Generate today's industry demand per ct and per sector

Only covers EU28 at the moment.

Uses the energy balances sheets from JRC-IDEES.

Snakefile

@@ -185,6 +185,13 @@ rule build_industrial_production_per_country_tomorrow:
     resources: mem_mb=1000
     script: 'scripts/build_industrial_production_per_country_tomorrow.py'
 
+rule build_industrial_energy_demand_per_country_today:
+    output:
+        industrial_energy_demand_per_country_today="resources/industrial_energy_demand_per_country_today.csv"
+    threads: 1
+    resources: mem_mb=1000
+    script: 'scripts/build_industrial_energy_demand_per_country_today.py'
+
 
 rule build_industrial_energy_demand_per_country:
     input:

scripts/build_industrial_energy_demand_per_country_today.py

@@ -0,0 +1,107 @@
+
+import pandas as pd
+
+# sub-sectors as used in PyPSA-Eur-Sec and listed in JRC-IDEES industry sheets
+sub_sectors = {'Iron and steel' : ['Integrated steelworks','Electric arc'],
+               'Non-ferrous metals' : ['Alumina production','Aluminium - primary production','Aluminium - secondary production','Other non-ferrous metals'],
+               'Chemicals' : ['Basic chemicals', 'Other chemicals', 'Pharmaceutical products etc.', 'Basic chemicals feedstock'],
+               'Non-metalic mineral' : ['Cement','Ceramics & other NMM','Glass production'],
+               'Printing' : ['Pulp production','Paper production','Printing and media reproduction'],
+               'Food' : ['Food, beverages and tobacco'],
+               'Transport equipment' : ['Transport Equipment'],
+               'Machinery equipment' : ['Machinery Equipment'],
+               'Textiles and leather' : ['Textiles and leather'],
+               'Wood and wood products' : ['Wood and wood products'],
+               'Other Industrial Sectors' : ['Other Industrial Sectors'],
+}
+
+
+# name in JRC-IDEES Energy Balances
+eb_sheet_name = {'Integrated steelworks' : 'cisb',
+                 'Electric arc' : 'cise',
+                 'Alumina production' : 'cnfa',
+                 'Aluminium - primary production' : 'cnfp',
+                 'Aluminium - secondary production' : 'cnfs',
+                 'Other non-ferrous metals' : 'cnfo',
+                 'Basic chemicals' : 'cbch',
+                 'Other chemicals' : 'coch',
+                 'Pharmaceutical products etc.' : 'cpha',
+                 'Basic chemicals feedstock' : 'cpch',
+                 'Cement' : 'ccem',
+                 'Ceramics & other NMM' : 'ccer',
+                 'Glass production' : 'cgla',
+                 'Pulp production' : 'cpul',
+                 'Paper production' : 'cpap',
+                 'Printing and media reproduction' : 'cprp',
+                 'Food, beverages and tobacco' : 'cfbt',
+                 'Transport Equipment' : 'ctre',
+                 'Machinery Equipment' : 'cmae',
+                 'Textiles and leather' : 'ctel',
+                 'Wood and wood products' : 'cwwp',
+                 'Mining and quarrying' : 'cmiq',
+                 'Construction' : 'ccon',
+                 'Non-specified': 'cnsi',
+}
+
+
+
+fuels = {'all' : ['All Products'],
+         'solid' : ['Solid Fuels'],
+         'liquid' : ['Total petroleum products (without biofuels)'],
+         'gas' : ['Gases'],
+         'heat' : ['Nuclear heat','Derived heat'],
+         'biomass' : ['Biomass and Renewable wastes'],
+         'waste' : ['Wastes (non-renewable)'],
+         'electricity' : ['Electricity'],
+}
+
+ktoe_to_twh = 0.011630
+
+eu28 = ['FR', 'DE', 'GB', 'IT', 'ES', 'PL', 'SE', 'NL', 'BE', 'FI',
+        'DK', 'PT', 'RO', 'AT', 'BG', 'EE', 'GR', 'LV', 'CZ',
+        'HU', 'IE', 'SK', 'LT', 'HR', 'LU', 'SI', 'CY', 'MT']
+
+jrc_names = {"GR" : "EL",
+             "GB" : "UK"}
+
+year = 2015
+summaries = {}
+
+#for some reason the Energy Balances list Other Industrial Sectors separately
+ois_subs = ['Mining and quarrying','Construction','Non-specified']
+
+
+
+for ct in eu28:
+    print(ct)
+    filename = 'data/jrc-idees-2015/JRC-IDEES-2015_EnergyBalance_{}.xlsx'.format(jrc_names.get(ct,ct))
+
+    summary = pd.DataFrame(index=list(fuels.keys()) + ['other'])
+
+    for sector in sub_sectors:
+        if sector == 'Other Industrial Sectors':
+            subs = ois_subs
+        else:
+            subs = sub_sectors[sector]
+
+        for sub in subs:
+            df = pd.read_excel(filename,
+                               sheet_name=eb_sheet_name[sub],
+                               index_col=0)
+
+            s = df[year].astype(float)
+
+            for fuel in fuels:
+                summary.at[fuel,sub] = s[fuels[fuel]].sum()
+                summary.at['other',sub] = summary.at['all',sub] - summary.loc[summary.index^['all','other'],sub].sum()
+
+    summary['Other Industrial Sectors'] = summary[ois_subs].sum(axis=1)
+    summary.drop(columns=ois_subs,inplace=True)
+
+    summaries[ct] = summary*ktoe_to_twh
+
+final_summary = pd.concat(summaries,axis=1)
+
+final_summary.index.name = 'TWh/a'
+
+final_summary.to_csv(snakemake.output.industrial_energy_demand_per_country_today)