Update openTEPES_OutputResults.py

openTEPES/openTEPES_OutputResults.py

@@ -1,5 +1,5 @@
 """
-Open Generation, Storage, and Transmission Operation and Expansion Planning Model with RES and ESS (openTEPES) - December 04, 2024
+Open Generation, Storage, and Transmission Operation and Expansion Planning Model with RES and ESS (openTEPES) - December 09, 2024
 """
 
 import time
@@ -1682,9 +1682,16 @@ def MarginalResults(DirName, CaseName, OptModel, mTEPES, pIndPlotOutput):
         if len(mTEPES.gc):
             sPSSTAR           = [(p,sc,st,ar) for p,sc,st,ar in mTEPES.ps*mTEPES.st*mTEPES.ar if mTEPES.pReserveMargin[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.pRatedMaxPowerElec[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.pDemandElecPeak[p,ar] * mTEPES.pReserveMargin[p,ar]]
             if len(sPSSTAR):
-                OutputResults = pd.Series(data=[mTEPES.pDuals["".join([f"eAdequacyReserveMargin_{p}_{sc}_{st}{ar}"])] for p,sc,st,ar in sPSSTAR], index=pd.Index(sPSSTAR))
+                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(_path+f'/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(_path+f'/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):
         OutputResults = pd.Series(data=[mTEPES.pDuals["".join([f"eMaxSystemEmission_{p}_{sc}_{st}{ar}"])] for p,sc,st,ar in sPSSTAR], index=pd.Index(sPSSTAR))
@@ -2082,7 +2089,7 @@ def Transformation1(df, _name):
     if sum(mTEPES.pReserveMargin[:,:]):
         if len(mTEPES.gc):
             sPSSTARGC           = [(p,sc,st,ar,gc) for p,sc,st,ar,gc in mTEPES.ps*mTEPES.st*mTEPES.ar*mTEPES.gc if gc in g2a[ar] and mTEPES.pReserveMargin[p,ar] and st == mTEPES.Last_st and sum(1 for gc in mTEPES.gc if gc in g2a[ar]) and sum(mTEPES.pRatedMaxPowerElec[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.pDemandElecPeak[p,ar] * mTEPES.pReserveMargin[p,ar]]
-            OutputToResRev      = pd.Series(data=[mTEPES.pDuals["".join([f"eAdequacyReserveMargin_{p}_{sc}_{st}{ar}"])]*mTEPES.pRatedMaxPowerElec[gc]*mTEPES.pAvailability[gc]() for p,sc,st,ar,gc in sPSSTARGC], index=pd.Index(sPSSTARGC))
+            OutputToResRev      = pd.Series(data=[mTEPES.pDuals["".join([f"eAdequacyReserveMarginElec_{p}_{sc}_{st}{ar}"])]*mTEPES.pRatedMaxPowerElec[gc]*mTEPES.pAvailability[gc]() for p,sc,st,ar,gc in sPSSTARGC], index=pd.Index(sPSSTARGC))
             ResRev              = pd.Series(data=[0.0 for gc in mTEPES.gc], index=mTEPES.gc, dtype='float64')
             if len(sPSSTARGC):
                 OutputToResRev /= 1e3