Merge pull request #118 from DeltaE/refactor-canada-us

Create Canada Equivalent Functions to USA Functions
DeltaE · Feb 4, 2022 · c8af7e6 · c8af7e6
2 parents 3873057 + 7a8fa0c
commit c8af7e6
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Showing 14 changed files with 397 additions and 877,125 deletions.
diff --git a/dataSources/techList_AUTO_GENERATED.csv b/dataSources/techList_AUTO_GENERATED.csv
diff --git a/scripts/EmissionActivityRatio.py b/scripts/EmissionActivityRatio.py
@@ -12,16 +12,24 @@ def main():
 
     ### EVERYTHING CURRENTLY MAPS TO MODE_OFOPERARION = 1
     ### EVERYTHING IS CO2 EMISSIONS
+
+    #write to a csv
+    dataOut = getCanEmissionActivityRatio()
+    dfUsa = getUsaEmissionActivityRatio()
+
+    dfOut = pd.DataFrame(dataOut,columns=['REGION','TECHNOLOGY','EMISSION','MODE_OF_OPERATION','YEAR','VALUE'])
+    dfOut = dfOut.append(dfUsa)
+    dfOut.to_csv('../src/data/EmissionActivityRatio.csv', index=False)
+
+def getCanEmissionActivityRatio():
+    # PURPOSE: Creates EmissionActivityRatio file from Canadian data
+    # INPUT:   N/A
+    # OUTPUT:  dataOut = Canadian Emission Activity Ratio data
 
-    # Parameters to print over
     continent = functions.getFromYaml('continent')
     canSubregions = functions.getFromYaml('regions_dict')['CAN'].keys() # Canadian subregions
     years = functions.getYears()
 
-    ###########################################
-    # Compile Emission Activity Ratio
-    ###########################################
-
     #read in raw emission activity values
     dfRaw = pd.read_csv('../dataSources/EmissionActivityRatioByTechnology.csv', index_col=0)
 
@@ -45,11 +53,7 @@ def main():
                 if tech in modeTwoTechs:
                     dataOut.append([continent, techName, 'CO2', 2, year, activityRatio])
 
-    #write to a csv
-    dfOut = pd.DataFrame(dataOut,columns=['REGION','TECHNOLOGY','EMISSION','MODE_OF_OPERATION','YEAR','VALUE'])
-    dfUsa = getUsaEmissionActivityRatio()
-    dfOut = dfOut.append(dfUsa)
-    dfOut.to_csv('../src/data/EmissionActivityRatio.csv', index=False)
+    return dataOut
 
 def getUsaEmissionActivityRatio():
     # PURPOSE: Creates EmissionActivityRatio file from USA data

diff --git a/scripts/RETags.py b/scripts/RETags.py
@@ -2,7 +2,7 @@
 import functions
 
 def main():
-    # PURPOSE: Creates otoole formatted RETagTechnology CSVs 
+    # PURPOSE: Creates otoole formatted RETagTechnology (renewable energy tag technology) CSVs 
     # INPUT: none
     # OUTPUT: none
 

diff --git a/scripts/ReserveMargin.py b/scripts/ReserveMargin.py
@@ -15,12 +15,66 @@ def main():
     # Model Parameters
     ###########################################
 
-    continent = functions.getFromYaml('continent')
+    #To include reserve margin in osemosys global naming scheme, we:
+    # Gave a value of 1 for all regions and years of reserve margin 
+    # assigned the regional reserve margin value to ELCCAN<subregion>01 in reserve margin tag fuel
+    # assign a value of one to all relevant PWR<technology>CAN<subregion>01
+
+    #write out all files
+    reserveMargin = getCanReserveMargin()
+    dfReserveMarginUsa = getUsaReserveMargin()
+
+    dfReserveMargin = pd.DataFrame(reserveMargin,columns=['REGION','YEAR','VALUE'])
+    dfReserveMargin = dfReserveMargin.append(dfReserveMarginUsa)
+    dfReserveMargin.to_csv('../src/data/ReserveMargin.csv', index=False)
+
+    reserveMarginTagFuel = getCanReserveMarginTagFuel()
+    dfReserveMarginFuelUsa = getUsaReserveMarginTagFuel()
+
+    dfReserveMarginFuel = pd.DataFrame(reserveMarginTagFuel,columns=['REGION','FUEL','YEAR','VALUE'])
+    dfReserveMarginFuel = dfReserveMarginFuel.append(dfReserveMarginFuelUsa)
+    dfReserveMarginFuel.to_csv('../src/data/ReserveMarginTagFuel.csv', index=False)
+
+    reserveMarginTagTech = getCanReserveMarginTagTechnology()
+    dfReserveMarginTechUsa = getUsaReserveMarginTagTechnology()
+
+    dfReserveMarginTech = pd.DataFrame(reserveMarginTagTech,columns=['REGION','TECHNOLOGY','YEAR','VALUE'])
+    dfReserveMarginTech = dfReserveMarginTech.append(dfReserveMarginTechUsa)
+    dfReserveMarginTech.to_csv('../src/data/ReserveMarginTagTechnology.csv', index=False)
+
+def getCanReserveMarginTagTechnology():
+    # PURPOSE: Creates getReserveMarginTagTechnology file from Canadian data
+    # INPUT:   N/A
+    # OUTPUT:  reserveMarginTagTech = Canadian Reserve Margin Tag Technology Data
+
     canSubregions = functions.getFromYaml('regions_dict')['CAN'] # Canadian subregions
-    seasons = functions.getFromYaml('seasons')
+    continent = functions.getFromYaml('continent')
     techTags = functions.getFromYaml('techs_master')
     variableTechs = functions.getFromYaml('variable_techs')
     years = functions.getYears()
+
+    # Make list of techs to tag by removing the non-dispachable techs from techTags
+    techTags = [x for x in techTags if x not in variableTechs]
+
+    #reserve margin Tag Technology = Region, Technology, Year, Value
+    reserveMarginTagTech = []
+    for subregion in canSubregions:
+        for year in years:
+            for tech in techTags:
+                techName = 'PWR' + tech + 'CAN' + subregion + '01'
+                reserveMarginTagTech.append([continent, techName, year, 1])
+
+    return reserveMarginTagTech
+
+def getCanReserveMarginTagFuel():
+    # PURPOSE: Creates ReserveMarginTagFuel file from Canadian data
+    # INPUT:   N/A
+    # OUTPUT:  reserveMarginTagFuel = Canadian Reserve Margin Tag Fuel Data
+
+    continent = functions.getFromYaml('continent')
+    canSubregions = functions.getFromYaml('regions_dict')['CAN'] # Canadian subregions
+    seasons = functions.getFromYaml('seasons')
+    years = functions.getYears()
 
     # holds baseline reserve margin for each province based on NERC
     # 10 percent for hydro dominated provinces
@@ -40,9 +94,6 @@ def main():
     # List of fuels to tag
     # fuelTag = ['ELC']
 
-    # Make list of techs to tag by removing the non-dispachable techs from techTags
-    techTags = [x for x in techTags if x not in variableTechs]
-
     #For timeslicing 
     hours = range(1,25)
 
@@ -128,16 +179,6 @@ def main():
             #save adjusted regional reserve margin
             reserveMarginRaw.append([subregion, year, regionReserveMargin])
 
-    #To include reserve margin in osemosys global naming scheme, we:
-    # Gave a value of 1 for all regions and years of reserve margin 
-    # assigned the regional reserve margin value to ELCCAN<subregion>01 in reserve margin tag fuel
-    # assign a value of one to all relevant PWR<technology>CAN<subregion>01
-
-    #Reserve Margin = Region, year, value
-    reserveMargin = []
-    for year in years:
-        reserveMargin.append([continent, year, 1])
-
     #reserve margin Tag Fuel = Region, Fuel, Year, Value
     reserveMarginTagFuel = []
     for i in range(len(reserveMarginRaw)):
@@ -147,29 +188,22 @@ def main():
         rm = round(rm,3)
         reserveMarginTagFuel.append([continent, fuelName, year, rm])
 
-    #reserve margin Tag Technology = Region, Technology, Year, Value
-    reserveMarginTagTech = []
-    for subregion in canSubregions:
-        for year in years:
-            for tech in techTags:
-                techName = 'PWR' + tech + 'CAN' + subregion + '01'
-                reserveMarginTagTech.append([continent, techName, year, 1])
+    return reserveMarginTagFuel
 
-    #write out all files
-    dfReserveMargin = pd.DataFrame(reserveMargin,columns=['REGION','YEAR','VALUE'])
-    dfReserveMarginUsa = getUsaReserveMargin()
-    dfReserveMargin = dfReserveMargin.append(dfReserveMarginUsa)
-    dfReserveMargin.to_csv('../src/data/ReserveMargin.csv', index=False)
+def getCanReserveMargin():
+    # PURPOSE: Creates ReserveMargin file from Canadian data
+    # INPUT:   N/A
+    # OUTPUT:  reserveMargin = Base Reserve Margin Data
 
-    dfReserveMarginFuel = pd.DataFrame(reserveMarginTagFuel,columns=['REGION','FUEL','YEAR','VALUE'])
-    dfReserveMarginFuelUsa = getUsaReserveMarginTagFuel()
-    dfReserveMarginFuel = dfReserveMarginFuel.append(dfReserveMarginFuelUsa)
-    dfReserveMarginFuel.to_csv('../src/data/ReserveMarginTagFuel.csv', index=False)
+    continent = functions.getFromYaml('continent')
+    years = functions.getYears()
 
-    dfReserveMarginTech = pd.DataFrame(reserveMarginTagTech,columns=['REGION','TECHNOLOGY','YEAR','VALUE'])
-    dfReserveMarginTechUsa = getUsaReserveMarginTagTechnology()
-    dfReserveMarginTech = dfReserveMarginTech.append(dfReserveMarginTechUsa)
-    dfReserveMarginTech.to_csv('../src/data/ReserveMarginTagTechnology.csv', index=False)
+    #Reserve Margin = Region, year, value
+    reserveMargin = []
+    for year in years:
+        reserveMargin.append([continent, year, 1])
+
+    return reserveMargin
 
 def getUsaReserveMarginTagTechnology():
     # PURPOSE: Creates getReserveMarginTagTechnology file from USA data
@@ -325,7 +359,7 @@ def getUsaReserveMarginTagFuel():
     return dfOut
 
 def getUsaReserveMargin():
-    # PURPOSE: Creates ReserveMargin file
+    # PURPOSE: Creates ReserveMargin file from USA data
     # INPUT:   N/A
     # OUTPUT:  dfOut = dataframe to be written to a csv