Added functions to calculate transmission distances and assign transm…

…ission tech groups
OSeMOSYS · Oct 12, 2024 · cfac058 · cfac058
1 parent 89f646a
commit cfac058
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Showing 2 changed files with 130 additions and 14 deletions.
diff --git a/workflow/scripts/osemosys_global/transmission/constants.py b/workflow/scripts/osemosys_global/transmission/constants.py
@@ -64,4 +64,74 @@
     'TRNCHNJXCHNNM' : 'CHNWM',
     'TRNCHNLICHNNM' : 'CHNEM',
     'TRNCHNNICHNNM' : 'CHNWM',
-}
+}
+
+SUBSEA_LINES = [
+    'TRNAREXXINDWE',
+    'TRNAREXXIRNXX',
+    'TRNAUSQLPNGXX',
+    'TRNAUSTAAUSVI',
+    'TRNAUSWAIDNNU',
+    'TRNAUSWATLSXX',
+    'TRNBELXXGBRXX',
+    'TRNCANARCANNL',
+    'TRNCANNLGRLXX',
+    'TRNCANONUSARE',
+    'TRNCHNFUTWNXX',
+    'TRNCHNSDKORXX',
+    'TRNCHNSDPRKXX',
+    'TRNCYPXXEGYXX',
+    'TRNCYPXXGRCXX',
+    'TRNCYPXXISRXX',
+    'TRNCYPXXLBNXX',
+    'TRNCYPXXSYRXX',
+    'TRNCYPXXTURXX',
+    'TRNDEUXXGBRXX',
+    'TRNDEUXXNORXX',
+    'TRNDEUXXSWEXX',
+    'TRNDJIXXYEMXX',
+    'TRNDNKXXGBRXX',
+    'TRNDNKXXNLDXX',
+    'TRNDNKXXNORXX',
+    'TRNDNKXXSWEXX',
+    'TRNDZAXXESPXX',
+    'TRNDZAXXFRAXX',
+    'TRNDZAXXITAXX',
+    'TRNEGYXXGRCXX',
+    'TRNEGYXXJORXX',
+    'TRNEGYXXSAUXX',
+    'TRNERIXXSAUXX',
+    'TRNERIXXYEMXX',
+    'TRNESPXXMARXX',
+    'TRNESTXXFINXX',
+    'TRNFRAXXGBRXX',
+    'TRNFRAXXIRLXX',
+    'TRNGBRXXISLXX',
+    'TRNGBRXXNLDXX',
+    'TRNGBRXXNORXX',
+    'TRNGRCXXITAXX',
+    'TRNGRCXXLBYXX',
+    'TRNGRLXXISLXX',
+    'TRNIDNXXMYSXX',
+    'TRNIDNXXSGPXX',
+    'TRNINDSOLKAXX',
+    'TRNINDWEOMNXX',
+    'TRNINDWESAUXX',
+    'TRNIRNXXOMNXX',
+    'TRNITAXXMNEXX',
+    'TRNITAXXTUNXX',
+    'TRNJPNCEKORXX',
+    'TRNJPNHORUSFE',
+    'TRNJPNKYKORXX',
+    'TRNLBYXXMLTXX',
+    'TRNLTUXXSWEXX',
+    'TRNLVAXXSWEXX',
+    'TRNMARXXPRTXX',
+    'TRNMLTXXTUNXX',
+    'TRNMYSXXPHLXX',
+    'TRNNLDXXNORXX',
+    'TRNOMNXXPAKXX',
+    'TRNPOLXXSWEXX',
+    'TRNSAUXXSDNXX',
+    'TRNSOMXXYEMXX',
+    ]
diff --git a/workflow/scripts/osemosys_global/transmission/data.py b/workflow/scripts/osemosys_global/transmission/data.py
@@ -87,37 +87,62 @@ def format_gtd_planned(df):
 
     return df
 
-def correct_gtd_line_mapping(df_exist, df_plan, region_mapping_dict, 
-                             CUSTOM_TRN_BA_DICT_FROM, CUSTOM_TRN_BA_DICT_TO):
+def correct_gtd_data(df_exist, df_plan, region_mapping_dict, 
+                     CUSTOM_TRN_BA_DICT_FROM, CUSTOM_TRN_BA_DICT_TO):
 
     # Create df with unique transmission technologies from GTD.
     tech_exist = get_unique_technologies(df_exist)
     tech_plan = get_unique_technologies(df_plan)
     tech_trn_list = list(set(tech_exist + tech_plan)) 
-    df = pd.DataFrame(tech_trn_list, columns = ['TECHNOLOGY'])
-    
+    df = pd.DataFrame(tech_trn_list, columns = ['TECHNOLOGY_gtd'])
+
     # Map OG regions to GTD technologies.
-    df['From'], df['To'] = df['TECHNOLOGY'].str[3:8], df['TECHNOLOGY'].str[8:13]
+    df['From'], df['To'] = df['TECHNOLOGY_gtd'].str[3:8], df['TECHNOLOGY_gtd'].str[8:13]
     df['From'], df['To'] = df['From'].map(region_mapping_dict
                                           ), df['To'].map(region_mapping_dict)
 
     # For USA GTD regions that are larger than certain OG regions (MISO, PJM, SWPP),
     # as well as for the Nei Mongol region in China, assign custom OG regions as a 
     # best estimate for transmission landing points.
     df.loc[df['From'] == 'DUPLICATE', 
-           'From'] = df['TECHNOLOGY'].map(CUSTOM_TRN_BA_DICT_FROM)
+           'From'] = df['TECHNOLOGY_gtd'].map(CUSTOM_TRN_BA_DICT_FROM)
 
     df.loc[df['To'] == 'DUPLICATE', 
-           'To'] = df['TECHNOLOGY'].map(CUSTOM_TRN_BA_DICT_TO)
+           'To'] = df['TECHNOLOGY_gtd'].map(CUSTOM_TRN_BA_DICT_TO)
 
-    return df
+    df.set_index('TECHNOLOGY_gtd', inplace = True)
+
+    # Create corrected TECHNOLOGY entry
+    df['TECHNOLOGY'] = 'TRN' + df['From'] + df['To']
+
+    # Update original GTD df's with corrected entries
+    df_exist.set_index('TECHNOLOGY', inplace = True)
+    df_exist.update(df)
+    df_exist = df_exist.merge(df[['TECHNOLOGY']], left_index = True, 
+                              right_index = True).reset_index(drop = True)
+    df_exist = df_exist[df_exist['From'] != df_exist['To']]
+
+    df_plan.set_index('TECHNOLOGY', inplace = True)
+    df_plan.update(df)
+    df_plan = df_plan.merge(df[['TECHNOLOGY']], left_index = True, 
+                            right_index = True).reset_index(drop = True)   
+    df_plan = df_plan[df_plan['From'] != df_plan['To']]
+
+    # Group corrected GTD entries
+    df_exist = df_exist.groupby(['TECHNOLOGY', 'From', 'To']
+                                ).sum('VALUE').reset_index()
+
+    df_plan = df_plan.groupby(['TECHNOLOGY', 'From', 'To', 'YEAR']
+                                ).sum('VALUE').reset_index()
+
+    return df_exist, df_plan
 
-def calculate_transmission_distances(df_exist, df_plan, region_mapping_dict, 
-                                     CUSTOM_TRN_BA_DICT_FROM, CUSTOM_TRN_BA_DICT_TO, 
+def calculate_transmission_distances(df_exist_corrected, df_plan_corrected, 
                                      centerpoints_dict):
 
-    df = correct_gtd_line_mapping(df_exist, df_plan, region_mapping_dict,
-                                  CUSTOM_TRN_BA_DICT_FROM, CUSTOM_TRN_BA_DICT_TO)
+    # Create df with unique transmission technologies from corrected GTD data.
+    df = pd.concat([df_exist_corrected[['TECHNOLOGY', 'From', 'To']], 
+                    df_plan_corrected[['TECHNOLOGY', 'From', 'To']]]).drop_duplicates()
 
     for row in centerpoints_dict:
       df.loc[df['From'] == row['region'], 'From_lat'] = row['lat']
@@ -148,4 +173,25 @@ def set_break_even_distance(trn_param):
 
         n = n + 1
 
-    return n
+    return n
+
+def set_transmission_tech_groups(df_exist_corrected, df_plan_corrected, 
+                                 centerpoints_dict, trn_param, SUBSEA_LINES):
+
+    break_even_dist = set_break_even_distance(trn_param)
+    df = calculate_transmission_distances(df_exist_corrected, df_plan_corrected, 
+                                          centerpoints_dict)
+
+    df.loc[df['distance'] >= break_even_dist, 
+           'tech_group'] = 'HVDC'
+
+    df.loc[df['distance'] < break_even_dist, 
+           'tech_group'] = 'HVAC'
+
+    df.loc[df['TECHNOLOGY'].isin(SUBSEA_LINES) , 
+           'tech_group'] = 'HVDC_subsea'
+
+    tech_group_dict = dict(zip(df['TECHNOLOGY'], 
+                               df['tech_group']))
+
+    return tech_group_dict