabel("Hour")
         plt.ylabel("Energy (Wh)")
+
+        # Show legend with a higher number of columns to avoid overlap
+        plt.legend(ncol=2)
+
+
+
+        # Electricity prices
+        hours_p = np.arange(0, len(strompreise))
+        plt.subplot(3, 2, 3)
+        plt.plot(
+            hours_p,
+            strompreise,
+            label="Electricity Price (€/Wh)",
+            color="purple",
+            marker="s",
+        )
+        plt.title("Electricity Prices")
+        plt.xlabel("Hour of the Day")
+        plt.ylabel("Price (€/Wh)")
         plt.legend()
+        plt.grid(True)
 
         # State of charge for batteries
         plt.subplot(3, 2, 2)
@@ -159,42 +164,30 @@ 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
 
-        ax1 = plt.subplot(3, 2, 3)
-        # Plot charge and discharge values
-        for hour, value in enumerate(discharge_hours):
-            # Determine color and label based on the value
-            if value > 0:  # Positive values (discharge)
-                color = "red"
-                label = "Discharge" if hour == 0 else ""
-            elif value < 0:  # Negative values (charge)
-                color = "blue"
-                label = "Charge" if hour == 0 else ""
+        # Plot for AC, DC charging, and Discharge status using bar charts
+        ax1 = plt.subplot(3, 2, 5)
 
-            else:
-                continue  # Skip zero values
+        # 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)
 
-            # Create colored areas with `axvspan`
-            ax1.axvspan(
-                hour,  # Start of the hour
-                hour + 1,  # End of the hour
-                ymin=0,  # Lower bound
-                ymax=abs(value) / 5 if value < 0 else value,  # Adjust height based on the value
-                color=color,
-                alpha=0.3,
-                label=label
-            )
+        # Plot DC charging as bars (relative values between 0 and 1)
+        plt.bar(hours + 0.4, dc, width=0.4, label="DC Charging (relative)", color="green", alpha=0.6)
 
+        # Plot Discharge as bars (0 or 1, binary values)
+        plt.bar(hours, discharge, width=0.4, label="Discharge Allowed", color="red", alpha=0.6, bottom=np.maximum(ac, dc))
 
         # Configure the plot
         ax1.legend(loc="upper left")
         ax1.set_xlim(0, prediction_hours)
         ax1.set_xlabel("Hour")
-        ax1.set_ylabel("Charge/Discharge Level")
-        ax1.set_title("Charge and Discharge Hours Overview")
+        ax1.set_ylabel("Relative Power (0-1) / Discharge (0 or 1)")
+        ax1.set_title("AC/DC Charging and Discharge Overview")
         ax1.grid(True)
 
 
 
+
+
         pdf.savefig()  # Save the current figure state to the PDF
         plt.close()  # Close the current figure to free up memory
 
@@ -219,7 +212,6 @@ def visualisiere_ergebnisse(
         )
         # Annotate costs
         for hour, value in enumerate(costs):
-            print(hour, " ", value)
             if value == None or np.isnan(value):
                 value=0
             axs[0].annotate(f'{value:.2f}', (hour, value), textcoords="offset points", xytext=(0,5), ha='center', fontsize=8, color='red')