diff --git a/openTEPES/openTEPES_InputData.py b/openTEPES/openTEPES_InputData.py
index f17bc58d..81fc9a61 100644
--- a/openTEPES/openTEPES_InputData.py
+++ b/openTEPES/openTEPES_InputData.py
@@ -621,7 +621,7 @@ def ProcessParameter(pDataFrame: pd.DataFrame, pTimeStep: int) -> pd.DataFrame:
     mTEPES.eb = mTEPES.gc | mTEPES.bc
 
     #%% inverse index load level to stage
-    pStageToLevel = pLevelToStage.reset_index().set_index(['Period','Scenario','Stage'])['Loadlevel']
+    pStageToLevel = pLevelToStage.reset_index().set_index(['Period','Scenario','Stage'])['LoadLevel']
     #Filter only valid indices
     pStageToLevel = pStageToLevel.loc[
         pStageToLevel.index.isin([(p, s, st) for (p, s) in mTEPES.ps for st in mTEPES.st]) &
@@ -2439,11 +2439,12 @@ def DetectInfeasibilities(mTEPES) -> None:
 
         # detecting reserve margin infeasibility
         for p,ar in mTEPES.p*mTEPES.ar:
-            if                          sum(mTEPES.pRatedMaxPowerElec[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g) < mTEPES.pDemandElecPeak[p,ar] * mTEPES.pReserveMargin[p,ar]:
-                raise ValueError('### Electricity reserve margin infeasibility ', p, ar, sum(mTEPES.pRatedMaxPowerElec[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g), mTEPES.pDemandElecPeak[p,ar] * mTEPES.pReserveMargin[p,ar])
+            if     sum(mTEPES.pRatedMaxPowerElec[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g) < mTEPES.pDemandElecPeak[p,ar] * mTEPES.pReserveMargin[p,ar]:
+                raise     ValueError('### Electricity reserve margin infeasibility ', p, ar, sum(mTEPES.pRatedMaxPowerElec[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g), mTEPES.pDemandElecPeak[p,ar] * mTEPES.pReserveMargin[p,ar])
 
-            if mTEPES.pIndHeat == 1 and sum(mTEPES.pRatedMaxPowerHeat[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g) < mTEPES.pDemandHeatPeak[p,ar] * mTEPES.pReserveMarginHeat[p,ar]:
-                raise ValueError('### Heat reserve margin infeasibility ',        p, ar, sum(mTEPES.pRatedMaxPowerHeat[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g), mTEPES.pDemandHeatPeak[p,ar] * mTEPES.pReserveMargin[p,ar])
+            if mTEPES.pIndHeat == 1:
+                if sum(mTEPES.pRatedMaxPowerHeat[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g) < mTEPES.pDemandHeatPeak[p,ar] * mTEPES.pReserveMarginHeat[p,ar]:
+                    raise ValueError('### Heat reserve margin infeasibility ',        p, ar, sum(mTEPES.pRatedMaxPowerHeat[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if (p,g) in mTEPES.pg and (ar,g) in mTEPES.a2g), mTEPES.pDemandHeatPeak[p,ar] * mTEPES.pReserveMargin[p,ar])
 
     DetectInfeasibilities(mTEPES)
 
diff --git a/openTEPES/openTEPES_OutputResults.py b/openTEPES/openTEPES_OutputResults.py
index 65f53252..ed5f15dc 100644
--- a/openTEPES/openTEPES_OutputResults.py
+++ b/openTEPES/openTEPES_OutputResults.py
@@ -1685,12 +1685,13 @@ def MarginalResults(DirName, CaseName, OptModel, mTEPES, pIndPlotOutput):
                 OutputResults = pd.Series(data=[mTEPES.pDuals["".join([f"eAdequacyReserveMarginElec_{p}_{sc}_{st}{ar}"])] for p,sc,st,ar in sPSSTAR], index=pd.Index(sPSSTAR))
                 OutputResults.to_frame(name='RM').reset_index().pivot_table(index=['level_0','level_1'], columns='level_3', values='RM').rename_axis(['Period', 'Scenario'], axis=0).rename_axis([None], axis=1).to_csv(f'{_path}/oT_Result_MarginalReserveMargin_{CaseName}.csv', sep=',')
 
-    if sum(mTEPES.pReserveMarginHeat[:,:]):
-        if len(mTEPES.gc):
-            sPSSTAR           = [(p,sc,st,ar) for p,sc,st,ar in mTEPES.ps*mTEPES.st*mTEPES.ar if mTEPES.pReserveMarginHeat[p,ar] and st == mTEPES.Last_st and sum(1 for g in mTEPES.g if g in g2a[ar]) and (p,sc,n) in mTEPES.psn and sum(mTEPES.pRatedMaxPowerHeat[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if g in g2a[ar] and g not in (mTEPES.gc or mTEPES.gd)) <= mTEPES.pDemandHeatPeak[p,ar] * mTEPES.pReserveMarginHeat[p,ar]]
-            if len(sPSSTAR):
-                OutputResults = pd.Series(data=[mTEPES.pDuals["".join([f"eAdequacyReserveMarginHeat_{p}_{sc}_{st}{ar}"])] for p,sc,st,ar in sPSSTAR], index=pd.Index(sPSSTAR))
-                OutputResults.to_frame(name='RM').reset_index().pivot_table(index=['level_0','level_1'], columns='level_3', values='RM').rename_axis(['Period', 'Scenario'], axis=0).rename_axis([None], axis=1).to_csv(f'{_path}/oT_Result_MarginalReserveMarginHeat_{CaseName}.csv', sep=',')
+    if mTEPES.pIndHeat == 1:
+        if sum(mTEPES.pReserveMarginHeat[:,:]):
+            if len(mTEPES.gc):
+                sPSSTAR           = [(p,sc,st,ar) for p,sc,st,ar in mTEPES.ps*mTEPES.st*mTEPES.ar if mTEPES.pReserveMarginHeat[p,ar] and st == mTEPES.Last_st and sum(1 for g in mTEPES.g if g in g2a[ar]) and (p,sc,n) in mTEPES.psn and sum(mTEPES.pRatedMaxPowerHeat[g] * mTEPES.pAvailability[g]() / (1.0-mTEPES.pEFOR[g]) for g in mTEPES.g if g in g2a[ar] and g not in (mTEPES.gc or mTEPES.gd)) <= mTEPES.pDemandHeatPeak[p,ar] * mTEPES.pReserveMarginHeat[p,ar]]
+                if len(sPSSTAR):
+                    OutputResults = pd.Series(data=[mTEPES.pDuals["".join([f"eAdequacyReserveMarginHeat_{p}_{sc}_{st}{ar}"])] for p,sc,st,ar in sPSSTAR], index=pd.Index(sPSSTAR))
+                    OutputResults.to_frame(name='RM').reset_index().pivot_table(index=['level_0','level_1'], columns='level_3', values='RM').rename_axis(['Period', 'Scenario'], axis=0).rename_axis([None], axis=1).to_csv(f'{_path}/oT_Result_MarginalReserveMarginHeat_{CaseName}.csv', sep=',')
 
     sPSSTAR           = [(p,sc,st,ar) for p,sc,st,ar in mTEPES.ps*mTEPES.st*mTEPES.ar if mTEPES.pEmission[p,ar] < math.inf and st == mTEPES.Last_st and (p,sc,n) in mTEPES.psn and sum(mTEPES.pEmissionVarCost[p,sc,na,g] for na,g in mTEPES.na*mTEPES.g if (ar,g) in mTEPES.a2g)]
     if len(sPSSTAR):