diff --git a/assume/units/powerplant.py b/assume/units/powerplant.py
index d13fa4ff..5614f271 100644
--- a/assume/units/powerplant.py
+++ b/assume/units/powerplant.py
@@ -63,7 +63,7 @@ def __init__(
         self.fuel_price = fuel_price
         if type(co2_price) is pd.Series and len(co2_price) == 1:
             co2_price = co2_price.item()
-        self.co2_price
+        self.co2_price = co2_price
         self.price_forecast = (
             pd.Series(0.0, index=self.index) if price_forecast.empty else price_forecast
         )
@@ -214,7 +214,7 @@ def calculate_energy_operational_window(
             "window": {"start": start, "end": end},
             "current_power": {
                 "power": previous_power,
-                "marginal_cost": self.calc_marginal_cost(
+                "marginal_cost": self.calc_marginal_cost_with_partial_eff(
                     power_output=previous_power,
                     timestep=start,
                 ),
diff --git a/assume/world.py b/assume/world.py
index 2f9476ac..aa558f66 100644
--- a/assume/world.py
+++ b/assume/world.py
@@ -283,21 +283,21 @@ def creator(container):
             else:
                 market_price_forecast = None
 
-            forecast_provider = ForecastProvider(
-                market_id=market_id,
-                price_forecast_df=market_price_forecast,
-                fuel_prices_df=fuel_prices_df,
-                vre_cf_df=vre_cf_df,
-                powerplants=powerplant_units,
-                demand_df=demand_df[f"demand_{market_id}"],
-            )
-            forecast_agent = RoleAgent(
-                self.container, suggested_aid=f"forecast_agent_{market_id}"
-            )
-            forecast_agent.add_role(forecast_provider)
-            self.forecast_providers[market_id] = forecast_provider
-
-            temp[market_id] = forecast_provider.price_forecast_df
+            # forecast_provider = ForecastProvider(
+            #     market_id=market_id,
+            #     price_forecast_df=market_price_forecast,
+            #     fuel_prices_df=fuel_prices_df,
+            #     vre_cf_df=vre_cf_df,
+            #     powerplants=powerplant_units,
+            #     demand_df=demand_df[f"demand_{market_id}"],
+            # )
+            # forecast_agent = RoleAgent(
+            #     self.container, suggested_aid=f"forecast_agent_{market_id}"
+            # )
+            # forecast_agent.add_role(forecast_provider)
+            # self.forecast_providers[market_id] = forecast_provider
+
+            # temp[market_id] = forecast_provider.price_forecast_df
 
         temp.to_csv(f"{path}/price_forecasts.csv", index=True)
 
diff --git a/examples/paper.py b/examples/paper.py
index d03949a5..1168f76a 100644
--- a/examples/paper.py
+++ b/examples/paper.py
@@ -56,8 +56,8 @@ def plot_and_save_results():
     ## Data preparation
     eom = df[df["name"] == "EOM"]
     ltm = df[df["name"] == "LTM_OTC"].reset_index()
-    ltm.loc[0, "average_cost"] = None
-    xticks = list(ltm["simulation"])
+    # ltm.loc[0, "average_cost"] = None
+    xticks = list(eom["simulation"])
     # xlabels = [f"{i}%" for i in range(0, 101, 10)]
     xlabels = ["EOM", "EOM + LTM"]
     plt.style.use("seaborn-v0_8")
@@ -65,14 +65,20 @@ def plot_and_save_results():
     fig, (ax1, ax2) = plt.subplots(2, 1)
     # Total Dispatch cost
     ax1.bar(eom["simulation"], eom["total_cost"], label="EOM")
-    ax1.bar(ltm["simulation"], ltm["total_cost"], bottom=eom["total_cost"], label="LTM")
+    eom_ltm = eom[eom.simulation == "ltm_case10"]
+    ax1.bar(
+        ltm["simulation"],
+        ltm["total_cost"],
+        bottom=eom_ltm["total_cost"],
+        label="LTM",
+    )
     ax1.set_ylabel("Total dispatch cost \n per market [mill. $€$]")
     ax1.set_xticks(xticks, xlabels)
     ax1.legend()
     # Total Average Cost
     ax2.scatter(eom["simulation"], eom["average_cost"], label="EOM")
     ax2.scatter(ltm["simulation"], ltm["average_cost"], label="LTM")
-    ax2.bar(ltm["simulation"], ltm["total_cost"] * 0)
+    ax2.bar(eom["simulation"], eom["total_cost"] * 0)
     ax2.set_ylabel("Average cost \n for each scenario [$€/MWh$]")
     # ax2.set_xlabel("Fraction of base load traded on LTM in percent")
     ax2.set_xlabel("Selected electricity market design")
@@ -134,5 +140,5 @@ def plot_and_save_results():
 
 
 if __name__ == "__main__":
-    run_cases()
+    # run_cases()
     plot_and_save_results()