Merge branch 'PyPSA:master' into master

.gitignore

@@ -46,6 +46,7 @@ data/costs_*.csv
 
 dask-worker-space/
 publications.jrc.ec.europa.eu/
+d1gam3xoknrgr2.cloudfront.net/
 
 *.org
 

.pre-commit-config.yaml

@@ -17,7 +17,7 @@ repos:
 
   # Sort package imports alphabetically
 - repo: https://github.com/PyCQA/isort
-  rev: 5.12.0
+  rev: 5.13.0
   hooks:
   - id: isort
     args: ["--profile", "black", "--filter-files"]

README.md

@@ -61,9 +61,9 @@ The dataset consists of:
 
 - A grid model based on a modified [GridKit](https://github.com/bdw/GridKit)
   extraction of the [ENTSO-E Transmission System
-  Map](https://www.entsoe.eu/data/map/). The grid model contains 6763 lines
+  Map](https://www.entsoe.eu/data/map/). The grid model contains 7072 lines
   (alternating current lines at and above 220kV voltage level and all high
-  voltage direct current lines) and 3642 substations.
+  voltage direct current lines) and 3803 substations.
 - The open power plant database
   [powerplantmatching](https://github.com/FRESNA/powerplantmatching).
 - Electrical demand time series from the

config/config.default.yaml

@@ -18,8 +18,6 @@ remote:
   ssh: ""
   path: ""
 
-focus_weights: false
-
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#run
 run:
   name: ""
@@ -88,7 +86,7 @@ co2_budget:
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#electricity
 electricity:
-  voltages: [220., 300., 380.]
+  voltages: [220., 300., 380., 500., 750.]
   gaslimit: false
   co2limit: 7.75e+7
   co2base: 1.487e+9
@@ -137,14 +135,14 @@ atlite:
       # module: era5
     europe-2013-era5:
       module: era5 # in priority order
-      x: [-12., 35.]
+      x: [-12., 42.]
       y: [33., 72]
       dx: 0.3
       dy: 0.3
       time: ['2013', '2013']
     europe-2013-sarah:
       module: [sarah, era5] # in priority order
-      x: [-12., 45.]
+      x: [-12., 42.]
       y: [33., 65]
       dx: 0.2
       dy: 0.2
@@ -237,10 +235,13 @@ lines:
     220.: "Al/St 240/40 2-bundle 220.0"
     300.: "Al/St 240/40 3-bundle 300.0"
     380.: "Al/St 240/40 4-bundle 380.0"
+    500.: "Al/St 240/40 4-bundle 380.0"
+    750.: "Al/St 560/50 4-bundle 750.0"
   s_max_pu: 0.7
   s_nom_max: .inf
   max_extension: .inf
   length_factor: 1.25
+  reconnect_crimea: true
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
   dynamic_line_rating:
     activate: false
@@ -449,6 +450,7 @@ sector:
   methanation: true
   helmeth: false
   coal_cc: false
+  coal_for_industry_cc: false
   dac: true
   co2_vent: false
   central_heat_vent: false
@@ -597,6 +599,7 @@ costs:
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#clustering
 clustering:
+  focus_weights: false
   simplify_network:
     to_substations: false
     algorithm: kmeans # choose from: [hac, kmeans]
@@ -722,6 +725,7 @@ plotting:
     H2: "Hydrogen Storage"
     lines: "Transmission Lines"
     ror: "Run of River"
+    load: "Load Shedding"
     ac: "AC"
     dc: "DC"
 
@@ -988,3 +992,4 @@ plotting:
     DC: "#8a1caf"
     DC-DC: "#8a1caf"
     DC link: "#8a1caf"
+    load: "#dd2e23"

config/config.entsoe-all.yaml

@@ -0,0 +1,43 @@
+# SPDX-FileCopyrightText: 2017-2023 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+run:
+  name: "entsoe-all"
+  disable_progressbar: true
+  shared_resources: false
+  shared_cutouts: true
+
+scenario:
+  simpl:
+  - ''
+  ll:
+  - vopt
+  clusters:
+  - 39
+  - 128
+  - 256
+  opts:
+  - ''
+  sector_opts:
+  - ''
+  planning_horizons:
+  - ''
+
+# TODO add Turkey (TR)
+countries: ['AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MD', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK', 'UA']
+
+electricity:
+  custom_powerplants: true
+  co2limit: 9.59e+7
+  co2base: 1.918e+9
+
+lines:
+  reconnect_crimea: true
+
+enable:
+  retrieve: true
+  retrieve_databundle: true
+  retrieve_sector_databundle: false
+  retrieve_cost_data: true
+  retrieve_cutout: true

data/GDP_PPP_30arcsec_v3_mapped_default.csv

@@ -0,0 +1,151 @@
+name,GDP_PPP,country
+3140,632728.0438507323,MD
+3139,806541.9318093687,MD
+3142,1392454.6690911907,MD
+3152,897871.2903553953,MD
+3246,645554.8588933202,MD
+7049,1150156.4449477682,MD
+1924,162285.16792916053,UA
+1970,751970.6071848695,UA
+2974,368873.75840156944,UA
+2977,294847.85539198935,UA
+2979,197988.13680768458,UA
+2980,301371.2491126519,UA
+3031,56925.21878805953,UA
+3032,139395.18279351242,UA
+3033,145377.8061037629,UA
+3035,52282.83655208812,UA
+3036,497950.25890516065,UA
+3037,1183293.1987702171,UA
+3038,255005.98207636533,UA
+3039,224711.50098325178,UA
+3040,342959.943226467,UA
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+3045,246273.65986119965,UA
+3047,146742.08407299497,UA
+3049,107265.7028733467,UA
+3050,1126147.985259493,UA
+3051,69833.56303043803,UA
+3052,67230.88206577855,UA
+3053,27019.224685201345,UA
+3054,260571.47337292184,UA
+3055,88760.94152915622,UA
+3056,101368.26196568517,UA
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+3062,358411.291265149,UA
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+4362,165753.82588729708,UA
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+4366,272003.25510057947,UA
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+4374,985354.331818515,UA
+4377,230805.08833664874,UA
+4382,125670.67125287943,UA
+4383,46914.065511740075,UA
+4384,48020.804310510954,UA
+4385,55612.34707641123,UA
+4387,74558.3475791577,UA
+4388,245243.33449409154,UA
+4389,95696.56767732685,UA
+4391,251085.7523045193,UA
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+7031,42001.73757065917,UA
+7059,159790.48382874,UA
+7063,39599.10564971086,UA

data/custom_powerplants.csv

@@ -1 +1,37 @@
-Name,Fueltype,Technology,Set,Country,Capacity,Efficiency,Duration,Volume_Mm3,DamHeight_m,YearCommissioned,Retrofit,lat,lon,projectID,YearDecommissioning
+,Name,Fueltype,Technology,Set,Country,Capacity,Efficiency,Duration,Volume_Mm3,DamHeight_m,StorageCapacity_MWh,DateIn,DateRetrofit,DateMothball,DateOut,lat,lon,EIC,projectID
+1266,Khmelnitskiy,Nuclear,,PP,UA,1901.8916595755832,,0.0,0.0,0.0,0.0,1988.0,2005.0,,,50.3023,26.6466,[nan],"{'GEO': ['GEO3842'], 'GPD': ['WRI1005111'], 'CARMA': ['CARMA22000']}"
+1268,Kaniv,Hydro,Reservoir,PP,UA,452.1656050955414,,0.0,0.0,0.0,0.0,1972.0,2003.0,,,49.76653,31.47165,[nan],"{'GEO': ['GEO43017'], 'GPD': ['WRI1005122'], 'CARMA': ['CARMA21140']}"
+1269,Kahovska kakhovka,Hydro,Reservoir,PP,UA,352.45222929936307,,0.0,0.0,0.0,0.0,1955.0,1956.0,,,46.77858,33.36965,[nan],"{'GEO': ['GEO43018'], 'GPD': ['WRI1005118'], 'CARMA': ['CARMA20855']}"
+1347,Kharkiv,Natural Gas,Steam Turbine,CHP,UA,494.94274967602314,,0.0,0.0,0.0,0.0,1979.0,1980.0,,,49.9719,36107,[nan],"{'GEO': ['GEO43027'], 'GPD': ['WRI1005126'], 'CARMA': ['CARMA21972']}"
+1348,Kremenchuk,Hydro,Reservoir,PP,UA,617.0382165605096,,0.0,0.0,0.0,0.0,1959.0,1960.0,,,49.07759,33.2505,[nan],"{'GEO': ['GEO43019'], 'GPD': ['WRI1005121'], 'CARMA': ['CARMA23072']}"
+1377,Krivorozhskaya,Hard Coal,Steam Turbine,PP,UA,2600.0164509342876,,0.0,0.0,0.0,0.0,1965.0,1992.0,,,47.5432,33.6583,[nan],"{'GEO': ['GEO42989'], 'GPD': ['WRI1005100'], 'CARMA': ['CARMA23176']}"
+1407,Zmiyevskaya zmiivskaya,Hard Coal,Steam Turbine,PP,UA,2028.3816283884514,,0.0,0.0,0.0,0.0,1960.0,2005.0,,,49.5852,36.5231,[nan],"{'GEO': ['GEO42999'], 'GPD': ['WRI1005103'], 'CARMA': ['CARMA51042']}"
+1408,Pridneprovskaya,Hard Coal,Steam Turbine,CHP,UA,1627.3152609570984,,0.0,0.0,0.0,0.0,1959.0,1966.0,,,48.4051,35.1131,[nan],"{'GEO': ['GEO42990'], 'GPD': ['WRI1005102'], 'CARMA': ['CARMA35874']}"
+1409,Kurakhovskaya,Hard Coal,Steam Turbine,PP,UA,1371.0015824607397,,0.0,0.0,0.0,0.0,1972.0,2003.0,,,47.9944,37.24022,[nan],"{'GEO': ['GEO42994'], 'GPD': ['WRI1005104'], 'CARMA': ['CARMA23339']}"
+1410,Dobrotvorsky,Hard Coal,Steam Turbine,PP,UA,553.1949895604868,,0.0,0.0,0.0,0.0,1960.0,1964.0,,,50.2133,24375,[nan],"{'GEO': ['GEO42992'], 'GPD': ['WRI1005096'], 'CARMA': ['CARMA10971']}"
+1422,Zuyevskaya,Hard Coal,Steam Turbine,PP,UA,1147.87960333801,,0.0,0.0,0.0,0.0,1982.0,2007.0,,,48.0331,38.28615,[nan],"{'GEO': ['GEO42995'], 'GPD': ['WRI1005106'], 'CARMA': ['CARMA51083']}"
+1423,Zaporozhye,Nuclear,,PP,UA,5705.67497872675,,0.0,0.0,0.0,0.0,1985.0,1996.0,,,47.5119,34.5863,[nan],"{'GEO': ['GEO6207'], 'GPD': ['WRI1005114'], 'CARMA': ['CARMA50875']}"
+1424,Trypilska,Hard Coal,Steam Turbine,PP,UA,1659.5849686814602,,0.0,0.0,0.0,0.0,1969.0,1972.0,,,50.1344,30.7468,[nan],"{'GEO': ['GEO43000'], 'GPD': ['WRI1005099'], 'CARMA': ['CARMA46410']}"
+1425,Tashlyk,Hydro,Pumped Storage,Store,UA,285.55968954109585,,0.0,0.0,0.0,0.0,2006.0,2007.0,,,47.7968,31.1811,[nan],"{'GEO': ['GEO43025'], 'GPD': ['WRI1005117'], 'CARMA': ['CARMA44696']}"
+1426,Starobeshivska,Hard Coal,Steam Turbine,PP,UA,1636.5351774497733,,0.0,0.0,0.0,0.0,1961.0,1967.0,,,47.7997,38.00612,[nan],"{'GEO': ['GEO43003'], 'GPD': ['WRI1005105'], 'CARMA': ['CARMA43083']}"
+1427,South,Nuclear,,PP,UA,2852.837489363375,,0.0,0.0,0.0,0.0,1983.0,1989.0,,,47812,31.22,[nan],"{'GEO': ['GEO5475'], 'GPD': ['WRI1005113'], 'CARMA': ['CARMA42555']}"
+1428,Rovno rivne,Nuclear,,PP,UA,2695.931427448389,,0.0,0.0,0.0,0.0,1981.0,2006.0,,,51.3245,25.89744,[nan],"{'GEO': ['GEO5174'], 'GPD': ['WRI1005112'], 'CARMA': ['CARMA38114']}"
+1429,Ladyzhinska,Hard Coal,Steam Turbine,PP,UA,1659.5849686814602,,0.0,0.0,0.0,0.0,1970.0,1971.0,,,48706,29.2202,[nan],"{'GEO': ['GEO42993'], 'GPD': ['WRI1005098'], 'CARMA': ['CARMA24024']}"
+1430,Kiev,Hydro,Pumped Storage,PP,UA,635.8694635681177,,0.0,0.0,0.0,0.0,1964.0,1972.0,,,50.5998,30501,"[nan, nan]","{'GEO': ['GEO43024', 'GEO43023'], 'GPD': ['WRI1005123', 'WRI1005124'], 'CARMA': ['CARMA23516', 'CARMA23517']}"
+2450,Cet chisinau,Natural Gas,,PP,MD,306.0,,0.0,0.0,0.0,0.0,,,,,47.027550000000005,28.8801,"[nan, nan]","{'GPD': ['WRI1002985', 'WRI1002984'], 'CARMA': ['CARMA8450', 'CARMA8451']}"
+2460,Hydropower che costesti,Hydro,,PP,MD,16.0,,0.0,0.0,0.0,0.0,1978.0,,,,47.8381,27.2246,[nan],"{'GPD': ['WRI1002987'], 'CARMA': ['CARMA9496']}"
+2465,Moldavskaya gres,Hard Coal,,PP,MD,2520.0,,0.0,0.0,0.0,0.0,,,,,46.6292,29.9407,[nan],"{'GPD': ['WRI1002989'], 'CARMA': ['CARMA28979']}"
+2466,Hydropower dubasari,Hydro,,PP,MD,48.0,,0.0,0.0,0.0,0.0,,,,,47.2778,29123,[nan],"{'GPD': ['WRI1002988'], 'CARMA': ['CARMA11384']}"
+2676,Cet nord balti,Natural Gas,,PP,MD,24.0,,0.0,0.0,0.0,0.0,,,,,47.7492,27.8938,[nan],"{'GPD': ['WRI1002986'], 'CARMA': ['CARMA3071']}"
+2699,Dniprodzerzhynsk,Hydro,Reservoir,PP,UA,360.3503184713376,,0.0,0.0,0.0,0.0,1963.0,1964.0,,,48.5485,34.541015,[nan],"{'GEO': ['GEO43020'], 'GPD': ['WRI1005119']}"
+2707,Burshtynska tes,Hard Coal,Steam Turbine,PP,UA,2212.779958241947,,0.0,0.0,0.0,0.0,1965.0,1984.0,,,49.21038,24.66654,[nan],"{'GEO': ['GEO42991'], 'GPD': ['WRI1005097']}"
+2708,Danipro dnieper,Hydro,Reservoir,PP,UA,1484.8407643312103,,0.0,0.0,0.0,0.0,1932.0,1947.0,,,47.86944,35.08611,[nan],"{'GEO': ['GEO43016'], 'GPD': ['WRI1005120']}"
+2709,Dniester,Hydro,Pumped Storage,Store,UA,612.7241020616891,,0.0,0.0,0.0,0.0,2009.0,2011.0,,,48.51361,27.47333,[nan],"{'GEO': ['GEO43022'], 'GPD': ['WRI1005116', 'WRI1005115']}"
+2710,Kiev,Natural Gas,Steam Turbine,CHP,UA,458.2803237740955,,0.0,0.0,0.0,0.0,1982.0,1984.0,,,50532,30.6625,[nan],"{'GEO': ['GEO42998'], 'GPD': ['WRI1005125']}"
+2712,Luganskaya,Hard Coal,Steam Turbine,PP,UA,1060.2903966575996,,0.0,0.0,0.0,0.0,1962.0,1969.0,,,48.74781,39.2624,[nan],"{'GEO': ['GEO42996'], 'GPD': ['WRI1005110']}"
+2713,Slavyanskaya,Hard Coal,Steam Turbine,PP,UA,737.5933194139823,,0.0,0.0,0.0,0.0,1971.0,1971.0,,,48872,37.76567,[nan],"{'GEO': ['GEO43002'], 'GPD': ['WRI1005109']}"
+2714,Vuhlehirska uglegorskaya,Hard Coal,Steam Turbine,PP,UA,3319.1699373629203,,0.0,0.0,0.0,0.0,1972.0,1977.0,,,48.4633,38.20328,[nan],"{'GEO': ['GEO43001'], 'GPD': ['WRI1005107']}"
+2715,Zaporiska,Hard Coal,Steam Turbine,PP,UA,3319.1699373629203,,0.0,0.0,0.0,0.0,1972.0,1977.0,,,47.5089,34.6253,[nan],"{'GEO': ['GEO42988'], 'GPD': ['WRI1005101']}"
+3678,Mironovskaya,Hard Coal,,PP,UA,815.0,,0.0,0.0,0.0,0.0,,,,,48.3407,38.4049,[nan],"{'GPD': ['WRI1005108'], 'CARMA': ['CARMA28679']}"
+3679,Kramatorskaya,Hard Coal,,PP,UA,120.0,,0.0,0.0,0.0,0.0,1974.0,,,,48.7477,37.5723,[nan],"{'GPD': ['WRI1075856'], 'CARMA': ['CARMA54560']}"
+3680,Chernihiv,Hard Coal,,PP,UA,200.0,,0.0,0.0,0.0,0.0,1968.0,,,,51455,31.2602,[nan],"{'GPD': ['WRI1075853'], 'CARMA': ['CARMA8190']}"

data/eia_hydro_annual_generation.csv

@@ -1,50 +1,53 @@
-https://www.eia.gov/international/data/world/electricity/electricity-generation?pd=2&p=000000000000000000000000000000g&u=1&f=A&v=mapbubble&a=-&i=none&vo=value&t=R&g=000000000000002&l=73-1028i008017kg6368g80a4k000e0ag00gg0004g8g0ho00g000400008&s=315532800000&e=1577836800000&ev=false&
-Report generated on: 03-28-2022 11:20:48
-"API","","1980","1981","1982","1983","1984","1985","1986","1987","1988","1989","1990","1991","1992","1993","1994","1995","1996","1997","1998","1999","2000","2001","2002","2003","2004","2005","2006","2007","2008","2009","2010","2011","2012","2013","2014","2015","2016","2017","2018","2019","2020"
-"","hydroelectricity net generation (billion kWh)","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
-"INTL.33-12-EURO-BKWH.A","    Europe","458.018","464.155","459.881","473.685","481.241","476.739","459.535","491.085","534.517","465.365","474.466","475.47","509.041","526.448","531.815","543.743","529.114164","543.845616","562.441501","569.308453","591.206662","587.371195","541.542535","506.19703","544.536443","545.176179","537.335934","540.934407","567.557921","564.244482","619.96477","543.05273","600.46622","631.86431","619.59229","615.53013","629.98906","562.59258","619.31106","610.62616","670.925"
-"INTL.33-12-ALB-BKWH.A","        Albania","2.919","3.018","3.093","3.167","3.241","3.315","3.365","3.979","3.713","3.846","2.82","3.483","3.187","3.281","3.733","4.162","5.669","4.978","4.872","5.231","4.548","3.519","3.477","5.117","5.411","5.319","4.951","2.76","3.759","5.201","7.49133","4.09068","4.67775","6.88941","4.67676","5.83605","7.70418","4.47975","8.46648","5.15394","5.281"
-"INTL.33-12-AUT-BKWH.A","        Austria","28.501","30.008","29.893","29.577","28.384","30.288","30.496","25.401","35.151","34.641","31.179","31.112","34.483","36.336","35.349","36.696","33.874","35.744","36.792","40.292","41.418","40.05","39.825","32.883","36.394","36.31","35.48","36.732","37.969","40.487","36.466","32.511","41.862","40.138","39.001","35.255","37.954","36.462","35.73","40.43655","45.344"
-"INTL.33-12-BEL-BKWH.A","        Belgium","0.274","0.377","0.325","0.331","0.348","0.282","0.339","0.425","0.354","0.3","0.263","0.226","0.338","0.252","0.342","0.335","0.237","0.30195","0.38511","0.338","0.455","0.437","0.356","0.245","0.314","0.285","0.355","0.385","0.406","0.325","0.298","0.193","0.353","0.376","0.289","0.314","0.367","0.268","0.311","0.108","1.29"
-"INTL.33-12-BIH-BKWH.A","        Bosnia and Herzegovina","--","--","--","--","--","--","--","--","--","--","--","--","3.374","2.343","3.424","3.607","5.104","4.608","4.511","5.477","5.043","5.129","5.215","4.456","5.919","5.938","5.798","3.961","4.818","6.177","7.946","4.343","4.173","7.164","5.876","5.495","5.585","3.7521","6.35382","6.02019","6.1"
-"INTL.33-12-BGR-BKWH.A","        Bulgaria","3.674","3.58","3.018","3.318","3.226","2.214","2.302","2.512","2.569","2.662","1.859","2.417","2.042","1.923","1.453","2.291","2.89","2.726","3.066","2.725","2.646","1.72","2.172","2.999","3.136","4.294","4.196","2.845","2.796","3.435","4.98168","2.84328","3.14622","3.99564","4.55598","5.59845","3.8412","2.79972","5.09553","3.34917","3.37"
-"INTL.33-12-HRV-BKWH.A","        Croatia","--","--","--","--","--","--","--","--","--","--","--","--","4.298","4.302","4.881","5.212","7.156","5.234","5.403","6.524","5.794","6.482","5.311","4.827","6.888","6.27","5.94","4.194","5.164","6.663","9.035","4.983","4.789","8.536","8.917","6.327","6.784","5.255","7.62399","5.87268","3.4"
-"INTL.33-12-CYP-BKWH.A","        Cyprus","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0"
-"INTL.33-12-CZE-BKWH.A","        Czech Republic","--","--","--","--","--","--","--","--","--","--","--","--","--","1.355","1.445","1.982","1.949","1.68201","1.382","1.664","1.7404","2.033","2.467","1.369","1.999","2.356","2.525","2.068","2.004","2.405","2.775","1.95","2.107","2.704","1.909","1.779","1.983","1.852","1.615","1.98792","3.4"
-"INTL.33-12-DNK-BKWH.A","        Denmark","0.03","0.031","0.028","0.036","0.028","0.027","0.029","0.029","0.032","0.027","0.027","0.026","0.028","0.027","0.033","0.03","0.019","0.019","0.02673","0.031","0.03","0.028","0.032","0.021","0.027","0.023","0.023","0.028","0.026","0.019","0.021","0.017","0.017","0.013","0.015","0.018","0.019","0.018","0.015","0.01584","0.02"
-"INTL.33-12-EST-BKWH.A","        Estonia","--","--","--","--","--","--","--","--","--","--","--","--","0.001","0.001","0.003","0.002","0.002","0.003","0.004","0.004","0.005","0.007","0.006","0.013","0.022","0.022","0.014","0.021","0.028","0.032","0.027","0.03","0.042","0.026","0.027","0.027","0.035","0.026","0.015","0.01881","0.04"
-"INTL.33-12-FRO-BKWH.A","        Faroe Islands","0.049","0.049","0.049","0.049","0.049","0.049","0.049","0.049","0.062","0.071","0.074","0.074","0.083","0.073","0.075","0.075","0.069564","0.075066","0.076501","0.069453","0.075262","0.075195","0.095535","0.08483","0.093443","0.097986","0.099934","0.103407","0.094921","0.091482","0.06676","0.092","0.099","0.091","0.121","0.132","0.105","0.11","0.107","0.102","0.11"
-"INTL.33-12-FIN-BKWH.A","        Finland","10.115","13.518","12.958","13.445","13.115","12.211","12.266","13.658","13.229","12.9","10.75","13.065","14.956","13.341","11.669","12.796","11.742","12.11958","14.9","12.652","14.513","13.073","10.668","9.495","14.919","13.646","11.379","14.035","16.941","12.559","12.743","12.278","16.667","12.672","13.24","16.584","15.634","14.61","13.137","12.31461","15.56"
-"INTL.33-12-CSK-BKWH.A","        Former Czechoslovakia","4.8","4.2","3.7","3.9","3.2","4.3","4","4.853","4.355","4.229","3.919","3.119","3.602","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--"
-"INTL.33-12-SCG-BKWH.A","        Former Serbia and Montenegro","--","--","--","--","--","--","--","--","--","--","--","--","11.23","10.395","11.016","12.071","14.266","12.636","12.763","13.243","11.88","12.326","11.633","9.752","11.01","11.912","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--"
-"INTL.33-12-YUG-BKWH.A","        Former Yugoslavia","27.868","25.044","23.295","21.623","25.645","24.363","27.474","25.98","25.612","23.256","19.601","18.929","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--"
-"INTL.33-12-FRA-BKWH.A","        France","68.253","70.358","68.6","67.515","64.01","60.248","60.953","68.623","73.952","45.744","52.796","56.277","68.313","64.3","78.057","72.196","64.43","63.151","61.479","71.832","66.466","73.888","59.992","58.567","59.276","50.965","55.741","57.029","63.017","56.428","61.945","45.184","59.099","71.042","62.993","54.876","60.094","49.389","64.485","56.98242","64.84"
-"INTL.33-12-DEU-BKWH.A","        Germany","--","--","--","--","--","--","--","--","--","--","--","14.742","17.223","17.699","19.731","21.562","21.737","17.18343","17.044","19.451","21.515","22.506","22.893","19.071","20.866","19.442","19.808","20.957","20.239","18.841","20.678","17.323","21.331","22.66","19.31","18.664","20.214","19.985","17.815","19.86039","24.75"
-"INTL.33-12-DDR-BKWH.A","        Germany, East","1.658","1.718","1.748","1.683","1.748","1.758","1.767","1.726","1.719","1.551","1.389","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--"
-"INTL.33-12-DEUW-BKWH.A","        Germany, West","17.125","17.889","17.694","16.713","16.434","15.354","16.526","18.36","18.128","16.482","15.769","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--"
-"INTL.33-12-GIB-BKWH.A","        Gibraltar","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0"
-"INTL.33-12-GRC-BKWH.A","        Greece","3.396","3.398","3.551","2.331","2.852","2.792","3.222","2.768","2.354","1.888","1.751","3.068","2.181","2.26","2.573","3.494","4.305","3.84318","3.68","4.546","3.656","2.076","2.772","4.718","4.625","4.967","5.806","2.565","3.279","5.32","7.431","3.998","4.387","6.337","4.464","5.782","5.543","3.962","5.035","3.9798","3.43"
-"INTL.33-12-HUN-BKWH.A","        Hungary","0.111","0.166","0.158","0.153","0.179","0.153","0.152","0.167","0.167","0.156","0.176","0.192","0.156","0.164","0.159","0.161","0.205","0.21384","0.15345","0.179","0.176","0.184","0.192","0.169","0.203","0.2","0.184","0.208","0.211","0.226","0.184","0.216","0.206","0.208","0.294","0.227","0.253","0.214","0.216","0.21681","0.24"
-"INTL.33-12-ISL-BKWH.A","        Iceland","3.053","3.085","3.407","3.588","3.738","3.667","3.846","3.918","4.169","4.217","4.162","4.162","4.267","4.421","4.47","4.635","4.724","5.15493","5.565","5.987","6.292","6.512","6.907","7.017","7.063","6.949","7.22","8.31","12.303","12.156","12.51","12.382","12.214","12.747","12.554","13.541","13.092","13.892","13.679","13.32441","12.46"
-"INTL.33-12-IRL-BKWH.A","        Ireland","0.833","0.855","0.792","0.776","0.68","0.824","0.91","0.673","0.862","0.684","0.69","0.738","0.809","0.757","0.911","0.706","0.715","0.67122","0.907","0.838","0.838","0.59","0.903","0.592","0.624","0.625","0.717","0.66","0.959","0.893","0.593","0.699","0.795","0.593","0.701","0.798","0.674","0.685","0.687","0.87813","1.21"
-"INTL.33-12-ITA-BKWH.A","        Italy","44.997","42.782","41.216","40.96","41.923","40.616","40.626","39.05","40.205","33.647","31.31","41.817","41.778","41.011","44.212","37.404","41.617","41.18697","40.808","44.911","43.763","46.343","39.125","33.303","41.915","35.706","36.624","32.488","41.207","48.647","50.506","45.36477","41.45625","52.24626","57.95955","45.08163","42.00768","35.83701","48.29913","45.31824","47.72"
-"INTL.33-12-XKS-BKWH.A","        Kosovo","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","0.075","0.119","0.154","0.104","0.095","0.142","0.149","0.139","0.243","0.177","0.27027","0.2079","0.26"
-"INTL.33-12-LVA-BKWH.A","        Latvia","--","--","--","--","--","--","--","--","--","--","--","--","2.498","2.846","3.272","2.908","1.841","2.922","2.99","2.729","2.791","2.805","2.438","2.243","3.078","3.293","2.671","2.706","3.078","3.422","3.488","2.857","3.677","2.838","1.953","1.841","2.523","4.356","2.417","2.08692","2.59"
-"INTL.33-12-LTU-BKWH.A","        Lithuania","--","--","--","--","--","--","--","--","--","--","--","--","0.308","0.389","0.447","0.369","0.323","0.291","0.413","0.409","0.336","0.322","0.35","0.323","0.417","0.446193","0.393","0.417","0.398","0.42","0.535","0.475","0.419","0.516","0.395","0.346","0.45","0.597","0.427","0.34254","1.06"
-"INTL.33-12-LUX-BKWH.A","        Luxembourg","0.086","0.095","0.084","0.083","0.088","0.071","0.084","0.101","0.097","0.072","0.07","0.083","0.069","0.066","0.117","0.087","0.059","0.082","0.114","0.084","0.119","0.117","0.098","0.078","0.103","0.093","0.11","0.116","0.131","0.105","0.104","0.061","0.095","0.114","0.104","0.095","0.111","0.082","0.089","0.10593","1.09"
-"INTL.33-12-MLT-BKWH.A","        Malta","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0","0"
-"INTL.33-12-MNE-BKWH.A","        Montenegro","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","1.733","1.271","1.524","2.05","2.723","1.192","1.462","2.479","1.734","1.476","1.825","1.014","2.09187","1.78","1.8"
-"INTL.33-12-NLD-BKWH.A","        Netherlands","0","0","0","0","0","0.003","0.003","0.001","0.002","0.037","0.119","0.079","0.119","0.091","0.1","0.087","0.079","0.09108","0.111","0.089","0.141","0.116","0.109","0.071","0.094","0.087","0.105","0.106","0.101","0.097","0.105","0.057","0.104","0.114","0.112","0.093","0.1","0.061","0.072","0.07326","0.05"
-"INTL.33-12-MKD-BKWH.A","        North Macedonia","--","--","--","--","--","--","--","--","--","--","--","--","0.817","0.517","0.696","0.793","0.842","0.891","1.072","1.375","1.158","0.62","0.749","1.36","1.467","1.477","1.634","1","0.832","1.257","2.407","1.419","1.031","1.568","1.195","1.846","1.878","1.099","1.773","1.15236","1.24"
-"INTL.33-12-NOR-BKWH.A","        Norway","82.717","91.876","91.507","104.704","104.895","101.464","95.321","102.341","107.919","117.369","119.933","109.032","115.505","118.024","110.398","120.315","102.823","108.677","114.546","120.237","140.4","119.258","128.078","104.425","107.693","134.331","118.175","132.319","137.654","124.03","116.257","119.78","141.189","127.551","134.844","136.662","142.244","141.651","138.202","123.66288","141.69"
-"INTL.33-12-POL-BKWH.A","        Poland","2.326","2.116","1.528","1.658","1.394","1.833","1.534","1.644","1.775","1.593","1.403","1.411","1.492","1.473","1.716","1.868","1.912","1.941","2.286","2.133","2.085","2.302","2.256","1.654","2.06","2.179","2.022","2.328","2.13","2.351","2.9","2.313","2.02","2.421","2.165","1.814","2.117","2.552","1.949","1.93842","2.93"
-"INTL.33-12-PRT-BKWH.A","        Portugal","7.873","4.934","6.82","7.897","9.609","10.512","8.364","9.005","12.037","5.72","9.065","8.952","4.599","8.453","10.551","8.26","14.613","12.97395","12.853","7.213","11.21","13.894","7.722","15.566","9.77","4.684","10.892","9.991","6.73","8.201","15.954","11.423","5.589","13.652","15.471","8.615","15.608","5.79","12.316","8.6526","13.96"
-"INTL.33-12-ROU-BKWH.A","        Romania","12.506","12.605","11.731","9.934","11.208","11.772","10.688","11.084","13.479","12.497","10.87","14.107","11.583","12.64","12.916","16.526","15.597","17.334","18.69","18.107","14.63","14.774","15.886","13.126","16.348","20.005","18.172","15.806","17.023","15.379","19.684","14.581","11.945","14.807","18.618","16.467","17.848","14.349","17.48736","15.65289","15.53"
-"INTL.33-12-SRB-BKWH.A","        Serbia","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","--","10.855","9.937","9.468","10.436","11.772","8.58","9.193","10.101","10.893","9.979","10.684","9.061","10.53261","10.07028","9.66"
-"INTL.33-12-SVK-BKWH.A","        Slovakia","--","--","--","--","--","--","--","--","--","--","--","--","--","3.432","4.311","4.831","4.185","4.023","4.224","4.429","4.569","4.878","5.215","3.4452","4.059","4.592","4.355","4.406","4","4.324","5.184","3.211","3.687","4.329","3.762","3.701","4.302","4.321","3.506","4.27383","4.67"
-"INTL.33-12-SVN-BKWH.A","        Slovenia","--","--","--","--","--","--","--","--","--","--","--","--","3.379","2.974","3.348","3.187","3.616","3.046","3.4","3.684","3.771","3.741","3.265","2.916","4.033","3.426","3.555","3.233","3.978","4.666","4.452","3.506","3.841","4.562","6.011","3.75","4.443","3.814","4.643","4.43421","5.24"
-"INTL.33-12-ESP-BKWH.A","        Spain","29.16","21.64","25.99","26.696","31.088","30.895","26.105","27.016","34.76","19.046","25.16","27.01","18.731","24.133","27.898","22.881","39.404","34.43","33.665","22.634","29.274","40.617","22.691","40.643","31.359","18.209","25.699","27.036","23.13","26.147","41.576","30.07","20.192","36.45","38.815","27.656","35.77","18.007","33.743","24.23025","33.34"
-"INTL.33-12-SWE-BKWH.A","        Sweden","58.133","59.006","54.369","62.801","67.106","70.095","60.134","70.95","69.016","70.911","71.778","62.603","73.588","73.905","58.508","67.421","51.2226","68.365","74.25","70.974","77.798","78.269","65.696","53.005","59.522","72.075","61.106","65.497","68.378","65.193","66.279","66.047","78.333","60.81","63.227","74.734","61.645","64.651","61.79","64.46583","71.6"
-"INTL.33-12-CHE-BKWH.A","        Switzerland","32.481","35.13","35.974","35.069","29.871","31.731","32.576","34.328","35.437","29.477","29.497","31.756","32.373","35.416","38.678","34.817","28.458","33.70257","33.136","39.604","36.466","40.895","34.862","34.471","33.411","30.914","30.649","34.898","35.676","35.366","35.704","32.069","38.218","38.08","37.659","37.879","34.281","33.754","34.637","37.6596","40.62"
-"INTL.33-12-TUR-BKWH.A","        Turkey","11.159","12.308","13.81","11.13","13.19","11.822","11.637","18.314","28.447","17.61","22.917","22.456","26.302","33.611","30.28","35.186","40.07","39.41784","41.80671","34.33","30.57","23.77","33.346","34.977","45.623","39.165","43.802","35.492","32.937","35.598","51.423","51.155","56.669","58.225","39.75","65.856","66.686","57.824","59.49","87.99714","77.39"
-"INTL.33-12-GBR-BKWH.A","        United Kingdom","3.921","4.369","4.543","4.548","3.992","4.08","4.767","4.13","4.915","4.732","5.119","4.534","5.329","4.237","5.043","4.79","3.359","4.127","5.067","5.283","5.035","4.015","4.74","3.195","4.795","4.873","4.547","5.026","5.094","5.178","3.566","5.655","5.286","4.667","5.832","6.246","5.342","5.836","5.189","5.89941","7.64"
+https://www.eia.gov/international/data/world/electricity/electricity-generation?pd=2&p=000000000000000000000000000000g&u=1&f=A&v=mapbubble&a=-&i=none&vo=value&t=R&g=000000000000002&l=73-1028i008017kg6368g80a4k000e0ag00gg0004g8g0ho00g000400008&l=72-00000000000000000000000000080000000000000000000g&s=315532800000&e=1609459200000&ev=false&,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+Report generated on: 01-06-2023 21:17:46,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+API,,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021
+,hydroelectricity net generation (billion kWh),,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+INTL.33-12-EURO-BKWH.A,    Europe,"458,018","464,155","459,881","473,685","481,241","476,739","459,535","491,085","534,517","465,365","474,466","475,47","509,041","526,448","531,815","543,743","529,114164","543,845616","562,491501","566,861453","588,644662","584,806195","539,051405","503,7067","542,112443","542,974669","535,006084","538,449707","565,143111","561,761402","617,547148","540,926277","598,055253","629,44709","617,111295","613,079848","627,720566217","560,362524","616,5081462","606,5997419","644,1106599","628,1390143"
+INTL.33-12-ALB-BKWH.A,        Albania,"2,919","3,018","3,093","3,167","3,241","3,315","3,365","3,979","3,713","3,846","2,82","3,483","3,187","3,281","3,733","4,162","5,669","4,978","4,872","5,231","4,548","3,519","3,477","5,117","5,411","5,319","4,951","2,76","3,759","5,201","7,49133","4,09068","4,67775","6,88941","4,67676","5,83605","7,70418","4,47975","8,46648","5,15394","5,281","8,891943"
+INTL.33-12-AUT-BKWH.A,        Austria,"28,501","30,008","29,893","29,577","28,384","30,288","30,496","25,401","35,151","34,641","31,179","31,112","34,483","36,336","35,349","36,696","33,874","35,744","36,792","40,292","41,418","40,05","39,825","32,883","36,394","36,31","35,48","36,732","37,969","40,487","36,466","32,511","41,862","40,138","39,001","35,255","37,954","36,462","35,73","40,43655","41,9356096","38,75133"
+INTL.33-12-BEL-BKWH.A,        Belgium,"0,274","0,377","0,325","0,331","0,348","0,282","0,339","0,425","0,354","0,3","0,263","0,226","0,338","0,252","0,342","0,335","0,237","0,30195","0,38511","0,338","0,455","0,437","0,356","0,245","0,314","0,285","0,355","0,385","0,406","0,325","0,298","0,193","0,353","0,376","0,289","0,314","0,367","0,268","0,3135","0,302","0,2669","0,3933"
+INTL.33-12-BIH-BKWH.A,        Bosnia and Herzegovina,--,--,--,--,--,--,--,--,--,--,--,--,"3,374","2,343","3,424","3,607","5,104","4,608","4,511","5,477","5,043","5,129","5,215","4,456","5,919","5,938","5,798","3,961","4,818","6,177","7,946","4,343","4,173","7,164","5,876","5,495","5,585","3,7521","6,35382","6,02019","4,58","6,722"
+INTL.33-12-BGR-BKWH.A,        Bulgaria,"3,674","3,58","3,018","3,318","3,226","2,214","2,302","2,512","2,569","2,662","1,859","2,417","2,042","1,923","1,453","2,291","2,89","2,726","3,066","2,725","2,646","1,72","2,172","2,999","3,136","4,294","4,196","2,845","2,796","3,435","4,98168","2,84328","3,14622","3,99564","4,55598","5,59845","3,8412","2,79972","5,09553","2,929499","2,820398","4,819205"
+INTL.33-12-HRV-BKWH.A,        Croatia,--,--,--,--,--,--,--,--,--,--,--,--,"4,298","4,302","4,881","5,212","7,156","5,234","5,403","6,524","5,794","6,482","5,311","4,827","6,888","6,27","5,94","4,194","5,164","6,663","9,035","4,983","4,789","8,536","8,917","6,327","6,784","5,255","7,62399","5,87268","5,6624","7,1277"
+INTL.33-12-CYP-BKWH.A,        Cyprus,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+INTL.33-12-CZE-BKWH.A,        Czechia,--,--,--,--,--,--,--,--,--,--,--,--,--,"1,355","1,445","1,982","1,949","1,68201","1,382","1,664","1,7404","2,033","2,467","1,369","1,999","2,356","2,525","2,068","2,004","2,405","2,775","1,95","2,107","2,704","1,909","1,779","1,983","1,852","1,615","1,98792","2,143884","2,40852"
+INTL.33-12-DNK-BKWH.A,        Denmark,"0,03","0,031","0,028","0,036","0,028","0,027","0,029","0,029","0,032","0,027","0,027","0,026","0,028","0,027","0,033","0,03","0,019","0,019","0,02673","0,031","0,03","0,028","0,032","0,021","0,027","0,023","0,023","0,028","0,026","0,019","0,021","0,017","0,017","0,013","0,015","0,01803","0,01927","0,017871","0,0148621","0,0172171","0,017064","0,016295"
+INTL.33-12-EST-BKWH.A,        Estonia,--,--,--,--,--,--,--,--,--,--,--,--,"0,001","0,001","0,003","0,002","0,002","0,003","0,004","0,004","0,005","0,007","0,006","0,013","0,022","0,022","0,014","0,021","0,028","0,032","0,027","0,029999","0,042","0,026","0,027","0,027","0,035","0,025999","0,0150003","0,0189999","0,03","0,0248"
+INTL.33-12-FRO-BKWH.A,        Faroe Islands,"0,049","0,049","0,049","0,049","0,049","0,049","0,049","0,049","0,062","0,071","0,074","0,074","0,083","0,073","0,075","0,075","0,069564","0,075066","0,076501","0,069453","0,075262","0,075195","0,095535","0,08483","0,093443","0,097986","0,099934","0,103407","0,094921","0,091482","0,06676","0,092","0,099","0,091","0,121","0,132","0,105","0,11","0,107","0,102","0,11","0,11"
+INTL.33-12-FIN-BKWH.A,        Finland,"10,115","13,518","12,958","13,445","13,115","12,211","12,266","13,658","13,229","12,9","10,75","13,065","14,956","13,341","11,669","12,796","11,742","12,11958","14,9","12,652","14,513","13,073","10,668","9,495","14,919","13,646","11,379","14,035","16,941","12,559","12,743","12,278001","16,666998","12,672","13,240001","16,583999","15,634127","14,609473","13,1369998","12,2454823","15,883","15,766"
+INTL.33-12-CSK-BKWH.A,        Former Czechoslovakia,"4,8","4,2","3,7","3,9","3,2","4,3",4,"4,853","4,355","4,229","3,919","3,119","3,602",--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--
+INTL.33-12-SCG-BKWH.A,        Former Serbia and Montenegro,--,--,--,--,--,--,--,--,--,--,--,--,"11,23","10,395","11,016","12,071","14,266","12,636","12,763","13,243","11,88","12,326","11,633","9,752","11,01","11,912",--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--
+INTL.33-12-YUG-BKWH.A,        Former Yugoslavia,"27,868","25,044","23,295","21,623","25,645","24,363","27,474","25,98","25,612","23,256","19,601","18,929",--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--
+INTL.33-12-FRA-BKWH.A,        France,"68,253","70,358","68,6","67,515","64,01","60,248","60,953","68,623","73,952","45,744","52,796","56,277","68,313","64,3","78,057","72,196","64,43","63,151","61,479","71,832","66,466","73,888","59,992","58,567","59,276","50,965","55,741","57,029","63,017","56,428","61,945","45,184","59,099","71,042","62,993","54,876","60,094","49,389","64,485","56,913891","62,06191","58,856657"
+INTL.33-12-DEU-BKWH.A,        Germany,--,--,--,--,--,--,--,--,--,--,--,"14,742","17,223","17,699","19,731","21,562","21,737","17,18343","17,044","19,451","21,515","22,506","22,893","19,071","20,866","19,442","19,808","20,957","20,239","18,841","20,678","17,323","21,331","22,66","19,31","18,664","20,214","19,985","17,694","19,731","18,322","19,252"
+INTL.33-12-DDR-BKWH.A,"        Germany, East","1,658","1,718","1,748","1,683","1,748","1,758","1,767","1,726","1,719","1,551","1,389",--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--
+INTL.33-12-DEUW-BKWH.A,"        Germany, West","17,125","17,889","17,694","16,713","16,434","15,354","16,526","18,36","18,128","16,482","15,769",--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--
+INTL.33-12-GIB-BKWH.A,        Gibraltar,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+INTL.33-12-GRC-BKWH.A,        Greece,"3,396","3,398","3,551","2,331","2,852","2,792","3,222","2,768","2,354","1,888","1,751","3,068","2,181","2,26","2,573","3,494","4,305","3,84318","3,68","4,546","3,656","2,076","2,772","4,718","4,625","4,967","5,806","2,565","3,279","5,32","7,431","3,998","4,387","6,337","4,464","5,782","5,543","3,962","5,035","3,9798","3,343687","5,909225"
+INTL.33-12-HUN-BKWH.A,        Hungary,"0,111","0,166","0,158","0,153","0,179","0,153","0,152","0,167","0,167","0,156","0,176","0,192","0,156","0,164","0,159","0,161","0,205","0,21384","0,15345","0,179","0,176","0,184","0,192","0,169","0,203","0,2","0,184","0,208","0,211","0,226","0,184","0,215999","0,205999","0,207999","0,294001","0,226719","0,253308","0,213999","0,216","0,2129999","0,238","0,202379"
+INTL.33-12-ISL-BKWH.A,        Iceland,"3,053","3,085","3,407","3,588","3,738","3,667","3,846","3,918","4,169","4,217","4,162","4,162","4,267","4,421","4,47","4,635","4,724","5,15493","5,565","5,987","6,292","6,512","6,907","7,017","7,063","6,949","7,22","8,31","12,303","12,156","12,509999","12,381999","12,213999","12,747001","12,554","13,541","13,091609","13,891929","13,679377","13,32911","12,9196201","13,5746171"
+INTL.33-12-IRL-BKWH.A,        Ireland,"0,833","0,855","0,792","0,776","0,68","0,824","0,91","0,673","0,862","0,684","0,69","0,738","0,809","0,757","0,911","0,706","0,715","0,67122","0,907","0,838","0,838","0,59","0,903","0,592","0,624","0,625","0,717","0,66","0,959","0,893","0,593","0,699","0,795","0,593","0,701","0,798","0,674","0,685","0,687","0,87813","0,932656","0,750122"
+INTL.33-12-ITA-BKWH.A,        Italy,"44,997","42,782","41,216","40,96","41,923","40,616","40,626","39,05","40,205","33,647","31,31","41,817","41,778","41,011","44,212","37,404","41,617","41,18697","40,808","44,911","43,763","46,343","39,125","33,303","41,915","35,706","36,624","32,488","41,207","48,647","50,506","45,36477","41,45625","52,24626","57,95955","45,08163","42,00768","35,83701","48,29913","45,31824","47,551784","44,739"
+INTL.33-12-XKS-BKWH.A,        Kosovo,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,"0,075","0,119","0,154","0,104","0,095","0,142","0,149","0,139","0,243","0,177","0,27027","0,2079","0,262826","0,300635"
+INTL.33-12-LVA-BKWH.A,        Latvia,--,--,--,--,--,--,--,--,--,--,--,--,"2,498","2,846","3,272","2,908","1,841","2,922","2,99","2,729","2,791","2,805","2,438","2,243","3,078","3,293","2,671","2,706","3,078","3,422","3,487998","2,8568","3,677","2,838","1,953","1,841","2,522819","4,355513","2,4170639","2,0958919","2,5840101","2,6889293"
+INTL.33-12-LTU-BKWH.A,        Lithuania,--,--,--,--,--,--,--,--,--,--,--,--,"0,308","0,389","0,447","0,369","0,323","0,291","0,413","0,409","0,336","0,322","0,35","0,323","0,417","0,446193","0,393","0,417","0,398","0,42","0,535","0,475","0,419","0,516","0,395","0,346","0,45","0,597","0,427","0,34254","0,3006","0,3837"
+INTL.33-12-LUX-BKWH.A,        Luxembourg,"0,086","0,095","0,084","0,083","0,088","0,071","0,084","0,101","0,097","0,072","0,07","0,083","0,069","0,066","0,117","0,087","0,059","0,082","0,114","0,084","0,119","0,117","0,098","0,078","0,103","0,093","0,11","0,116","0,131","0,105","0,104","0,061","0,095","0,114","0,104","0,095","0,111","0,082","0,089","0,10593","0,091602","0,1068"
+INTL.33-12-MLT-BKWH.A,        Malta,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+INTL.33-12-MNE-BKWH.A,        Montenegro,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,"1,733","1,271","1,524","2,05","2,723","1,192","1,462","2,479","1,734","1,476","1,825","1,014","1,693443","1,262781","0,867637","1,212652"
+INTL.33-12-NLD-BKWH.A,        Netherlands,0,0,0,0,0,"0,003","0,003","0,001","0,002","0,037","0,119","0,079","0,119","0,091","0,1","0,087","0,079","0,09108","0,111","0,089","0,141","0,116","0,109","0,071","0,094","0,087","0,105","0,106","0,101","0,097","0,105","0,057","0,104389","0,11431","0,112202","0,0927","0,100078","0,060759","0,0723481","0,074182","0,0462851","0,0838927"
+INTL.33-12-MKD-BKWH.A,        North Macedonia,--,--,--,--,--,--,--,--,--,--,--,--,"0,817","0,517","0,696","0,793","0,842","0,891","1,072","1,375","1,158","0,62","0,749","1,36","1,467","1,477","1,634",1,"0,832","1,257","2,407","1,419","1,031","1,568","1,195","1,846","1,878","1,099","1,773","1,15236","1,277144","1,451623"
+INTL.33-12-NOR-BKWH.A,        Norway,"82,717","91,876","91,507","104,704","104,895","101,464","95,321","102,341","107,919","117,369","119,933","109,032","115,505","118,024","110,398","120,315","102,823","108,677","114,546","120,237","140,4","119,258","128,078","104,425","107,693","134,331","118,175","132,319","137,654","124,03","116,257","119,78","141,189","127,551","134,844","136,662","142,244","141,651","138,202","123,66288","141,69",144
+INTL.33-12-POL-BKWH.A,        Poland,"2,326","2,116","1,528","1,658","1,394","1,833","1,534","1,644","1,775","1,593","1,403","1,411","1,492","1,473","1,716","1,868","1,912","1,941","2,286","2,133","2,085","2,302","2,256","1,654","2,06","2,179","2,022","2,328","2,13","2,351","2,9","2,313","2,02","2,421","2,165","1,814","2,117","2,552","1,949","1,93842","2,118337","2,339192"
+INTL.33-12-PRT-BKWH.A,        Portugal,"7,873","4,934","6,82","7,897","9,609","10,512","8,364","9,005","12,037","5,72","9,065","8,952","4,599","8,453","10,551","8,26","14,613","12,97395","12,853","7,213","11,21","13,894","7,722","15,566","9,77","4,684","10,892","9,991","6,73","8,201","15,954","11,423","5,589","13,652","15,471","8,615","15,608","5,79","12,316","8,6526","12,082581","11,846464"
+INTL.33-12-ROU-BKWH.A,        Romania,"12,506","12,605","11,731","9,934","11,208","11,772","10,688","11,084","13,479","12,497","10,87","14,107","11,583","12,64","12,916","16,526","15,597","17,334","18,69","18,107","14,63","14,774","15,886","13,126","16,348","20,005","18,172","15,806","17,023","15,379","19,684","14,581","11,945","14,807","18,618","16,467","17,848","14,349","17,48736","15,580622","15,381243","17,376933"
+INTL.33-12-SRB-BKWH.A,        Serbia,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,--,"10,855","9,937","9,468","10,436","11,772","8,58","9,193","10,101","10,893","9,979","10,684","9,061","10,53261","9,457175","9,034496","11,284232"
+INTL.33-12-SVK-BKWH.A,        Slovakia,--,--,--,--,--,--,--,--,--,--,--,--,--,"3,432","4,311","4,831","4,185","4,023","4,224","4,429","4,569","4,878","5,215","3,4452","4,059","4,592","4,355","4,406",4,"4,324","5,184","3,211","3,687","4,329","3,762","3,701","4,302","4,321","3,506","4,27383","4,517","4,17"
+INTL.33-12-SVN-BKWH.A,        Slovenia,--,--,--,--,--,--,--,--,--,--,--,--,"3,379","2,974","3,348","3,187","3,616","3,046","3,4","3,684","3,771","3,741","3,265","2,916","4,033","3,426","3,555","3,233","3,978","4,666","4,452","3,506","3,841","4,562","6,011","3,75","4,443","3,814","4,643","4,43421","4,93406","4,711944"
+INTL.33-12-ESP-BKWH.A,        Spain,"29,16","21,64","25,99","26,696","31,088","30,895","26,105","27,016","34,76","19,046","25,16","27,01","18,731","24,133","27,898","22,881","39,404","34,43","33,665","22,634","29,274","40,617","22,691","40,643","31,359","18,209","25,699","27,036","23,13","26,147","41,576","30,07","20,192","36,45","38,815","27,656","35,77","18,007","33,743","24,23025","30,507","29,626"
+INTL.33-12-SWE-BKWH.A,        Sweden,"58,133","59,006","54,369","62,801","67,106","70,095","60,134","70,95","69,016","70,911","71,778","62,603","73,588","73,905","58,508","67,421","51,2226","68,365","74,25","70,974","77,798","78,269","65,696","53,005","59,522","72,075","61,106","65,497","68,378","65,193","66,279","66,047","78,333","60,81","63,227","74,734","61,645","64,651","61,79","64,46583","71,6","71,086"
+INTL.33-12-CHE-BKWH.A,        Switzerland,"32,481","35,13","35,974","35,069","29,871","31,731","32,576","34,328","35,437","29,477","29,497","31,756","32,373","35,416","38,678","34,817","28,458","33,70257","33,136","37,104","33,854","38,29","32,323","31,948","30,938","28,664","28,273","32,362","33,214","32,833","33,261","29,906","35,783","35,628","35,122","35,378","31,984","31,47968","32,095881","35,156989","37,867647","36,964485"
+INTL.33-12-TUR-BKWH.A,        Turkey,"11,159","12,308","13,81","11,13","13,19","11,822","11,637","18,314","28,447","17,61","22,917","22,456","26,302","33,611","30,28","35,186","40,07","39,41784","41,80671","34,33","30,57","23,77","33,346","34,977","45,623","39,165","43,802","35,492","32,937","35,598","51,423001","51,154999","56,668998","58,225","39,750001","65,856","66,685883","57,823851","59,490211","88,2094218","78,094369","55,1755392"
+INTL.33-12-GBR-BKWH.A,        United Kingdom,"3,921","4,369","4,543","4,548","3,992","4,08","4,767","4,13","4,915","4,732","5,119","4,534","5,329","4,237","5,043","4,79","3,359","4,127","5,117","5,336","5,085","4,055","4,78787","3,22767","4,844","4,92149","4,59315","5,0773","5,14119","5,22792","3,59138","5,69175","5,30965","4,70147","5,8878","6,29727","5,370412217","5,88187","5,44327","5,84628","6,75391","5,0149"
+,    Eurasia,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
+INTL.33-12-MDA-BKWH.A,        Moldova,--,--,--,--,--,--,--,--,--,--,--,--,"0,255","0,371","0,275","0,321","0,362","0,378","0,387","0,363","0,392","0,359","0,348","0,358","0,35","0,359","0,365","0,354","0,385","0,354","0,403","0,348","0,266","0,311","0,317","0,265","0,228","0,282","0,27324","0,29799","0,276","0,316"
+INTL.33-12-UKR-BKWH.A,        Ukraine,--,--,--,--,--,--,--,--,--,--,--,--,"7,725","10,929","11,997","9,853","8,546","9,757","15,756","14,177","11,161","11,912","9,531","9,146","11,635","12,239","12,757","10,042","11,397","11,817","13,02","10,837","10,374","13,663","8,393","5,343","7,594","8,856","10,32372","6,5083","7,5638","10,3326"

doc/configtables/clustering.csv

@@ -1,4 +1,5 @@
 ,Unit,Values,Description
+focus_weights,,,Optionally specify the focus weights for the clustering of countries. For instance: `DE: 0.8` will distribute 80% of all nodes to Germany and 20% to the rest of the countries.
 simplify_network,,,
 -- to_substations,bool,"{'true','false'}","Aggregates all nodes without power injection (positive or negative, i.e. demand or generation) to electrically closest ones"
 -- algorithm,str,"One of {‘kmeans’, ‘hac’, ‘modularity‘}",

doc/configtables/licenses.csv

@@ -5,7 +5,7 @@
 "naturalearth/*",,,,,http://www.naturalearthdata.com/about/terms-of-use/
 "NUTS_2013 _60M_SH/*","x","x",,"x",https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units
 "cantons.csv","x",,"x",,https://en.wikipedia.org/wiki/Data_codes_for_Switzerland
-"EIA_hydro_generation _2000_2014.csv","x",,,,https://www.eia.gov/about/copyrights_reuse.php
+"eia_hydro_annual_generation.csv","x",,,,https://www.eia.gov/about/copyrights_reuse.php
 "GEBCO_2014_2D.nc","x",,,,https://www.gebco.net/data_and_products/gridded_bathymetry_data/documents/gebco_2014_historic.pdf
 "hydro_capacities.csv","x",,,,
 "je-e-21.03.02.xls","x","x",,,https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html

doc/configtables/lines.csv

@@ -5,6 +5,7 @@ s_nom_max,MW,"float","Global upper limit for the maximum capacity of each extend
 max_extension,MW,"float","Upper limit for the extended capacity of each extendable line."
 length_factor,--,float,"Correction factor to account for the fact that buses are *not* connected by lines through air-line distance."
 under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction."
+reconnect_crimea,--,"true or false","Whether to reconnect Crimea to the Ukrainian grid"
 dynamic_line_rating,,,
 -- activate,bool,"true or false","Whether to take dynamic line rating into account"
 -- cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-era5') or reference an existing folder in the directory ``cutouts``. Source module must be ERA5.","Specifies the directory where the relevant weather data ist stored."

doc/configtables/sector.csv

@@ -73,6 +73,7 @@ marginal_cost_storage,currency/MWh ,float,The marginal cost of discharging batte
 methanation,--,"{true, false}",Add option for transforming hydrogen and CO2 into methane using methanation.
 helmeth,--,"{true, false}",Add option for transforming power into gas using HELMETH (Integrated High-Temperature ELectrolysis and METHanation for Effective Power to Gas Conversion)
 coal_cc,--,"{true, false}",Add option for coal CHPs with carbon capture
+coal_for_industry_cc,--,"{true, false}",Add option for carbon capture in integrated steel making (blast furnaces)
 dac,--,"{true, false}",Add option for Direct Air Capture (DAC)
 co2_vent,--,"{true, false}",Add option for vent out CO2 from storages to the atmosphere.
 allam_cycle,--,"{true, false}",Add option to include `Allam cycle gas power plants <https://en.wikipedia.org/wiki/Allam_power_cycle>`_

doc/configtables/toplevel.csv

@@ -10,4 +10,3 @@ private,,,
 remote,,,
 -- ssh,--,,Optionally specify the SSH of a remote cluster to be synchronized.
 -- path,--,,Optionally specify the file path within the remote cluster to be synchronized.
-focus_weights,,,Optionally specify the focus weights for the clustering of countries. For instance: `DE: 0.8` will distribute 80% of all nodes to Germany and 20% to the rest of the countries.

doc/release_notes.rst

@@ -12,6 +12,8 @@ Upcoming Release
 
 * Updated Global Energy Monitor LNG terminal data to March 2023 version.
 
+* Add option for carbon capture in integrated steelworks.
+
 * For industry distribution, use EPRTR as fallback if ETS data is not available.
 
 * The minimum capacity for renewable generators when using the myopic option has been fixed.
@@ -33,12 +35,27 @@ Upcoming Release
 
 * Split configuration to enable SMR and SMR CC.
 
+* The configuration setting for country focus weights when clustering the
+  network has been moved from ``focus_weights:`` to ``clustering:
+  focus_weights:``. Backwards compatibility to old config files is maintained.
+
 * The ``mock_snakemake`` function can now be used with a Snakefile from a different directory using the new ``root_dir`` argument.
 
+* Merged option to extend geographical scope to Ukraine and Moldova. These
+  countries are excluded by default and is currently constrained to power-sector
+  only parts of the workflow. A special config file
+  `config/config.entsoe-all.yaml` was added as an example to run the workflow
+  with all ENTSO-E member countries (including observer members like Ukraine and
+  Moldova). Moldova can currently only be included in conjunction with Ukraine
+  due to the absence of demand data. The Crimean power system is manually
+  reconnected to the main Ukrainian grid with the configuration option
+  `reconnect_crimea`.
+
 
 **Bugs and Compatibility**
 
 * A bug preventing custom powerplants specified in ``data/custom_powerplants.csv`` was fixed. (https://github.com/PyPSA/pypsa-eur/pull/732)
+* Fix nodal fraction in ``add_existing_year`` when using distributed generators
 
 
 PyPSA-Eur 0.8.1 (27th July 2023)

doc/retrieve.rst

@@ -22,11 +22,11 @@ Rule ``retrieve_databundle``
 Rule ``retrieve_cutout``
 ============================
 
-.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3517949.svg
-   :target: https://doi.org/10.5281/zenodo.3517949
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.6382570.svg
+   :target: https://doi.org/10.5281/zenodo.6382570
 
 Cutouts are spatio-temporal subsets of the European weather data from the `ECMWF ERA5 <https://software.ecmwf.int/wiki/display/CKB/ERA5+data+documentation>`_ reanalysis dataset and the `CMSAF SARAH-2 <https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002>`_ solar surface radiation dataset for the year 2013.
-They have been prepared by and are for use with the `atlite <https://github.com/PyPSA/atlite>`_ tool. You can either generate them yourself using the ``build_cutouts`` rule or retrieve them directly from `zenodo <https://doi.org/10.5281/zenodo.3517949>`__ through the rule ``retrieve_cutout``.
+They have been prepared by and are for use with the `atlite <https://github.com/PyPSA/atlite>`_ tool. You can either generate them yourself using the ``build_cutouts`` rule or retrieve them directly from `zenodo <https://doi.org/10.5281/zenodo.6382570>`__ through the rule ``retrieve_cutout``.
 The :ref:`tutorial` uses a smaller cutout than required for the full model (30 MB), which is also automatically downloaded.
 
 .. note::

envs/environment.yaml

@@ -11,7 +11,7 @@ dependencies:
 - pip
 
 - atlite>=0.2.9
-- pypsa==0.25.2
+- pypsa
 - linopy
 - dask
 

rules/build_electricity.smk

@@ -206,10 +206,62 @@ rule build_ship_raster:
         "../scripts/build_ship_raster.py"
 
 
+rule determine_availability_matrix_MD_UA:
+    input:
+        copernicus=RESOURCES
+        + "Copernicus_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif",
+        wdpa=RESOURCES + f"WDPA_{bYYYY}.gpkg",
+        wdpa_marine=RESOURCES + f"WDPA_WDOECM_{bYYYY}_marine.gpkg",
+        gebco=lambda w: (
+            "data/bundle/GEBCO_2014_2D.nc"
+            if "max_depth" in config["renewable"][w.technology].keys()
+            else []
+        ),
+        ship_density=lambda w: (
+            RESOURCES + "shipdensity_raster.tif"
+            if "ship_threshold" in config["renewable"][w.technology].keys()
+            else []
+        ),
+        country_shapes=RESOURCES + "country_shapes.geojson",
+        offshore_shapes=RESOURCES + "offshore_shapes.geojson",
+        regions=lambda w: (
+            RESOURCES + "regions_onshore.geojson"
+            if w.technology in ("onwind", "solar")
+            else RESOURCES + "regions_offshore.geojson"
+        ),
+        cutout=lambda w: "cutouts/"
+        + CDIR
+        + config["renewable"][w.technology]["cutout"]
+        + ".nc",
+    output:
+        availability_matrix=RESOURCES + "availability_matrix_MD-UA_{technology}.nc",
+        availability_map=RESOURCES + "availability_matrix_MD-UA_{technology}.png",
+    log:
+        LOGS + "determine_availability_matrix_MD_UA_{technology}.log",
+    threads: ATLITE_NPROCESSES
+    resources:
+        mem_mb=ATLITE_NPROCESSES * 5000,
+    conda:
+        "../envs/environment.yaml"
+    script:
+        "../scripts/determine_availability_matrix_MD_UA.py"
+
+
+# Optional input when having Ukraine (UA) or Moldova (MD) in the countries list
+if {"UA", "MD"}.intersection(set(config["countries"])):
+    opt = {
+        "availability_matrix_MD_UA": RESOURCES
+        + "availability_matrix_MD-UA_{technology}.nc"
+    }
+else:
+    opt = {}
+
+
 rule build_renewable_profiles:
     params:
         renewable=config["renewable"],
     input:
+        **opt,
         base_network=RESOURCES + "networks/base.nc",
         corine=ancient("data/bundle/corine/g250_clc06_V18_5.tif"),
         natura=lambda w: (
@@ -355,6 +407,7 @@ rule add_electricity:
         else [],
         load=RESOURCES + "load.csv",
         nuts3_shapes=RESOURCES + "nuts3_shapes.geojson",
+        ua_md_gdp="data/GDP_PPP_30arcsec_v3_mapped_default.csv",
     output:
         RESOURCES + "networks/elec.nc",
     log:
@@ -374,7 +427,9 @@ rule simplify_network:
     params:
         simplify_network=config["clustering"]["simplify_network"],
         aggregation_strategies=config["clustering"].get("aggregation_strategies", {}),
-        focus_weights=config.get("focus_weights", None),
+        focus_weights=config["clustering"].get(
+            "focus_weights", config.get("focus_weights")
+        ),
         renewable_carriers=config["electricity"]["renewable_carriers"],
         max_hours=config["electricity"]["max_hours"],
         length_factor=config["lines"]["length_factor"],
@@ -409,7 +464,9 @@ rule cluster_network:
         cluster_network=config["clustering"]["cluster_network"],
         aggregation_strategies=config["clustering"].get("aggregation_strategies", {}),
         custom_busmap=config["enable"].get("custom_busmap", False),
-        focus_weights=config.get("focus_weights", None),
+        focus_weights=config["clustering"].get(
+            "focus_weights", config.get("focus_weights")
+        ),
         renewable_carriers=config["electricity"]["renewable_carriers"],
         conventional_carriers=config["electricity"].get("conventional_carriers", []),
         max_hours=config["electricity"]["max_hours"],

rules/build_sector.smk

@@ -269,7 +269,7 @@ rule build_biomass_potentials:
         biomass=config["biomass"],
     input:
         enspreso_biomass=HTTP.remote(
-            "https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx",
+            "https://zenodo.org/records/10356004/files/ENSPRESO_BIOMASS.xlsx",
             keep_local=True,
         ),
         nuts2="data/bundle-sector/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",  # https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/#nuts21

rules/retrieve.smk

@@ -2,6 +2,9 @@
 #
 # SPDX-License-Identifier: MIT
 
+import requests
+from datetime import datetime, timedelta
+
 if config["enable"].get("retrieve", "auto") == "auto":
     config["enable"]["retrieve"] = has_internet_access()
 
@@ -224,6 +227,87 @@ if config["enable"]["retrieve"]:
         run:
             move(input[0], output[0])
 
+if config["enable"]["retrieve"]:
+
+    # Downloading Copernicus Global Land Cover for land cover and land use:
+    # Website: https://land.copernicus.eu/global/products/lc
+    rule download_copernicus_land_cover:
+        input:
+            HTTP.remote(
+                "zenodo.org/record/3939050/files/PROBAV_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif",
+                static=True,
+            ),
+        output:
+            RESOURCES + "Copernicus_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif",
+        run: move(input[0], output[0])
+
+
+if config["enable"]["retrieve"]:
+
+    current_month = datetime.now().strftime('%b')
+    current_year = datetime.now().strftime('%Y')
+    bYYYY = f"{current_month}{current_year}"
+
+    def check_file_exists(url):
+        response = requests.head(url)
+        return response.status_code == 200
+
+    url = f'https://d1gam3xoknrgr2.cloudfront.net/current/WDPA_{bYYYY}_Public.zip'
+
+    if not check_file_exists(url):
+        prev_month = (datetime.now()-timedelta(30)).strftime('%b')
+        bYYYY = f"{prev_month}{current_year}"
+        assert check_file_exists(f'https://d1gam3xoknrgr2.cloudfront.net/current/WDPA_{bYYYY}_Public.zip'), "The file does not exist."
+
+    # Downloading protected area database from WDPA
+    # extract the main zip and then merge the contained 3 zipped shapefiles
+    # Website: https://www.protectedplanet.net/en/thematic-areas/wdpa
+    rule download_wdpa:
+        input:
+            HTTP.remote(
+                f"d1gam3xoknrgr2.cloudfront.net/current/WDPA_{bYYYY}_Public_shp.zip",
+                static=True,
+                keep_local=True,
+            )
+        params:
+            zip=RESOURCES + f"WDPA_{bYYYY}_shp.zip",
+            folder=directory(RESOURCES + f"WDPA_{bYYYY}"),
+        output:
+            gpkg=RESOURCES + f"WDPA_{bYYYY}.gpkg",
+        run:
+            shell("cp {input} {params.zip}")
+            shell("unzip -o {params.zip} -d {params.folder}")
+            for i in range(3):
+                # vsizip is special driver for directly working with zipped shapefiles in ogr2ogr
+                layer_path = f"/vsizip/{params.folder}/WDPA_{bYYYY}_Public_shp_{i}.zip"
+                print(f"Adding layer {i+1} of 3 to combined output file.")
+                shell("ogr2ogr -f gpkg -update -append {output.gpkg} {layer_path}")
+
+
+    # Downloading Marine protected area database from WDPA
+    # extract the main zip and then merge the contained 3 zipped shapefiles
+    # Website: https://www.protectedplanet.net/en/thematic-areas/marine-protected-areas
+    rule download_wdpa_marine:
+        input:
+            HTTP.remote(
+                f"d1gam3xoknrgr2.cloudfront.net/current/WDPA_WDOECM_{bYYYY}_Public_marine_shp.zip",
+                static=True,
+                keep_local=True,
+            ),
+        params:
+            zip=RESOURCES + f"WDPA_WDOECM_{bYYYY}_marine.zip",
+            folder=directory(RESOURCES + f"WDPA_WDOECM_{bYYYY}_marine"),
+        output:
+            gpkg=RESOURCES + f"WDPA_WDOECM_{bYYYY}_marine.gpkg",
+        run:
+            shell("cp {input} {params.zip}")
+            shell("unzip -o {params.zip} -d {params.folder}")
+            for i in range(3):
+                # vsizip is special driver for directly working with zipped shapefiles in ogr2ogr
+                layer_path = f"/vsizip/{params.folder}/WDPA_WDOECM_{bYYYY}_Public_marine_shp_{i}.zip"
+                print(f"Adding layer {i+1} of 3 to combined output file.")
+                shell("ogr2ogr -f gpkg -update -append {output.gpkg} {layer_path}")
+
 
 if config["enable"]["retrieve"]:
 

scripts/add_electricity.py

@@ -84,6 +84,7 @@ It further adds extendable ``generators`` with **zero** capacity for
 
 import logging
 from itertools import product
+from typing import Dict, List
 
 import geopandas as gpd
 import numpy as np
@@ -255,6 +256,7 @@ def load_powerplants(ppl_fn):
         "bioenergy": "biomass",
         "ccgt, thermal": "CCGT",
         "hard coal": "coal",
+        "natural gas": "OCGT",
     }
     return (
         pd.read_csv(ppl_fn, index_col=0, dtype={"bus": "str"})
@@ -279,11 +281,13 @@ def shapes_to_shapes(orig, dest):
     return transfer
 
 
-def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
+def attach_load(n, regions, load, nuts3_shapes, ua_md_gdp, countries, scaling=1.0):
     substation_lv_i = n.buses.index[n.buses["substation_lv"]]
     regions = gpd.read_file(regions).set_index("name").reindex(substation_lv_i)
     opsd_load = pd.read_csv(load, index_col=0, parse_dates=True).filter(items=countries)
 
+    ua_md_gdp = pd.read_csv(ua_md_gdp, dtype={"name": "str"}).set_index("name")
+
     logger.info(f"Load data scaled with scalling factor {scaling}.")
     opsd_load *= scaling
 
@@ -291,6 +295,7 @@ def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
 
     def upsample(cntry, group):
         l = opsd_load[cntry]
+
         if len(group) == 1:
             return pd.DataFrame({group.index[0]: l})
         nuts3_cntry = nuts3.loc[nuts3.country == cntry]
@@ -305,6 +310,9 @@ def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
         # relative factors 0.6 and 0.4 have been determined from a linear
         # regression on the country to continent load data
         factors = normed(0.6 * normed(gdp_n) + 0.4 * normed(pop_n))
+        if cntry in ["UA", "MD"]:
+            # overwrite factor because nuts3 provides no data for UA+MD
+            factors = normed(ua_md_gdp.loc[group.index, "GDP_PPP"].squeeze())
         return pd.DataFrame(
             factors.values * l.values[:, np.newaxis],
             index=l.index,
@@ -710,7 +718,17 @@ def attach_extendable_generators(n, costs, ppl, carriers):
             )
 
 
-def attach_OPSD_renewables(n, tech_map):
+def attach_OPSD_renewables(n: pypsa.Network, tech_map: Dict[str, List[str]]) -> None:
+    """
+    Attach renewable capacities from the OPSD dataset to the network.
+
+    Args:
+    - n: The PyPSA network to attach the capacities to.
+    - tech_map: A dictionary mapping fuel types to carrier names.
+
+    Returns:
+    - None
+    """
     tech_string = ", ".join(sum(tech_map.values(), []))
     logger.info(f"Using OPSD renewable capacities for carriers {tech_string}.")
 
@@ -735,7 +753,26 @@ def attach_OPSD_renewables(n, tech_map):
         n.generators.p_nom_min.update(gens.bus.map(caps).dropna())
 
 
-def estimate_renewable_capacities(n, year, tech_map, expansion_limit, countries):
+def estimate_renewable_capacities(
+    n: pypsa.Network, year: int, tech_map: dict, expansion_limit: bool, countries: list
+) -> None:
+    """
+    Estimate a different between renewable capacities in the network and
+    reported country totals from IRENASTAT dataset. Distribute the difference
+    with a heuristic.
+
+    Heuristic: n.generators_t.p_max_pu.mean() * n.generators.p_nom_max
+
+    Args:
+    - n: The PyPSA network.
+    - year: The year of optimisation.
+    - tech_map: A dictionary mapping fuel types to carrier names.
+    - expansion_limit: Boolean value from config file
+    - countries: A list of country codes to estimate capacities for.
+
+    Returns:
+    - None
+    """
     if not len(countries) or not len(tech_map):
         return
 
@@ -752,7 +789,10 @@ def estimate_renewable_capacities(n, year, tech_map, expansion_limit, countries)
 
     for ppm_technology, techs in tech_map.items():
         tech_i = n.generators.query("carrier in @techs").index
-        stats = capacities.loc[ppm_technology].reindex(countries, fill_value=0.0)
+        if ppm_technology in capacities.index.get_level_values("Technology"):
+            stats = capacities.loc[ppm_technology].reindex(countries, fill_value=0.0)
+        else:
+            stats = pd.Series(0.0, index=countries)
         country = n.generators.bus[tech_i].map(n.buses.country)
         existent = n.generators.p_nom[tech_i].groupby(country).sum()
         missing = stats - existent
@@ -825,6 +865,7 @@ if __name__ == "__main__":
         snakemake.input.regions,
         snakemake.input.load,
         snakemake.input.nuts3_shapes,
+        snakemake.input.ua_md_gdp,
         params.countries,
         params.scaling_factor,
     )

scripts/add_existing_baseyear.py

@@ -88,7 +88,9 @@ def add_existing_renewables(df_agg):
             ]
             cfs = n.generators_t.p_max_pu[gens].mean()
             cfs_key = cfs / cfs.sum()
-            nodal_fraction.loc[n.generators.loc[gens, "bus"]] = cfs_key.values
+            nodal_fraction.loc[n.generators.loc[gens, "bus"]] = cfs_key.groupby(
+                n.generators.loc[gens, "bus"]
+            ).sum()
 
         nodal_df = df.loc[n.buses.loc[elec_buses, "country"]]
         nodal_df.index = elec_buses

scripts/base_network.py

@@ -366,6 +366,25 @@ def _apply_parameter_corrections(n, parameter_corrections):
                 df.loc[inds, attr] = r[inds].astype(df[attr].dtype)
 
 
+def _reconnect_crimea(lines):
+    logger.info("Reconnecting Crimea to the Ukrainian grid.")
+    lines_to_crimea = pd.DataFrame(
+        {
+            "bus0": ["3065", "3181", "3181"],
+            "bus1": ["3057", "3055", "3057"],
+            "v_nom": [300, 300, 300],
+            "num_parallel": [1, 1, 1],
+            "length": [140, 120, 140],
+            "carrier": ["AC", "AC", "AC"],
+            "underground": [False, False, False],
+            "under_construction": [False, False, False],
+        },
+        index=["Melitopol", "Liubymivka left", "Luibymivka right"],
+    )
+
+    return pd.concat([lines, lines_to_crimea])
+
+
 def _set_electrical_parameters_lines(lines, config):
     v_noms = config["electricity"]["voltages"]
     linetypes = config["lines"]["types"]
@@ -450,12 +469,12 @@ def _remove_dangling_branches(branches, buses):
     )
 
 
-def _remove_unconnected_components(network):
+def _remove_unconnected_components(network, threshold=6):
     _, labels = csgraph.connected_components(network.adjacency_matrix(), directed=False)
     component = pd.Series(labels, index=network.buses.index)
 
     component_sizes = component.value_counts()
-    components_to_remove = component_sizes.iloc[1:]
+    components_to_remove = component_sizes.loc[component_sizes < threshold]
 
     logger.info(
         f"Removing {len(components_to_remove)} unconnected network components with less than {components_to_remove.max()} buses. In total {components_to_remove.sum()} buses."
@@ -699,6 +718,9 @@ def base_network(
     lines = _load_lines_from_eg(buses, eg_lines)
     transformers = _load_transformers_from_eg(buses, eg_transformers)
 
+    if config["lines"].get("reconnect_crimea", True) and "UA" in config["countries"]:
+        lines = _reconnect_crimea(lines)
+
     lines = _set_electrical_parameters_lines(lines, config)
     transformers = _set_electrical_parameters_transformers(transformers, config)
     links = _set_electrical_parameters_links(links, config, links_p_nom)

scripts/build_electricity_demand.py

@@ -155,7 +155,7 @@ def copy_timeslice(load, cntry, start, stop, delta, fn_load=None):
             ].values
 
 
-def manual_adjustment(load, fn_load, powerstatistics):
+def manual_adjustment(load, fn_load, powerstatistics, countries):
     """
     Adjust gaps manual for load data from OPSD time-series package.
 
@@ -278,6 +278,14 @@ def manual_adjustment(load, fn_load, powerstatistics):
             load, "LU", "2019-02-05 20:00", "2019-02-06 19:00", Delta(weeks=-1)
         )
 
+    if "UA" in countries:
+        copy_timeslice(
+            load, "UA", "2013-01-25 14:00", "2013-01-28 21:00", Delta(weeks=1)
+        )
+        copy_timeslice(
+            load, "UA", "2013-10-28 03:00", "2013-10-28 20:00", Delta(weeks=1)
+        )
+
     return load
 
 
@@ -298,8 +306,22 @@ if __name__ == "__main__":
 
     load = load_timeseries(snakemake.input[0], years, countries, powerstatistics)
 
+    if "UA" in countries:
+        # attach load of UA (best data only for entsoe transparency)
+        load_ua = load_timeseries(snakemake.input[0], "2018", ["UA"], False)
+        snapshot_year = str(snapshots.year.unique().item())
+        time_diff = pd.Timestamp("2018") - pd.Timestamp(snapshot_year)
+        load_ua.index -= (
+            time_diff  # hack indices (currently, UA is manually set to 2018)
+        )
+        load["UA"] = load_ua
+        # attach load of MD (no time-series available, use 2020-totals and distribute according to UA):
+        # https://www.iea.org/data-and-statistics/data-browser/?country=MOLDOVA&fuel=Energy%20consumption&indicator=TotElecCons
+        if "MD" in countries:
+            load["MD"] = 6.2e6 * (load_ua / load_ua.sum())
+
     if snakemake.params.load["manual_adjustments"]:
-        load = manual_adjustment(load, snakemake.input[0], powerstatistics)
+        load = manual_adjustment(load, snakemake.input[0], powerstatistics, countries)
 
     if load.empty:
         logger.warning("Build electricity demand time series is empty.")

scripts/build_hydro_profile.py

@@ -26,7 +26,7 @@ Relevant Settings
 Inputs
 ------
 
-- ``data/bundle/EIA_hydro_generation_2000_2014.csv``: Hydroelectricity net generation per country and year (`EIA <https://www.eia.gov/beta/international/data/browser/#/?pa=000000000000000000000000000000g&c=1028i008006gg6168g80a4k000e0ag00gg0004g800ho00g8&ct=0&ug=8&tl_id=2-A&vs=INTL.33-12-ALB-BKWH.A&cy=2014&vo=0&v=H&start=2000&end=2016>`_)
+- ``data/bundle/eia_hydro_annual_generation.csv``: Hydroelectricity net generation per country and year (`EIA <https://www.eia.gov/beta/international/data/browser/#/?pa=000000000000000000000000000000g&c=1028i008006gg6168g80a4k000e0ag00gg0004g800ho00g8&ct=0&ug=8&tl_id=2-A&vs=INTL.33-12-ALB-BKWH.A&cy=2014&vo=0&v=H&start=2000&end=2016>`_)
 
     .. image:: img/hydrogeneration.png
         :scale: 33 %
@@ -72,12 +72,14 @@ cc = coco.CountryConverter()
 
 def get_eia_annual_hydro_generation(fn, countries):
     # in billion kWh/a = TWh/a
-    df = pd.read_csv(fn, skiprows=2, index_col=1, na_values=[" ", "--"]).iloc[1:, 1:]
+    df = pd.read_csv(
+        fn, skiprows=2, index_col=1, na_values=[" ", "--"], decimal=","
+    ).iloc[1:, 1:]
     df.index = df.index.str.strip()
 
     former_countries = {
         "Former Czechoslovakia": dict(
-            countries=["Czech Republic", "Slovakia"], start=1980, end=1992
+            countries=["Czechia", "Slovakia"], start=1980, end=1992
         ),
         "Former Serbia and Montenegro": dict(
             countries=["Serbia", "Montenegro"], start=1992, end=2005

scripts/build_renewable_profiles.py

@@ -287,6 +287,14 @@ if __name__ == "__main__":
     else:
         availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
 
+    # For Moldova and Ukraine: Overwrite parts not covered by Corine with
+    # externally determined available areas
+    if "availability_matrix_MD_UA" in snakemake.input.keys():
+        availability_MDUA = xr.open_dataarray(
+            snakemake.input["availability_matrix_MD_UA"]
+        )
+        availability.loc[availability_MDUA.coords] = availability_MDUA
+
     area = cutout.grid.to_crs(3035).area / 1e6
     area = xr.DataArray(
         area.values.reshape(cutout.shape), [cutout.coords["y"], cutout.coords["x"]]

scripts/build_shapes.py

@@ -174,8 +174,8 @@ def nuts3(country_shapes, nuts3, nuts3pop, nuts3gdp, ch_cantons, ch_popgdp):
             pd.MultiIndex.from_tuples(pop.pop("unit,geo\\time").str.split(","))
         )
         .loc["THS"]
-        .applymap(lambda x: pd.to_numeric(x, errors="coerce"))
-        .fillna(method="bfill", axis=1)
+        .map(lambda x: pd.to_numeric(x, errors="coerce"))
+        .bfill(axis=1)
     )["2014"]
 
     gdp = pd.read_table(nuts3gdp, na_values=[":"], delimiter=" ?\t", engine="python")
@@ -184,8 +184,8 @@ def nuts3(country_shapes, nuts3, nuts3pop, nuts3gdp, ch_cantons, ch_popgdp):
             pd.MultiIndex.from_tuples(gdp.pop("unit,geo\\time").str.split(","))
         )
         .loc["EUR_HAB"]
-        .applymap(lambda x: pd.to_numeric(x, errors="coerce"))
-        .fillna(method="bfill", axis=1)
+        .map(lambda x: pd.to_numeric(x, errors="coerce"))
+        .bfill(axis=1)
     )["2014"]
 
     cantons = pd.read_csv(ch_cantons)

scripts/cluster_network.py

@@ -16,8 +16,7 @@ Relevant Settings
     clustering:
       cluster_network:
       aggregation_strategies:
-
-    focus_weights:
+      focus_weights:
 
     solving:
         solver:
@@ -271,7 +270,7 @@ def distribute_clusters(n, n_clusters, focus_weights=None, solver_name="cbc"):
     )
 
     opt = po.SolverFactory(solver_name)
-    if not opt.has_capability("quadratic_objective"):
+    if solver_name == "appsi_highs" or not opt.has_capability("quadratic_objective"):
         logger.warning(
             f"The configured solver `{solver_name}` does not support quadratic objectives. Falling back to `ipopt`."
         )
@@ -466,9 +465,13 @@ if __name__ == "__main__":
 
     params = snakemake.params
     solver_name = snakemake.config["solving"]["solver"]["name"]
+    solver_name = "appsi_highs" if solver_name == "highs" else solver_name
 
     n = pypsa.Network(snakemake.input.network)
 
+    # remove integer outputs for compatibility with PyPSA v0.26.0
+    n.generators.drop("n_mod", axis=1, inplace=True, errors='ignore')
+
     exclude_carriers = params.cluster_network["exclude_carriers"]
     aggregate_carriers = set(n.generators.carrier) - set(exclude_carriers)
     conventional_carriers = set(params.conventional_carriers)

scripts/determine_availability_matrix_MD_UA.py

@@ -0,0 +1,156 @@
+# -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: MIT
+
+import functools
+import logging
+import time
+
+import atlite
+import fiona
+import geopandas as gpd
+import matplotlib.pyplot as plt
+import numpy as np
+from _helpers import configure_logging
+from atlite.gis import shape_availability
+from rasterio.plot import show
+
+logger = logging.getLogger(__name__)
+
+
+def get_wdpa_layer_name(wdpa_fn, layer_substring):
+    """
+    Get layername from file "wdpa_fn" whose name contains "layer_substring".
+    """
+    l = fiona.listlayers(wdpa_fn)
+    return [_ for _ in l if layer_substring in _][0]
+
+
+if __name__ == "__main__":
+    if "snakemake" not in globals():
+        from _helpers import mock_snakemake
+
+        snakemake = mock_snakemake(
+            "determine_availability_matrix_MD_UA", technology="solar"
+        )
+    configure_logging(snakemake)
+
+    nprocesses = None  # snakemake.config["atlite"].get("nprocesses")
+    noprogress = not snakemake.config["atlite"].get("show_progress", True)
+    config = snakemake.config["renewable"][snakemake.wildcards.technology]
+
+    cutout = atlite.Cutout(snakemake.input.cutout)
+    regions = (
+        gpd.read_file(snakemake.input.regions).set_index("name").rename_axis("bus")
+    )
+    buses = regions.index
+
+    excluder = atlite.ExclusionContainer(crs=3035, res=100)
+
+    corine = config.get("corine", {})
+    if "grid_codes" in corine:
+        # Land cover codes to emulate CORINE results
+        if snakemake.wildcards.technology == "solar":
+            codes = [20, 30, 40, 50, 60, 90, 100]
+        elif snakemake.wildcards.technology == "onwind":
+            codes = [20, 30, 40, 60, 100]
+        elif snakemake.wildcards.technology == "offwind-ac":
+            codes = [80, 200]
+        elif snakemake.wildcards.technology == "offwind-dc":
+            codes = [80, 200]
+        else:
+            assert False, "technology not supported"
+
+        excluder.add_raster(
+            snakemake.input.copernicus, codes=codes, invert=True, crs="EPSG:4326"
+        )
+    if "distance" in corine and corine.get("distance", 0.0) > 0.0:
+        # Land cover codes to emulate CORINE results
+        if snakemake.wildcards.technology == "onwind":
+            codes = [50]
+        else:
+            assert False, "technology not supported"
+
+        buffer = corine["distance"]
+        excluder.add_raster(
+            snakemake.input.copernicus, codes=codes, buffer=buffer, crs="EPSG:4326"
+        )
+
+    if config["natura"]:
+        wdpa_fn = (
+            snakemake.input.wdpa_marine
+            if "offwind" in snakemake.wildcards.technology
+            else snakemake.input.wdpa
+        )
+        layer = get_wdpa_layer_name(wdpa_fn, "polygons")
+        wdpa = gpd.read_file(
+            wdpa_fn,
+            bbox=regions.geometry,
+            layer=layer,
+        ).to_crs(3035)
+        if not wdpa.empty:
+            excluder.add_geometry(wdpa.geometry)
+
+        layer = get_wdpa_layer_name(wdpa_fn, "points")
+        wdpa_pts = gpd.read_file(
+            wdpa_fn,
+            bbox=regions.geometry,
+            layer=layer,
+        ).to_crs(3035)
+        wdpa_pts = wdpa_pts[wdpa_pts["REP_AREA"] > 1]
+        wdpa_pts["buffer_radius"] = np.sqrt(wdpa_pts["REP_AREA"] / np.pi) * 1000
+        wdpa_pts = wdpa_pts.set_geometry(
+            wdpa_pts["geometry"].buffer(wdpa_pts["buffer_radius"])
+        )
+        if not wdpa_pts.empty:
+            excluder.add_geometry(wdpa_pts.geometry)
+
+    if "max_depth" in config:
+        # lambda not supported for atlite + multiprocessing
+        # use named function np.greater with partially frozen argument instead
+        # and exclude areas where: -max_depth > grid cell depth
+        func = functools.partial(np.greater, -config["max_depth"])
+        excluder.add_raster(snakemake.input.gebco, codes=func, crs=4236, nodata=-1000)
+
+    if "min_shore_distance" in config:
+        buffer = config["min_shore_distance"]
+        excluder.add_geometry(snakemake.input.country_shapes, buffer=buffer)
+
+    if "max_shore_distance" in config:
+        buffer = config["max_shore_distance"]
+        excluder.add_geometry(
+            snakemake.input.country_shapes, buffer=buffer, invert=True
+        )
+
+    if "ship_threshold" in config:
+        shipping_threshold = config["ship_threshold"] * 8760 * 6
+        func = functools.partial(np.less, shipping_threshold)
+        excluder.add_raster(
+            snakemake.input.ship_density, codes=func, crs=4326, allow_no_overlap=True
+        )
+
+    kwargs = dict(nprocesses=nprocesses, disable_progressbar=noprogress)
+    if noprogress:
+        logger.info("Calculate landuse availabilities...")
+        start = time.time()
+        availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
+        duration = time.time() - start
+        logger.info(f"Completed availability calculation ({duration:2.2f}s)")
+    else:
+        availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
+
+    regions_geometry = regions.to_crs(3035).geometry
+    band, transform = shape_availability(regions_geometry, excluder)
+    fig, ax = plt.subplots(figsize=(4, 8))
+    gpd.GeoSeries(regions_geometry.unary_union).plot(ax=ax, color="none")
+    show(band, transform=transform, cmap="Greens", ax=ax)
+    plt.axis("off")
+    plt.savefig(snakemake.output.availability_map, bbox_inches="tight", dpi=500)
+
+    # Limit results only to buses for UA and MD
+    buses = regions.loc[regions["country"].isin(["UA", "MD"])].index.values
+    availability = availability.sel(bus=buses)
+
+    # Save and plot for verification
+    availability.to_netcdf(snakemake.output.availability_matrix)

scripts/prepare_sector_network.py

@@ -145,6 +145,8 @@ def define_spatial(nodes, options):
     spatial.coal = SimpleNamespace()
     spatial.coal.nodes = ["EU coal"]
     spatial.coal.locations = ["EU"]
+    spatial.coal.industry = ["coal for industry"]
+    spatial.coal.industry_cc = ["coal for industry CC"]
 
     # lignite
     spatial.lignite = SimpleNamespace()
@@ -2003,7 +2005,11 @@ def add_heat(n, costs):
             space_heat_demand = demand * w_space[sec][node]
             # normed time profile of space heat demand 'space_pu' (values between 0-1),
             # p_max_pu/p_min_pu of retrofitting generators
-            space_pu = (space_heat_demand / space_heat_demand.max()).to_frame(name=node)
+            space_pu = (
+                (space_heat_demand / space_heat_demand.max())
+                .to_frame(name=node)
+                .fillna(0)
+            )
 
             # minimum heat demand 'dE' after retrofitting in units of original heat demand (values between 0-1)
             dE = retro_data.loc[(ct, sec), ("dE")]
@@ -2015,6 +2021,9 @@ def add_heat(n, costs):
                 * floor_area_node
                 / ((1 - dE) * space_heat_demand.max())
             )
+            if space_heat_demand.max() == 0:
+                capital_cost = capital_cost.apply(lambda b: 0 if b == np.inf else b)
+
             # number of possible retrofitting measures 'strengths' (set in list at config.yaml 'l_strength')
             # given in additional insulation thickness [m]
             # for each measure, a retrofitting generator is added at the node
@@ -2907,15 +2916,56 @@ def add_industry(n, costs):
             + mwh_coal_per_mwh_coke * industrial_demand["coke"].sum()
         ) / nhours
 
+        n.madd(
+            "Bus",
+            spatial.coal.industry,
+            location=spatial.coal.locations,
+            carrier="coal for industry",
+            unit="MWh_LHV",
+        )
+
         n.madd(
             "Load",
-            spatial.coal.nodes,
-            suffix=" for industry",
-            bus=spatial.coal.nodes,
+            spatial.coal.industry,
+            bus=spatial.coal.industry,
             carrier="coal for industry",
             p_set=p_set,
         )
 
+        n.madd(
+            "Link",
+            spatial.coal.industry,
+            bus0=spatial.coal.nodes,
+            bus1=spatial.coal.industry,
+            bus2="co2 atmosphere",
+            carrier="coal for industry",
+            p_nom_extendable=True,
+            p_min_pu=1.0,
+            efficiency=1.0,
+            efficiency2=costs.at["coal", "CO2 intensity"],
+        )
+
+        if options.get("coal_for_industry_cc", False):
+            n.madd(
+                "Link",
+                spatial.coal.industry_cc,
+                bus0=spatial.coal.nodes,
+                bus1=spatial.coal.industry,
+                bus2="co2 atmosphere",
+                bus3=spatial.co2.nodes,
+                carrier="coal for industry CC",
+                p_min_pu=1.0,
+                p_nom_extendable=True,
+                capital_cost=costs.at["cement capture", "fixed"]
+                * costs.at["coal", "CO2 intensity"],
+                efficiency=0.9,
+                efficiency2=costs.at["coal", "CO2 intensity"]
+                * (1 - costs.at["cement capture", "capture_rate"]),
+                efficiency3=costs.at["coal", "CO2 intensity"]
+                * costs.at["cement capture", "capture_rate"],
+                lifetime=costs.at["cement capture", "lifetime"],
+            )
+
 
 def add_waste_heat(n):
     # TODO options?

scripts/simplify_network.py

@@ -536,6 +536,9 @@ if __name__ == "__main__":
     n = pypsa.Network(snakemake.input.network)
     Nyears = n.snapshot_weightings.objective.sum() / 8760
 
+    # remove integer outputs for compatibility with PyPSA v0.26.0
+    n.generators.drop("n_mod", axis=1, inplace=True, errors='ignore')
+
     n, trafo_map = simplify_network_to_380(n)
 
     technology_costs = load_costs(