Merge branch 'master' into reduced-data-bundle

.github/workflows/ci.yaml

@@ -31,7 +31,7 @@ jobs:
         os:
         - ubuntu-latest
         - macos-latest
-#        - windows-latest
+        - windows-latest
         inhouse:
         - stable
         - master

.pre-commit-config.yaml

@@ -51,7 +51,7 @@ repos:
 
   # Formatting with "black" coding style
 - repo: https://github.com/psf/black-pre-commit-mirror
-  rev: 24.3.0
+  rev: 24.4.2
   hooks:
       # Format Python files
   - id: black
@@ -74,7 +74,7 @@ repos:
 
   # Format Snakemake rule / workflow files
 - repo: https://github.com/snakemake/snakefmt
-  rev: v0.10.0
+  rev: v0.10.1
   hooks:
   - id: snakefmt
 

Snakefile

@@ -8,7 +8,7 @@ from os.path import normpath, exists
 from shutil import copyfile, move, rmtree
 from snakemake.utils import min_version
 
-min_version("8.5")
+min_version("8.11")
 
 from scripts._helpers import path_provider, copy_default_files, get_scenarios, get_rdir
 

config/config.default.yaml

@@ -71,7 +71,6 @@ enable:
   retrieve_databundle: true
   retrieve_cost_data: true
   build_cutout: false
-  retrieve_irena: false
   retrieve_cutout: true
   custom_busmap: false
   drop_leap_day: true
@@ -767,7 +766,7 @@ solving:
 
   solver_options:
     highs-default:
-      # refer to https://ergo-code.github.io/HiGHS/options/definitions.html#solver
+      # refer to https://ergo-code.github.io/HiGHS/dev/options/definitions/
       threads: 4
       solver: "ipm"
       run_crossover: "off"

data/existing_infrastructure/offwind_capacity_IRENA.csv

@@ -1,34 +0,0 @@
-Country/area,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022
-Albania,,,,,,,,,,,,,,,,,,,,,,,
-Austria,,,,,,,,,,,,,,,,,,,,,,,
-Belgium,,,,,,,,,,31.5,196.5,196.5,381.0,707.7,707.7,712.0,712.2,877.2,1185.9,1555.5,2261.8,2261.8,2261.8
-Bosnia Herzg,,,,,,,,,,,,,,,,,,,,,,,
-Bulgaria,,,,,,,,,,,,,,,,,,,,,,,
-Croatia,,,,,,,,,,,,,,,,,,,,,,,
-Czechia,,,,,,,,,,,,,,,,,,,,,,,
-Denmark,49.95,49.95,213.95,423.35,423.35,423.35,423.35,423.35,423.35,660.85,867.85,871.45,921.85,1271.05,1271.05,1271.05,1271.05,1263.8,1700.8,1700.8,1700.8,2305.6,2305.6
-Estonia,,,,,,,,,,,,,,,,,,,,,,,
-Finland,,,,,,,,,24.0,24.0,26.3,26.3,26.3,26.3,26.3,32.0,32.0,72.7,72.7,73.0,73.0,73.0,73.0
-France,,,,,,,,,,,,,,,,,,2.0,2.0,2.0,2.0,2.0,482.0
-Germany,,,,,,,,,,35.0,80.0,188.0,268.0,508.0,994.0,3283.0,4132.0,5406.0,6393.0,7555.0,7787.0,7787.0,8129.0
-Greece,,,,,,,,,,,,,,,,,,,,,,,
-Hungary,,,,,,,,,,,,,,,,,,,,,,,
-Ireland,,,,,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2
-Italy,,,,,,,,,,,,,,,,,,,,,,,30.0
-Latvia,,,,,,,,,,,,,,,,,,,,,,,
-Lithuania,,,,,,,,,,,,,,,,,,,,,,,
-Luxembourg,,,,,,,,,,,,,,,,,,,,,,,
-Montenegro,,,,,,,,,,,,,,,,,,,,,,,
-Netherlands,,,,,,,108.0,108.0,228.0,228.0,228.0,228.0,228.0,228.0,228.0,357.0,957.0,957.0,957.0,957.0,2459.5,2459.5,2571.0
-North Macedonia,,,,,,,,,,,,,,,,,,,,,,,
-Norway,,,,,,,,,,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,6.3,66.3
-Poland,,,,,,,,,,,,,,,,,,,,,,,
-Portugal,,,,,,,,,,,,1.86,2.0,2.0,2.0,2.0,,,,,25.0,25.0,25.0
-Romania,,,,,,,,,,,,,,,,,,,,,,,
-Serbia,,,,,,,,,,,,,,,,,,,,,,,
-Slovakia,,,,,,,,,,,,,,,,,,,,,,,
-Slovenia,,,,,,,,,,,,,,,,,,,,,,,
-Spain,,,,,,,,,,,,,,5.0,5.0,5.0,5.0,5.0,5.0,5.0,5.0,5.0,5.0
-Sweden,13.0,22.0,22.0,22.0,22.0,22.0,22.0,131.0,133.0,163.0,163.0,163.0,163.0,212.0,213.0,213.0,203.0,203.0,203.0,203.0,203.0,193.0,193.0
-Switzerland,,,,,,,,,,,,,,,,,,,,,,,
-UK,4.0,4.0,4.0,64.0,124.0,214.0,304.0,394.0,596.2,951.0,1341.0,1838.0,2995.0,3696.0,4501.0,5093.0,5293.0,6988.0,8181.0,9888.0,10383.0,11255.0,13928.0

data/existing_infrastructure/onwind_capacity_IRENA.csv

@@ -1,34 +0,0 @@
-Country/area,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022
-Albania,,,,,,,,,,,,,,,,,,,,,,,
-Austria,50.0,67.0,109.0,322.0,581.0,825.22,968.27,991.16,991.97,1000.99,1015.83,1105.97,1337.15,1674.54,2110.28,2488.73,2730.0,2886.7,3132.71,3224.12,3225.98,3407.81,3735.81
-Belgium,14.0,26.0,31.0,67.0,96.0,167.0,212.0,276.0,324.0,576.5,715.5,872.5,985.9,1061.3,1225.0,1469.3,1621.6,1902.2,2119.0,2308.0,2410.9,2686.6,2989.6
-Bosnia Herzg,,,,,,,,,,,,0.3,0.3,0.3,0.3,0.3,0.3,0.3,51.0,87.0,87.0,135.0,135.0
-Bulgaria,,,,,1.0,8.0,27.0,30.0,114.0,333.0,488.0,541.0,677.0,683.0,699.0,699.0,699.0,698.39,698.92,703.12,702.8,704.38,704.38
-Croatia,,,,,6.0,6.0,17.0,17.0,17.0,70.0,79.0,130.0,180.0,254.0,339.0,418.0,483.0,576.1,586.3,646.3,801.3,986.9,1042.9
-Czechia,2.0,,6.4,10.6,16.5,22.0,43.5,113.8,150.0,193.0,213.0,213.0,258.0,262.0,278.0,281.0,282.0,308.21,316.2,339.41,339.42,339.41,339.41
-Denmark,2340.07,2447.2,2680.58,2696.57,2700.36,2704.49,2712.35,2700.86,2739.52,2821.24,2933.98,3080.53,3240.09,3547.87,3615.35,3805.92,3974.09,4225.15,4421.86,4409.74,4566.23,4715.24,4782.24
-Estonia,,,1.0,3.0,7.0,31.0,31.0,50.0,77.0,104.0,108.0,180.0,266.0,248.0,275.0,300.0,310.0,311.8,310.0,316.0,317.0,315.0,315.0
-Finland,38.0,39.0,43.0,52.0,82.0,82.0,86.0,110.0,119.0,123.0,170.7,172.7,230.7,420.7,600.7,973.0,1533.0,1971.3,1968.3,2211.0,2513.0,3184.0,5541.0
-France,38.0,66.0,138.0,218.0,358.0,690.0,1412.0,2223.0,3403.0,4582.0,5912.0,6758.02,7607.5,8155.96,9201.42,10298.18,11566.56,13497.35,14898.14,16424.85,17512.0,18737.98,20637.98
-Germany,6095.0,8754.0,12001.0,14381.0,16419.0,18248.0,20474.0,22116.0,22794.0,25697.0,26823.0,28524.0,30711.0,32969.0,37620.0,41297.0,45303.0,50174.0,52328.0,53187.0,54414.0,56046.0,58165.0
-Greece,226.0,270.0,287.0,371.0,470.0,491.0,749.0,846.0,1022.0,1171.0,1298.0,1640.0,1753.0,1809.0,1978.0,2091.0,2370.0,2624.0,2877.5,3589.0,4119.25,4649.13,4879.13
-Hungary,,1.0,1.0,3.0,3.0,17.0,33.0,61.0,134.0,203.0,293.0,331.0,325.0,329.0,329.0,329.0,329.0,329.0,329.0,323.0,323.0,324.0,324.0
-Ireland,116.5,122.9,134.8,210.3,311.2,468.1,651.3,715.3,917.1,1226.1,1365.2,1559.4,1679.15,1898.1,2258.05,2425.95,2776.45,3293.95,3648.65,4101.25,4281.5,4313.84,4593.84
-Italy,363.0,664.0,780.0,874.0,1127.0,1635.0,1902.0,2702.0,3525.0,4879.0,5794.0,6918.0,8102.0,8542.0,8683.0,9137.0,9384.0,9736.58,10230.25,10679.46,10870.62,11253.73,11749.73
-Latvia,2.0,2.0,22.0,26.0,26.0,26.0,26.0,26.0,28.0,29.0,30.0,36.0,59.0,65.89,68.92,68.17,69.91,77.11,78.17,78.07,78.07,77.13,136.13
-Lithuania,,,,,1.0,1.0,31.0,47.0,54.0,98.0,133.0,202.0,275.0,279.0,288.0,436.0,509.0,518.0,533.0,534.0,540.0,671.0,814.0
-Luxembourg,14.0,13.9,13.9,20.5,34.9,34.9,34.9,34.9,42.92,42.93,43.73,44.53,58.33,58.33,58.34,63.79,119.69,119.69,122.89,135.79,152.74,136.44,165.44
-Montenegro,,,,,,,,,,,,,,,,,,72.0,72.0,118.0,118.0,118.0,118.0
-Netherlands,447.0,486.0,672.0,905.0,1075.0,1224.0,1453.0,1641.0,1921.0,1994.0,2009.0,2088.0,2205.0,2485.0,2637.0,3033.84,3300.12,3245.0,3436.11,3527.16,4188.38,5309.87,6176.0
-North Macedonia,,,,,,,,,,,,,,,37.0,37.0,37.0,37.0,37.0,37.0,37.0,37.0,37.0
-Norway,13.0,13.0,97.0,97.0,152.0,265.0,284.0,348.0,395.0,420.7,422.7,509.7,702.7,815.7,856.7,864.7,880.7,1204.7,1707.7,2911.7,4027.7,5042.7,5067.7
-Poland,4.0,19.0,32.0,35.0,40.0,121.0,172.0,306.0,526.0,709.0,1108.0,1800.0,2564.0,3429.0,3836.0,4886.0,5747.0,5759.36,5766.08,5837.76,6298.25,6967.34,7987.34
-Portugal,83.0,125.0,190.0,268.0,553.0,1064.0,1681.0,2201.0,2857.0,3326.0,3796.0,4254.35,4409.55,4607.95,4854.56,4934.84,5124.1,5124.1,5172.36,5222.75,5097.26,5402.33,5430.33
-Romania,,,,,,1.0,1.0,3.0,5.0,15.0,389.0,988.0,1822.0,2773.0,3244.0,3130.0,3025.0,3029.8,3032.26,3037.52,3012.53,3014.96,3014.96
-Serbia,,,,,,,,,,,,,0.5,0.5,0.5,10.4,17.0,25.0,227.0,398.0,398.0,398.0,398.0
-Slovakia,,,,3.0,3.0,5.0,5.0,5.0,5.0,3.0,3.0,3.0,3.0,5.0,3.0,3.0,3.0,4.0,3.0,4.0,4.0,4.0,4.0
-Slovenia,,,,,,,,,,,,,2.0,2.0,3.0,3.0,3.0,3.3,3.3,3.3,3.3,3.33,3.33
-Spain,2206.0,3397.0,4891.0,5945.0,8317.0,9918.0,11722.0,14820.0,16555.0,19176.0,20693.0,21529.0,22789.0,22953.0,22920.0,22938.0,22985.0,23119.48,23400.06,25585.08,26814.19,27902.65,29302.84
-Sweden,196.0,273.0,335.0,395.0,453.0,500.0,563.0,692.0,956.0,1312.0,1854.0,2601.0,3443.0,3982.0,4875.0,5606.0,6232.0,6408.0,7097.0,8478.0,9773.0,11923.0,14364.0
-Switzerland,3.0,5.0,5.0,5.0,9.0,12.0,12.0,12.0,14.0,18.0,42.0,46.0,49.0,60.0,60.0,60.0,75.0,75.0,75.0,75.0,87.0,87.0,87.0
-UK,431.0,490.0,531.0,678.0,809.0,1351.0,1651.0,2083.0,2849.8,3468.0,4080.0,4758.0,6035.0,7586.0,8573.0,9212.0,10833.0,12597.0,13425.0,13999.0,14075.0,14492.0,14832.0

data/existing_infrastructure/solar_capacity_IRENA.csv

@@ -1,34 +0,0 @@
-Country/area,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022
-Albania,,0.1,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.3,0.4,0.56,0.68,0.76,0.87,1.05,1.0,1.0,1.0,14.0,21.0,23.0,28.6
-Austria,5.0,7.0,9.0,23.0,27.0,18.49,19.61,21.42,27.0,45.56,85.27,169.88,333.09,620.78,779.76,931.56,1089.53,1262.01,1447.94,1694.4,2034.74,2773.91,3538.91
-Belgium,,,1.0,1.0,1.0,2.0,2.0,20.0,62.0,386.0,1006.6,1978.6,2646.6,2901.6,3015.0,3131.6,3328.8,3620.6,4000.0,4636.6,5572.8,6012.4,6898.4
-Bosnia Herzg,,,,0.1,0.2,0.3,0.3,0.3,0.3,0.3,0.3,0.3,0.35,1.34,7.17,8.17,14.12,16.0,18.15,22.35,34.89,56.51,107.47
-Bulgaria,,,,,,,,0.03,0.1,2.0,25.0,154.0,921.99,1038.54,1028.92,1027.89,1029.89,1030.7,1033.06,1044.39,1100.21,1274.71,1948.36
-Croatia,,,,,,,,,,0.3,0.3,0.3,4.0,19.0,33.0,47.8,55.8,60.0,67.7,84.8,108.5,138.3,182.3
-Czechia,0.1,0.1,0.2,0.3,0.4,0.59,0.84,3.96,39.5,464.6,1727.0,1913.0,2022.0,2063.5,2067.4,2074.9,2067.9,2075.44,2081.05,2110.67,2171.96,2246.09,2627.09
-Denmark,1.0,1.0,2.0,2.0,2.0,3.0,3.0,3.0,3.0,5.0,7.0,17.0,402.0,571.0,607.0,782.11,850.95,906.35,998.0,1080.0,1304.29,1704.04,3122.04
-Estonia,,,,,,,,,,0.1,0.1,0.2,0.38,1.5,3.34,6.5,10.0,15.0,31.9,120.6,207.67,394.77,534.77
-Finland,2.0,3.0,3.0,3.0,4.0,4.0,5.0,5.0,6.0,6.0,7.0,7.0,8.0,9.0,11.0,17.0,39.0,82.0,140.0,222.0,318.0,425.0,590.6
-France,7.0,7.0,8.0,9.0,11.0,13.0,15.0,26.0,80.0,277.0,1044.0,3003.57,4358.75,5277.29,6034.42,7137.52,7702.08,8610.44,9638.88,10738.39,11812.2,14436.97,17036.97
-Germany,114.0,195.0,260.0,435.0,1105.0,2056.0,2899.0,4170.0,6120.0,10564.0,18004.0,25914.0,34075.0,36708.0,37898.0,39222.0,40677.0,42291.0,45156.0,48912.0,53669.0,59371.0,66662.0
-Greece,,1.0,1.0,1.0,1.0,1.0,5.0,9.0,12.0,46.0,202.0,612.0,1536.0,2579.0,2596.0,2604.0,2604.0,2605.53,2651.57,2833.79,3287.72,4277.42,5557.42
-Hungary,,,,,,,,0.4,1.0,1.0,2.0,4.0,12.0,35.0,89.0,172.0,235.0,344.0,728.0,1400.0,2131.0,2968.0,2988.0
-Ireland,,,,,,,,,,,,,,,,,,,,,,,
-Italy,19.0,20.0,22.0,26.0,31.0,34.0,45.0,110.0,483.0,1264.0,3592.0,13131.0,16785.0,18185.0,18594.0,18901.0,19283.0,19682.29,20107.59,20865.28,21650.04,22594.26,25076.56
-Latvia,,,,,,,,,,,,,,,,,0.69,0.69,1.96,3.3,5.1,7.16,56.16
-Lithuania,,,,,,,,,0.1,0.1,0.1,0.3,7.0,68.0,69.0,69.0,70.0,70.08,72.0,73.0,80.0,84.0,397.0
-Luxembourg,,0.16,1.59,14.17,23.56,23.58,23.7,23.93,24.56,26.36,29.45,40.67,74.65,95.02,109.93,116.27,121.9,128.1,130.62,159.74,186.64,277.16,319.16
-Montenegro,,,,,,,,,,,,,,,,,,,,,2.57,2.57,22.2
-Netherlands,13.0,21.0,26.0,46.0,50.0,51.0,53.0,54.0,59.0,69.0,90.0,149.0,287.0,650.0,1007.0,1526.26,2135.02,2910.89,4608.0,7226.0,11108.43,14910.69,18848.69
-North Macedonia,,,,,,,,,,,,2.0,4.0,7.0,15.0,17.0,16.7,16.7,16.7,16.71,84.93,84.93,84.93
-Norway,6.0,6.0,6.0,7.0,7.0,7.0,8.0,8.0,8.3,8.7,9.1,9.5,10.0,11.0,13.0,15.0,26.7,44.9,53.11,102.53,141.53,186.53,302.53
-Poland,,,,,,,,,,,,1.11,1.3,2.39,27.15,107.78,187.25,287.09,561.98,1539.26,3954.96,7415.52,11166.52
-Portugal,1.0,1.0,1.0,2.0,2.0,2.0,3.0,24.0,59.0,115.0,134.0,169.6,235.6,293.6,412.6,441.75,493.05,539.42,617.85,832.74,1010.07,1474.78,2364.78
-Romania,,,,,,,,,0.1,0.1,0.1,1.0,41.0,761.0,1293.0,1326.0,1372.0,1374.13,1385.82,1397.71,1382.54,1393.92,1413.92
-Serbia,,,,,,0.1,0.2,0.4,0.9,1.2,1.3,1.5,3.1,4.7,6.0,9.0,11.0,10.0,11.0,11.0,11.5,11.94,11.94
-Slovakia,,,,,,,,,,,19.0,496.0,513.0,533.0,533.0,533.0,533.0,528.0,472.0,590.0,535.0,537.0,537.0
-Slovenia,1.0,1.0,,,,0.05,0.19,0.59,1.0,4.0,12.0,57.0,142.0,187.0,223.0,238.0,233.0,246.8,246.8,277.88,369.78,461.16,632.16
-Spain,1.0,3.0,6.0,10.0,19.0,37.0,113.0,476.0,3365.0,3403.0,3851.0,4260.0,4545.0,4665.0,4672.0,4677.0,4687.0,4696.0,4730.7,8772.02,10100.42,13678.4,18176.73
-Sweden,3.0,3.0,3.0,4.0,4.0,4.0,5.0,6.0,8.0,9.0,11.0,12.0,24.0,43.0,60.0,104.0,153.0,231.0,411.0,698.0,1090.0,1587.0,2587.0
-Switzerland,16.0,18.0,20.0,22.0,24.0,28.0,30.0,37.0,49.0,79.0,125.0,223.0,437.0,756.0,1061.0,1394.0,1664.0,1906.0,2173.0,2498.0,2973.0,3655.0,4339.92
-UK,2.0,3.0,4.0,6.0,8.0,11.0,14.0,18.0,23.0,27.0,95.0,1000.0,1753.0,2937.0,5528.0,9601.0,11914.0,12760.0,13059.0,13345.0,13579.0,13965.0,14660.0

doc/configtables/enable.csv

@@ -4,7 +4,6 @@ prepare_links_p_nom,bool,"{true, false}","Switch to retrieve current HVDC projec
 retrieve_databundle,bool,"{true, false}","Switch to retrieve databundle from zenodo via the rule :mod:`retrieve_databundle` or whether to keep a custom databundle located in the corresponding folder."
 retrieve_cost_data,bool,"{true, false}","Switch to retrieve technology cost data from `technology-data repository <https://github.com/PyPSA/technology-data>`_."
 build_cutout,bool,"{true, false}","Switch to enable the building of cutouts via the rule :mod:`build_cutout`."
-retrieve_irena,bool,"{true, false}",Switch to enable the retrieval of ``existing_capacities`` from IRENASTAT with :mod:`retrieve_irena`.
 retrieve_cutout,bool,"{true, false}","Switch to enable the retrieval of cutouts from zenodo with :mod:`retrieve_cutout`."
 custom_busmap,bool,"{true, false}","Switch to enable the use of custom busmaps in rule :mod:`cluster_network`. If activated the rule looks for provided busmaps at ``data/custom_busmap_elec_s{simpl}_{clusters}.csv`` which should have the same format as ``resources/busmap_elec_s{simpl}_{clusters}.csv``, i.e. the index should contain the buses of ``networks/elec_s{simpl}.nc``."
 drop_leap_day,bool,"{true, false}","Switch to drop February 29 from all time-dependent data in leap years"

doc/configtables/solving.csv

@@ -20,7 +20,7 @@ constraints ,,,
 -- BAU,bool,"{'true','false'}",Add a per-``carrier`` minimal overall capacity; i.e. at least ``40GW`` of ``OCGT`` in Europe; configured in ``electricity: BAU_mincapacities``
 -- SAFE,bool,"{'true','false'}",Add a capacity reserve margin of a certain fraction above the peak demand to which renewable generators and storage do *not* contribute. Ignores network.
 solver,,,
--- name,--,"One of {'gurobi', 'cplex', 'cbc', 'glpk', 'ipopt'}; potentially more possible",Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow.
+-- name,--,"One of {'gurobi', 'cplex', 'highs', 'cbc', 'glpk'}; potentially more possible",Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow.
 -- options,--,Key listed under ``solver_options``.,Link to specific parameter settings.
 solver_options,,dict,Dictionaries with solver-specific parameter settings.
 mem,MB,int,Estimated maximum memory requirement for solving networks.

doc/index.rst

@@ -135,7 +135,7 @@ as part of the `Stromnetze Research Initiative
 Workflow
 ========
 
-.. image:: ../graphics/workflow.png
+.. image:: img/workflow.png
     :class: full-width
     :align: center
 

doc/installation.rst

@@ -62,7 +62,7 @@ PyPSA is known to work with the free software
 - `HiGHS <https://highs.dev/>`__
 - `Cbc <https://projects.coin-or.org/Cbc#DownloadandInstall>`__
 - `GLPK <https://www.gnu.org/software/glpk/>`__ (`WinGLKP <http://winglpk.sourceforge.net/>`__)
-- `Ipopt <https://coin-or.github.io/Ipopt/INSTALL.html>`__
+- `SCIP <https://scipopt.github.io/PySCIPOpt/docs/html/index.html>`__
 
 and the non-free, commercial software (for some of which free academic licenses are available)
 
@@ -80,7 +80,7 @@ Nevertheless, you can still use open-source solvers for smaller problems.
 
 .. note::
     The rules :mod:`cluster_network` and :mod:`simplify_network` solve a mixed-integer quadratic optimisation problem for clustering.
-    The open-source solvers HiGHS, Cbc and GlPK cannot handle this. A fallback to SCIP is implemented in this case.
+    The open-source solvers HiGHS, Cbc and GlPK cannot handle this. A fallback to SCIP is implemented in this case, which is included in the standard environment specifications.
     For an open-source solver setup install in your ``conda`` environment on OSX/Linux. To install the default solver Gurobi, run
 
     .. code:: bash

doc/preparation.rst

@@ -21,8 +21,7 @@ Having downloaded the necessary data,
 With these and the externally extracted ENTSO-E online map topology
 (``data/entsoegridkit``), it can build a base PyPSA network with the following rules:
 
-- :mod:`base_network` builds and stores the base network with all buses, HVAC lines and HVDC links, while
-- :mod:`build_bus_regions` determines `Voronoi cells <https://en.wikipedia.org/wiki/Voronoi_diagram>`__ for all substations.
+- :mod:`base_network` builds and stores the base network with all buses, HVAC lines and HVDC links, and determines `Voronoi cells <https://en.wikipedia.org/wiki/Voronoi_diagram>`__ for all substations.
 
 Then the process continues by calculating conventional power plant capacities, potentials, and per-unit availability time series for variable renewable energy carriers and hydro power plants with the following rules:
 
@@ -34,13 +33,6 @@ Then the process continues by calculating conventional power plant capacities, p
 The central rule :mod:`add_electricity` then ties all the different data inputs
 together into a detailed PyPSA network stored in ``networks/elec.nc``.
 
-.. _busregions:
-
-Rule ``build_bus_regions``
-=============================
-
-.. automodule:: build_bus_regions
-
 .. _cutout:
 
 Rule ``build_cutout``

doc/release_notes.rst

@@ -194,6 +194,10 @@ Upcoming Release
 
 * Bugfix: allow modelling sector-coupled landlocked regions. (Fixed handling of offshore wind.)
 
+* Bugfix: approximation of hydro power generation if Portugal or Spain are not included works now.
+
+* Bugfix: copy_timeslice does not copy anymore, if country not present in load data.
+
 * Adapt the disabling of transmission expansion in myopic foresight optimisations when limit is already reached to also handle cost limits.
 
 * Fix duplicated years and grouping years reference in `add_land_use_constraint_m`.
@@ -206,8 +210,15 @@ Upcoming Release
 
 * Fix custom busmap read in `cluster_network`.
 
+* Data on existing renewable capacities is now consistently taken from powerplantmatching (instead of being retrieved separately); the dataset has also been updated to include 2023 values.
+
+* Added shapes to .nc file for different stages of the network object in `base_network`, `simplify_network`, and `cluster_network`; the `build_bus_regions` rule is now integrated into the `base_network` rule.
+
+* Fix p_nom_min of renewables generators for myopic approach and add check of existing capacities in `add_land_use_constraint_m`.
+
 * Add documentation section for how to contribute documentation
 
+
 PyPSA-Eur 0.10.0 (19th February 2024)
 =====================================
 

doc/retrieve.rst

@@ -92,11 +92,6 @@ This rule downloads techno-economic assumptions from the `technology-data reposi
 
 - ``resources/costs.csv``
 
-Rule ``retrieve_irena``
-================================
-
-.. automodule:: retrieve_irena
-
 Rule ``retrieve_ship_raster``
 ================================
 

doc/tutorial.rst

@@ -132,89 +132,76 @@ This triggers a workflow of multiple preceding jobs that depend on each rule's i
         graph[bgcolor=white, margin=0];
         node[shape=box, style=rounded, fontname=sans,                 fontsize=10, penwidth=2];
         edge[penwidth=2, color=grey];
-            0[label = "solve_network", color = "0.39 0.6 0.85", style="rounded"];
-            1[label = "prepare_network\nll: copt\nopts: Co2L-24H", color = "0.29 0.6 0.85", style="rounded"];
-            2[label = "add_extra_components", color = "0.28 0.6 0.85", style="rounded"];
-            3[label = "cluster_network\nclusters: 6", color = "0.19 0.6 0.85", style="rounded"];
-            4[label = "simplify_network\nsimpl: ", color = "0.01 0.6 0.85", style="rounded"];
-            5[label = "add_electricity", color = "0.49 0.6 0.85", style="rounded"];
-            6[label = "build_renewable_profiles\ntechnology: solar", color = "0.21 0.6 0.85", style="rounded"];
-            7[label = "base_network", color = "0.27 0.6 0.85", style="rounded"];
-            8[label = "build_shapes", color = "0.26 0.6 0.85", style="rounded"];
-            9[label = "retrieve_databundle", color = "0.59 0.6 0.85", style="rounded"];
-            11[label = "build_bus_regions", color = "0.13 0.6 0.85", style="rounded"];
-            12[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.36 0.6 0.85", style="rounded,dashed"];
-            13[label = "build_renewable_profiles\ntechnology: onwind", color = "0.21 0.6 0.85", style="rounded"];
-            14[label = "build_renewable_profiles\ntechnology: offwind-ac", color = "0.21 0.6 0.85", style="rounded"];
-            15[label = "build_ship_raster", color = "0.00 0.6 0.85", style="rounded"];
-            16[label = "retrieve_ship_raster", color = "0.51 0.6 0.85", style="rounded,dashed"];
-            17[label = "build_renewable_profiles\ntechnology: offwind-dc", color = "0.21 0.6 0.85", style="rounded"];
-            18[label = "build_line_rating", color = "0.05 0.6 0.85", style="rounded"];
-            19[label = "retrieve_cost_data\nyear: 2030", color = "0.15 0.6 0.85", style="rounded"];
-            20[label = "build_powerplants", color = "0.54 0.6 0.85", style="rounded"];
-            21[label = "build_electricity_demand", color = "0.52 0.6 0.85", style="rounded"];
-            22[label = "retrieve_electricity_demand", color = "0.22 0.6 0.85", style="rounded"];
-            23[label = "copy_config", color = "0.44 0.6 0.85", style="rounded"];
+            0[label = "solve_network", color = "0.38 0.6 0.85", style="rounded"];
+            1[label = "prepare_network\nll: copt\nopts: Co2L-24H", color = "0.53 0.6 0.85", style="rounded"];
+            2[label = "add_extra_components", color = "0.01 0.6 0.85", style="rounded"];
+            3[label = "cluster_network\nclusters: 6", color = "0.03 0.6 0.85", style="rounded"];
+            4[label = "simplify_network\nsimpl: ", color = "0.42 0.6 0.85", style="rounded"];
+            5[label = "add_electricity", color = "0.10 0.6 0.85", style="rounded"];
+            6[label = "build_renewable_profiles\ntechnology: solar", color = "0.50 0.6 0.85", style="rounded"];
+            7[label = "base_network", color = "0.22 0.6 0.85", style="rounded"];
+            8[label = "build_shapes", color = "0.44 0.6 0.85", style="rounded"];
+            9[label = "retrieve_databundle", color = "0.29 0.6 0.85", style="rounded"];
+            10[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.49 0.6 0.85", style="rounded"];
+            11[label = "build_renewable_profiles\ntechnology: onwind", color = "0.50 0.6 0.85", style="rounded"];
+            12[label = "build_renewable_profiles\ntechnology: offwind-ac", color = "0.50 0.6 0.85", style="rounded"];
+            13[label = "build_ship_raster", color = "0.19 0.6 0.85", style="rounded"];
+            14[label = "retrieve_ship_raster", color = "0.35 0.6 0.85", style="rounded"];
+            15[label = "build_renewable_profiles\ntechnology: offwind-dc", color = "0.50 0.6 0.85", style="rounded"];
+            16[label = "build_line_rating", color = "0.60 0.6 0.85", style="rounded"];
+            17[label = "retrieve_cost_data\nyear: 2030", color = "0.59 0.6 0.85", style="rounded"];
+            18[label = "build_powerplants", color = "0.06 0.6 0.85", style="rounded"];
+            19[label = "build_electricity_demand", color = "0.13 0.6 0.85", style="rounded"];
+            20[label = "retrieve_electricity_demand", color = "0.49 0.6 0.85", style="rounded"];
+            21[label = "retrieve_synthetic_electricity_demand", color = "0.41 0.6 0.85", style="rounded"];
             1 -> 0
-            23 -> 0
             2 -> 1
-            19 -> 1
+            17 -> 1
             3 -> 2
-            19 -> 2
+            17 -> 2
             4 -> 3
-            19 -> 3
+            17 -> 3
             5 -> 4
-            19 -> 4
-            11 -> 4
+            17 -> 4
+            7 -> 4
             6 -> 5
-            13 -> 5
-            14 -> 5
-            17 -> 5
+            11 -> 5
+            12 -> 5
+            15 -> 5
             7 -> 5
+            16 -> 5
+            17 -> 5
             18 -> 5
             19 -> 5
-            11 -> 5
-            20 -> 5
-            9 -> 5
-            21 -> 5
             8 -> 5
             7 -> 6
             9 -> 6
-            10 -> 6
             8 -> 6
-            11 -> 6
-            12 -> 6
+            10 -> 6
             8 -> 7
             9 -> 8
-            8 -> 11
             7 -> 11
-            7 -> 13
-            9 -> 13
+            9 -> 11
+            8 -> 11
+            10 -> 11
+            7 -> 12
+            9 -> 12
+            13 -> 12
+            8 -> 12
+            10 -> 12
+            14 -> 13
             10 -> 13
-            8 -> 13
-            11 -> 13
-            12 -> 13
-            7 -> 14
-            9 -> 14
-            10 -> 14
-            15 -> 14
-            8 -> 14
-            11 -> 14
-            12 -> 14
-            16 -> 15
-            12 -> 15
-            7 -> 17
-            9 -> 17
-            10 -> 17
-            15 -> 17
-            8 -> 17
-            11 -> 17
-            12 -> 17
+            7 -> 15
+            9 -> 15
+            13 -> 15
+            8 -> 15
+            10 -> 15
+            7 -> 16
+            10 -> 16
             7 -> 18
-            12 -> 18
-            7 -> 20
-            22 -> 21
-    }
+            20 -> 19
+            21 -> 19
+    }   
 
 |
 
@@ -224,27 +211,28 @@ In the terminal, this will show up as a list of jobs to be run:
 
     Building DAG of jobs...
     Job stats:
-    job                            count
-    ---------------------------  -------
-    add_electricity                    1
-    add_extra_components               1
-    base_network                       1
-    build_bus_regions                  1
-    build_electricity_demand           1
-    build_line_rating                  1
-    build_powerplants                  1
-    build_renewable_profiles           4
-    build_shapes                       1
-    build_ship_raster                  1
-    cluster_network                    1
-    copy_config                        1
-    prepare_network                    1
-    retrieve_cost_data                 1
-    retrieve_databundle                1
-    retrieve_electricity_demand        1
-    simplify_network                   1
-    solve_network                      1
-    total                             22
+    job                                      count
+    -------------------------------------  -------
+    add_electricity                              1
+    add_extra_components                         1
+    base_network                                 1
+    build_electricity_demand                     1
+    build_line_rating                            1
+    build_powerplants                            1
+    build_renewable_profiles                     4
+    build_shapes                                 1
+    build_ship_raster                            1
+    cluster_network                              1
+    prepare_network                              1
+    retrieve_cost_data                           1
+    retrieve_cutout                              1
+    retrieve_databundle                          1
+    retrieve_electricity_demand                  1
+    retrieve_ship_raster                         1
+    retrieve_synthetic_electricity_demand        1
+    simplify_network                             1
+    solve_network                                1
+    total                                       22
 
 
 ``snakemake`` then runs these jobs in the correct order.

envs/environment.fixed.yaml

@@ -7,440 +7,466 @@ channels:
 - bioconda
 - http://conda.anaconda.org/gurobi
 - conda-forge
-- defaults
 dependencies:
-- _libgcc_mutex=0.1
-- _openmp_mutex=4.5
-- affine=2.4.0
-- alsa-lib=1.2.10
-- ampl-mp=3.1.0
-- amply=0.1.6
-- appdirs=1.4.4
-- asttokens=2.4.1
-- atk-1.0=2.38.0
-- atlite=0.2.12
-- attr=2.5.1
-- attrs=23.2.0
-- aws-c-auth=0.7.15
-- aws-c-cal=0.6.9
-- aws-c-common=0.9.12
-- aws-c-compression=0.2.17
-- aws-c-event-stream=0.4.1
-- aws-c-http=0.8.0
-- aws-c-io=0.14.3
-- aws-c-mqtt=0.10.1
-- aws-c-s3=0.5.0
-- aws-c-sdkutils=0.1.14
-- aws-checksums=0.1.17
-- aws-crt-cpp=0.26.1
-- aws-sdk-cpp=1.11.242
-- azure-core-cpp=1.10.3
-- azure-storage-blobs-cpp=12.10.0
-- azure-storage-common-cpp=12.5.0
-- beautifulsoup4=4.12.3
-- blosc=1.21.5
-- bokeh=3.3.4
-- bottleneck=1.3.7
-- branca=0.7.1
-- brotli=1.1.0
-- brotli-bin=1.1.0
-- brotli-python=1.1.0
-- bzip2=1.0.8
-- c-ares=1.26.0
-- c-blosc2=2.13.2
-- ca-certificates=2024.2.2
-- cairo=1.18.0
-- cartopy=0.22.0
-- cdsapi=0.6.1
-- certifi=2024.2.2
-- cffi=1.16.0
-- cfgv=3.3.1
-- cfitsio=4.3.1
-- cftime=1.6.3
-- charset-normalizer=3.3.2
-- click=8.1.7
-- click-plugins=1.1.1
-- cligj=0.7.2
-- cloudpickle=3.0.0
-- coin-or-cbc=2.10.10
-- coin-or-cgl=0.60.7
-- coin-or-clp=1.17.8
-- coin-or-osi=0.108.8
-- coin-or-utils=2.11.9
-- coincbc=2.10.10
-- colorama=0.4.6
-- configargparse=1.7
-- connection_pool=0.0.3
-- contourpy=1.2.0
-- country_converter=1.2
-- cppad=20240000.2
-- cycler=0.12.1
-- cytoolz=0.12.3
-- dask=2024.2.0
-- dask-core=2024.2.0
-- datrie=0.8.2
-- dbus=1.13.6
-- decorator=5.1.1
-- deprecation=2.1.0
-- descartes=1.1.0
-- distlib=0.3.8
-- distributed=2024.2.0
-- distro=1.9.0
-- docutils=0.20.1
-- dpath=2.1.6
-- entsoe-py=0.6.6
-- et_xmlfile=1.1.0
-- exceptiongroup=1.2.0
-- executing=2.0.1
-- expat=2.5.0
-- filelock=3.13.1
-- fiona=1.9.5
-- folium=0.15.1
-- font-ttf-dejavu-sans-mono=2.37
-- font-ttf-inconsolata=3.000
-- font-ttf-source-code-pro=2.038
-- font-ttf-ubuntu=0.83
-- fontconfig=2.14.2
-- fonts-conda-ecosystem=1
-- fonts-conda-forge=1
-- fonttools=4.49.0
-- freetype=2.12.1
-- freexl=2.0.0
-- fribidi=1.0.10
-- fsspec=2024.2.0
-- gdal=3.8.4
-- gdk-pixbuf=2.42.10
-- geographiclib=1.52
-- geojson-rewind=1.1.0
-- geopandas=0.14.3
-- geopandas-base=0.14.3
-- geopy=2.4.1
-- geos=3.12.1
-- geotiff=1.7.1
-- gettext=0.21.1
-- gflags=2.2.2
-- giflib=5.2.1
-- gitdb=4.0.11
-- gitpython=3.1.42
-- glib=2.78.4
-- glib-tools=2.78.4
-- glog=0.6.0
-- glpk=5.0
-- gmp=6.3.0
-- graphite2=1.3.13
-- graphviz=9.0.0
-- gst-plugins-base=1.22.9
-- gstreamer=1.22.9
-- gtk2=2.24.33
-- gts=0.7.6
-- harfbuzz=8.3.0
-- hdf4=4.2.15
-- hdf5=1.14.3
-- humanfriendly=10.0
-- icu=73.2
-- identify=2.5.35
-- idna=3.6
-- importlib-metadata=7.0.1
-- importlib_metadata=7.0.1
-- importlib_resources=6.1.1
-- iniconfig=2.0.0
-- ipopt=3.14.14
-- ipython=8.21.0
-- jedi=0.19.1
-- jinja2=3.1.3
-- joblib=1.3.2
-- json-c=0.17
-- jsonschema=4.21.1
-- jsonschema-specifications=2023.12.1
-- jupyter_core=5.7.1
-- kealib=1.5.3
-- keyutils=1.6.1
-- kiwisolver=1.4.5
-- krb5=1.21.2
-- lame=3.100
-- lcms2=2.16
-- ld_impl_linux-64=2.40
-- lerc=4.0.0
-- libabseil=20230802.1
-- libaec=1.1.2
-- libarchive=3.7.2
-- libarrow=15.0.0
-- libarrow-acero=15.0.0
-- libarrow-dataset=15.0.0
-- libarrow-flight=15.0.0
-- libarrow-flight-sql=15.0.0
-- libarrow-gandiva=15.0.0
-- libarrow-substrait=15.0.0
-- libblas=3.9.0
-- libboost-headers=1.84.0
-- libbrotlicommon=1.1.0
-- libbrotlidec=1.1.0
-- libbrotlienc=1.1.0
-- libcap=2.69
-- libcblas=3.9.0
-- libclang=15.0.7
-- libclang13=15.0.7
-- libcrc32c=1.1.2
-- libcups=2.3.3
-- libcurl=8.5.0
-- libdeflate=1.19
-- libedit=3.1.20191231
-- libev=4.33
-- libevent=2.1.12
-- libexpat=2.5.0
-- libffi=3.4.2
-- libflac=1.4.3
-- libgcc-ng=13.2.0
-- libgcrypt=1.10.3
-- libgd=2.3.3
-- libgdal=3.8.4
-- libgfortran-ng=13.2.0
-- libgfortran5=13.2.0
-- libglib=2.78.4
-- libgomp=13.2.0
-- libgoogle-cloud=2.12.0
-- libgpg-error=1.47
-- libgrpc=1.60.1
-- libhwloc=2.9.3
-- libiconv=1.17
-- libjpeg-turbo=3.0.0
-- libkml=1.3.0
-- liblapack=3.9.0
-- liblapacke=3.9.0
-- libllvm15=15.0.7
-- libnetcdf=4.9.2
-- libnghttp2=1.58.0
-- libnl=3.9.0
-- libnsl=2.0.1
-- libnuma=2.0.16
-- libogg=1.3.4
-- libopenblas=0.3.26
-- libopus=1.3.1
-- libparquet=15.0.0
-- libpng=1.6.42
-- libpq=16.2
-- libprotobuf=4.25.1
-- libre2-11=2023.06.02
-- librsvg=2.56.3
-- librttopo=1.1.0
-- libscotch=7.0.4
-- libsndfile=1.2.2
-- libspatialindex=1.9.3
-- libspatialite=5.1.0
-- libspral=2023.09.07
-- libsqlite=3.45.1
-- libssh2=1.11.0
-- libstdcxx-ng=13.2.0
-- libsystemd0=255
-- libthrift=0.19.0
-- libtiff=4.6.0
-- libutf8proc=2.8.0
-- libuuid=2.38.1
-- libvorbis=1.3.7
-- libwebp=1.3.2
-- libwebp-base=1.3.2
-- libxcb=1.15
-- libxcrypt=4.4.36
-- libxkbcommon=1.6.0
-- libxml2=2.12.5
-- libxslt=1.1.39
-- libzip=1.10.1
-- libzlib=1.2.13
-- linopy=0.3.4
-- locket=1.0.0
-- lxml=5.1.0
-- lz4=4.3.3
-- lz4-c=1.9.4
-- lzo=2.10
-- mapclassify=2.6.1
-- markupsafe=2.1.5
-- matplotlib=3.8.3
-- matplotlib-base=3.8.3
-- matplotlib-inline=0.1.6
-- memory_profiler=0.61.0
-- metis=5.1.0
-- minizip=4.0.4
-- mpg123=1.32.4
-- msgpack-python=1.0.7
-- mumps-include=5.6.2
-- mumps-seq=5.6.2
-- munkres=1.1.4
-- mysql-common=8.0.33
-- mysql-libs=8.0.33
-- nbformat=5.9.2
-- ncurses=6.4
-- netcdf4=1.6.5
-- networkx=3.2.1
-- nodeenv=1.8.0
-- nomkl=1.0
-- nspr=4.35
-- nss=3.98
-- numexpr=2.9.0
-- numpy=1.26.4
-- openjdk=21.0.2
-- openjpeg=2.5.0
-- openpyxl=3.1.2
-- openssl=3.2.1
-- orc=1.9.2
-- packaging=23.2
-- pandas=2.2.0
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+- platformdirs=4.2.1=pyhd8ed1ab_0
+- pluggy=1.5.0=pyhd8ed1ab_0
+- ply=3.11=pyhd8ed1ab_2
+- poppler=24.04.0=hb6cd0d7_0
+- poppler-data=0.4.12=hd8ed1ab_0
+- postgresql=16.2=h82ecc9d_1
+- powerplantmatching=0.5.14=pyhd8ed1ab_0
+- pre-commit=3.7.0=pyha770c72_0
+- progressbar2=4.4.2=pyhd8ed1ab_0
+- proj=9.4.0=h1d62c97_1
+- prompt-toolkit=3.0.42=pyha770c72_0
+- psutil=5.9.8=py311h459d7ec_0
+- pthread-stubs=0.4=h36c2ea0_1001
+- ptyprocess=0.7.0=pyhd3deb0d_0
+- pulp=2.8.0=py311h38be061_0
+- pulseaudio-client=17.0=hb77b528_0
+- pure_eval=0.2.2=pyhd8ed1ab_0
+- py-cpuinfo=9.0.0=pyhd8ed1ab_0
+- pyarrow=15.0.2=py311hd5e4297_6_cpu
+- pyarrow-hotfix=0.6=pyhd8ed1ab_0
+- pycountry=22.3.5=pyhd8ed1ab_0
+- pycparser=2.22=pyhd8ed1ab_0
+- pygments=2.17.2=pyhd8ed1ab_0
+- pyomo=6.6.1=py311hb755f60_0
+- pyparsing=3.1.2=pyhd8ed1ab_0
+- pyproj=3.6.1=py311hb3a3e68_6
+- pypsa=0.27.1=pyhd8ed1ab_0
+- pyqt=5.15.9=py311hf0fb5b6_5
+- pyqt5-sip=12.12.2=py311hb755f60_5
+- pyscipopt=5.0.1=py311hb755f60_0
+- pyshp=2.3.1=pyhd8ed1ab_0
+- pysocks=1.7.1=pyha2e5f31_6
+- pytables=3.9.2=py311h3e8b7c9_2
+- pytest=8.2.0=pyhd8ed1ab_0
+- python=3.11.9=hb806964_0_cpython
+- python-dateutil=2.9.0=pyhd8ed1ab_0
+- python-fastjsonschema=2.19.1=pyhd8ed1ab_0
+- python-tzdata=2024.1=pyhd8ed1ab_0
+- python-utils=3.8.2=pyhd8ed1ab_0
+- python_abi=3.11=4_cp311
+- pytz=2024.1=pyhd8ed1ab_0
+- pyxlsb=1.0.10=pyhd8ed1ab_0
+- pyyaml=6.0.1=py311h459d7ec_1
+- qt-main=5.15.8=hc9dc06e_21
+- rasterio=1.3.10=py311h375a7ea_0
+- rdma-core=51.0=hd3aeb46_0
+- re2=2023.09.01=h7f4b329_2
+- readline=8.2=h8228510_1
+- referencing=0.35.1=pyhd8ed1ab_0
+- requests=2.31.0=pyhd8ed1ab_0
+- reretry=0.11.8=pyhd8ed1ab_0
+- rioxarray=0.15.5=pyhd8ed1ab_0
+- rpds-py=0.18.0=py311h46250e7_0
+- rtree=1.2.0=py311h3bb2b0f_0
+- s2n=1.4.12=h06160fa_0
+- scikit-learn=1.4.2=py311hc009520_0
+- scip=9.0.0=hded5f35_4
+- scipy=1.13.0=py311h64a7726_0
+- scotch=7.0.4=h23d43cc_1
+- seaborn=0.13.2=hd8ed1ab_2
+- seaborn-base=0.13.2=pyhd8ed1ab_2
+- setuptools=69.5.1=pyhd8ed1ab_0
+- setuptools-scm=8.0.4=pyhd8ed1ab_1
+- setuptools_scm=8.0.4=hd8ed1ab_1
+- shapely=2.0.4=py311h2032efe_0
+- sip=6.7.12=py311hb755f60_0
+- six=1.16.0=pyh6c4a22f_0
+- smart_open=7.0.4=pyhd8ed1ab_0
+- smmap=5.0.0=pyhd8ed1ab_0
+- snakemake-interface-common=1.17.2=pyhdfd78af_0
+- snakemake-interface-executor-plugins=9.1.1=pyhdfd78af_0
+- snakemake-interface-report-plugins=1.0.0=pyhdfd78af_0
+- snakemake-interface-storage-plugins=3.2.2=pyhdfd78af_0
+- snakemake-minimal=8.11.1=pyhdfd78af_0
+- snappy=1.2.0=hdb0a2a9_1
+- snuggs=1.4.7=py_0
+- sortedcontainers=2.4.0=pyhd8ed1ab_0
+- soupsieve=2.5=pyhd8ed1ab_1
+- spdlog=1.13.0=hd2e6256_0
+- sqlite=3.45.3=h2c6b66d_0
+- stack_data=0.6.2=pyhd8ed1ab_0
+- statsmodels=0.14.1=py311h1f0f07a_0
+- stopit=1.1.2=py_0
+- tabula-py=2.7.0=py311h38be061_1
+- tabulate=0.9.0=pyhd8ed1ab_1
+- tbb=2021.11.0=h00ab1b0_1
+- tblib=3.0.0=pyhd8ed1ab_0
+- threadpoolctl=3.5.0=pyhc1e730c_0
+- throttler=1.2.2=pyhd8ed1ab_0
+- tiledb=2.22.0=h27f064a_3
+- tk=8.6.13=noxft_h4845f30_101
+- toml=0.10.2=pyhd8ed1ab_0
+- tomli=2.0.1=pyhd8ed1ab_0
+- toolz=0.12.1=pyhd8ed1ab_0
+- toposort=1.10=pyhd8ed1ab_0
+- tornado=6.4=py311h459d7ec_0
+- tqdm=4.66.2=pyhd8ed1ab_0
+- traitlets=5.14.3=pyhd8ed1ab_0
+- typing-extensions=4.11.0=hd8ed1ab_0
+- typing_extensions=4.11.0=pyha770c72_0
+- tzcode=2024a=h3f72095_0
+- tzdata=2024a=h0c530f3_0
+- ucx=1.15.0=ha691c75_8
+- ukkonen=1.0.1=py311h9547e67_4
+- unidecode=1.3.8=pyhd8ed1ab_0
+- unixodbc=2.3.12=h661eb56_0
+- uriparser=0.9.7=h59595ed_1
+- urllib3=2.2.1=pyhd8ed1ab_0
+- validators=0.28.1=pyhd8ed1ab_0
+- virtualenv=20.26.1=pyhd8ed1ab_0
+- wcwidth=0.2.13=pyhd8ed1ab_0
+- wheel=0.43.0=pyhd8ed1ab_1
+- wrapt=1.16.0=py311h459d7ec_0
+- xarray=2024.3.0=pyhd8ed1ab_0
+- xcb-util=0.4.0=hd590300_1
+- xcb-util-image=0.4.0=h8ee46fc_1
+- xcb-util-keysyms=0.4.0=h8ee46fc_1
+- xcb-util-renderutil=0.3.9=hd590300_1
+- xcb-util-wm=0.4.1=h8ee46fc_1
+- xerces-c=3.2.5=hac6953d_0
+- xkeyboard-config=2.41=hd590300_0
+- xlrd=2.0.1=pyhd8ed1ab_3
+- xorg-fixesproto=5.0=h7f98852_1002
+- xorg-inputproto=2.3.2=h7f98852_1002
+- xorg-kbproto=1.0.7=h7f98852_1002
+- xorg-libice=1.1.1=hd590300_0
+- xorg-libsm=1.2.4=h7391055_0
+- xorg-libx11=1.8.9=h8ee46fc_0
+- xorg-libxau=1.0.11=hd590300_0
+- xorg-libxdmcp=1.1.3=h7f98852_0
+- xorg-libxext=1.3.4=h0b41bf4_2
+- xorg-libxfixes=5.0.3=h7f98852_1004
+- xorg-libxi=1.7.10=h7f98852_0
+- xorg-libxrender=0.9.11=hd590300_0
+- xorg-libxt=1.3.0=hd590300_1
+- xorg-libxtst=1.2.3=h7f98852_1002
+- xorg-recordproto=1.14.2=h7f98852_1002
+- xorg-renderproto=0.11.1=h7f98852_1002
+- xorg-xextproto=7.3.0=h0b41bf4_1003
+- xorg-xf86vidmodeproto=2.3.1=h7f98852_1002
+- xorg-xproto=7.0.31=h7f98852_1007
+- xyzservices=2024.4.0=pyhd8ed1ab_0
+- xz=5.2.6=h166bdaf_0
+- yaml=0.2.5=h7f98852_2
+- yte=1.5.4=pyha770c72_0
+- zict=3.0.0=pyhd8ed1ab_0
+- zipp=3.17.0=pyhd8ed1ab_0
+- zlib=1.2.13=hd590300_5
+- zlib-ng=2.0.7=h0b41bf4_0
+- zstd=1.5.5=hfc55251_0
 - pip:
   - highspy==1.5.3
+  - oauthlib==3.2.2
+  - requests-oauthlib==1.3.1
+  - snakemake-executor-plugin-cluster-generic==1.0.9
+  - snakemake-executor-plugin-slurm==0.4.5
+  - snakemake-executor-plugin-slurm-jobstep==0.2.1
+  - snakemake-storage-plugin-http==0.2.3
   - tsam==2.3.1

envs/environment.yaml

@@ -20,12 +20,12 @@ dependencies:
 - openpyxl!=3.1.1
 - pycountry
 - seaborn
-- snakemake-minimal>=8.5
+- snakemake-minimal>=8.11
 - memory_profiler
 - yaml
 - pytables
 - lxml
-- powerplantmatching>=0.5.5,!=0.5.9
+- powerplantmatching>=0.5.13
 - numpy
 - pandas>=2.1
 - geopandas>=0.11.0

rules/build_electricity.smk

@@ -86,7 +86,9 @@ rule base_network:
         offshore_shapes=resources("offshore_shapes.geojson"),
         europe_shape=resources("europe_shape.geojson"),
     output:
-        resources("networks/base.nc"),
+        base_network=resources("networks/base.nc"),
+        regions_onshore=resources("regions_onshore.geojson"),
+        regions_offshore=resources("regions_offshore.geojson"),
     log:
         logs("base_network.log"),
     benchmark:
@@ -127,27 +129,6 @@ rule build_shapes:
         "../scripts/build_shapes.py"
 
 
-rule build_bus_regions:
-    params:
-        countries=config_provider("countries"),
-    input:
-        country_shapes=resources("country_shapes.geojson"),
-        offshore_shapes=resources("offshore_shapes.geojson"),
-        base_network=resources("networks/base.nc"),
-    output:
-        regions_onshore=resources("regions_onshore.geojson"),
-        regions_offshore=resources("regions_offshore.geojson"),
-    log:
-        logs("build_bus_regions.log"),
-    threads: 1
-    resources:
-        mem_mb=1000,
-    conda:
-        "../envs/environment.yaml"
-    script:
-        "../scripts/build_bus_regions.py"
-
-
 if config["enable"].get("build_cutout", False):
 
     rule build_cutout:
@@ -412,7 +393,7 @@ rule add_electricity:
             else resources("networks/base.nc")
         ),
         tech_costs=lambda w: resources(
-            f"costs_{config_provider('costs', 'year')(w)}.csv"
+            f"costs_{config_provider('costs', 'year') (w)}.csv"
         ),
         regions=resources("regions_onshore.geojson"),
         powerplants=resources("powerplants.csv"),
@@ -457,7 +438,7 @@ rule simplify_network:
     input:
         network=resources("networks/elec.nc"),
         tech_costs=lambda w: resources(
-            f"costs_{config_provider('costs', 'year')(w)}.csv"
+            f"costs_{config_provider('costs', 'year') (w)}.csv"
         ),
         regions_onshore=resources("regions_onshore.geojson"),
         regions_offshore=resources("regions_offshore.geojson"),
@@ -466,7 +447,6 @@ rule simplify_network:
         regions_onshore=resources("regions_onshore_elec_s{simpl}.geojson"),
         regions_offshore=resources("regions_offshore_elec_s{simpl}.geojson"),
         busmap=resources("busmap_elec_s{simpl}.csv"),
-        connection_costs=resources("connection_costs_s{simpl}.csv"),
     log:
         logs("simplify_network/elec_s{simpl}.log"),
     benchmark:
@@ -506,7 +486,7 @@ rule cluster_network:
             else []
         ),
         tech_costs=lambda w: resources(
-            f"costs_{config_provider('costs', 'year')(w)}.csv"
+            f"costs_{config_provider('costs', 'year') (w)}.csv"
         ),
     output:
         network=resources("networks/elec_s{simpl}_{clusters}.nc"),
@@ -535,7 +515,7 @@ rule add_extra_components:
     input:
         network=resources("networks/elec_s{simpl}_{clusters}.nc"),
         tech_costs=lambda w: resources(
-            f"costs_{config_provider('costs', 'year')(w)}.csv"
+            f"costs_{config_provider('costs', 'year') (w)}.csv"
         ),
     output:
         resources("networks/elec_s{simpl}_{clusters}_ec.nc"),
@@ -570,7 +550,7 @@ rule prepare_network:
     input:
         resources("networks/elec_s{simpl}_{clusters}_ec.nc"),
         tech_costs=lambda w: resources(
-            f"costs_{config_provider('costs', 'year')(w)}.csv"
+            f"costs_{config_provider('costs', 'year') (w)}.csv"
         ),
         co2_price=lambda w: resources("co2_price.csv") if "Ept" in w.opts else [],
     output:

rules/retrieve.smk

@@ -55,24 +55,6 @@ if config["enable"]["retrieve"] and config["enable"].get("retrieve_databundle",
             "../scripts/retrieve_eurostat_data.py"
 
 
-if config["enable"].get("retrieve_irena"):
-
-    rule retrieve_irena:
-        output:
-            offwind="data/existing_infrastructure/offwind_capacity_IRENA.csv",
-            onwind="data/existing_infrastructure/onwind_capacity_IRENA.csv",
-            solar="data/existing_infrastructure/solar_capacity_IRENA.csv",
-        log:
-            "logs/retrieve_irena.log",
-        resources:
-            mem_mb=1000,
-        retries: 2
-        conda:
-            "../envs/retrieve.yaml"
-        script:
-            "../scripts/retrieve_irena.py"
-
-
 if config["enable"]["retrieve"] and config["enable"].get("retrieve_cutout", True):
 
     rule retrieve_cutout:

rules/solve_myopic.smk

@@ -26,9 +26,6 @@ rule add_existing_baseyear:
         existing_heating_distribution=resources(
             "existing_heating_distribution_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
         ),
-        existing_solar="data/existing_infrastructure/solar_capacity_IRENA.csv",
-        existing_onwind="data/existing_infrastructure/onwind_capacity_IRENA.csv",
-        existing_offwind="data/existing_infrastructure/offwind_capacity_IRENA.csv",
     output:
         RESULTS
         + "prenetworks-brownfield/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",

rules/solve_perfect.smk

@@ -25,9 +25,6 @@ rule add_existing_baseyear:
             "existing_heating_distribution_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
         ),
         existing_heating="data/existing_infrastructure/existing_heating_raw.csv",
-        existing_solar="data/existing_infrastructure/solar_capacity_IRENA.csv",
-        existing_onwind="data/existing_infrastructure/onwind_capacity_IRENA.csv",
-        existing_offwind="data/existing_infrastructure/offwind_capacity_IRENA.csv",
     output:
         RESULTS
         + "prenetworks-brownfield/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",

scripts/add_existing_baseyear.py

@@ -13,6 +13,7 @@ from types import SimpleNamespace
 import country_converter as coco
 import numpy as np
 import pandas as pd
+import powerplantmatching as pm
 import pypsa
 import xarray as xr
 from _helpers import (
@@ -60,14 +61,22 @@ def add_existing_renewables(df_agg, costs):
     Append existing renewables to the df_agg pd.DataFrame with the conventional
     power plants.
     """
-    carriers = {"solar": "solar", "onwind": "onwind", "offwind": "offwind-ac"}
+    tech_map = {"solar": "PV", "onwind": "Onshore", "offwind": "Offshore"}
 
-    for tech in ["solar", "onwind", "offwind"]:
-        carrier = carriers[tech]
+    countries = snakemake.config["countries"]
+    irena = pm.data.IRENASTAT().powerplant.convert_country_to_alpha2()
+    irena = irena.query("Country in @countries")
+    irena = irena.groupby(["Technology", "Country", "Year"]).Capacity.sum()
 
-        df = pd.read_csv(snakemake.input[f"existing_{tech}"], index_col=0).fillna(0.0)
+    irena = irena.unstack().reset_index()
+
+    for carrier, tech in tech_map.items():
+        df = (
+            irena[irena.Technology.str.contains(tech)]
+            .drop(columns=["Technology"])
+            .set_index("Country")
+        )
         df.columns = df.columns.astype(int)
-        df.index = cc.convert(df.index, to="iso2")
 
         # calculate yearly differences
         df.insert(loc=0, value=0.0, column="1999")
@@ -97,14 +106,16 @@ def add_existing_renewables(df_agg, costs):
 
         for year in nodal_df.columns:
             for node in nodal_df.index:
-                name = f"{node}-{tech}-{year}"
+                name = f"{node}-{carrier}-{year}"
                 capacity = nodal_df.loc[node, year]
                 if capacity > 0.0:
-                    df_agg.at[name, "Fueltype"] = tech
+                    df_agg.at[name, "Fueltype"] = carrier
                     df_agg.at[name, "Capacity"] = capacity
                     df_agg.at[name, "DateIn"] = year
-                    df_agg.at[name, "lifetime"] = costs.at[tech, "lifetime"]
-                    df_agg.at[name, "DateOut"] = year + costs.at[tech, "lifetime"] - 1
+                    df_agg.at[name, "lifetime"] = costs.at[carrier, "lifetime"]
+                    df_agg.at[name, "DateOut"] = (
+                        year + costs.at[carrier, "lifetime"] - 1
+                    )
                     df_agg.at[name, "cluster_bus"] = node
 
 
@@ -310,7 +321,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
                     n.madd(
                         "Generator",
                         new_capacity.index,
-                        suffix=" " + name_suffix,
+                        suffix=name_suffix,
                         bus=new_capacity.index,
                         carrier=generator,
                         p_nom=new_capacity,

scripts/base_network.py

@@ -5,10 +5,7 @@
 
 # coding: utf-8
 """
-Creates the network topology from a `ENTSO-E map extract.
-
-<https://github.com/PyPSA/GridKit/tree/master/entsoe>`_ (March 2022) as a PyPSA
-network.
+Creates the network topology from an `ENTSO-E map extract <https://github.com/PyPSA/GridKit/tree/master/entsoe>`_ (March 2022) as a PyPSA network.
 
 Relevant Settings
 -----------------
@@ -59,8 +56,19 @@ Outputs
     .. image:: img/base.png
         :scale: 33 %
 
+- ``resources/regions_onshore.geojson``:
+
+    .. image:: img/regions_onshore.png
+        :scale: 33 %
+
+- ``resources/regions_offshore.geojson``:
+
+    .. image:: img/regions_offshore.png
+        :scale: 33 %
+
 Description
 -----------
+Creates the network topology from an ENTSO-E map extract, and create Voronoi shapes for each bus representing both onshore and offshore regions.
 """
 
 import logging
@@ -75,11 +83,11 @@ import shapely
 import shapely.prepared
 import shapely.wkt
 import yaml
-from _helpers import configure_logging, get_snapshots, set_scenario_config
+from _helpers import REGION_COLS, configure_logging, get_snapshots, set_scenario_config
 from packaging.version import Version, parse
 from scipy import spatial
 from scipy.sparse import csgraph
-from shapely.geometry import LineString, Point
+from shapely.geometry import LineString, Point, Polygon
 
 PD_GE_2_2 = parse(pd.__version__) >= Version("2.2")
 
@@ -698,6 +706,22 @@ def _adjust_capacities_of_under_construction_branches(n, config):
     return n
 
 
+def _set_shapes(n, country_shapes, offshore_shapes):
+    # Write the geodataframes country_shapes and offshore_shapes to the network.shapes component
+    country_shapes = gpd.read_file(country_shapes).rename(columns={"name": "idx"})
+    country_shapes["type"] = "country"
+    offshore_shapes = gpd.read_file(offshore_shapes).rename(columns={"name": "idx"})
+    offshore_shapes["type"] = "offshore"
+    all_shapes = pd.concat([country_shapes, offshore_shapes], ignore_index=True)
+    n.madd(
+        "Shape",
+        all_shapes.index,
+        geometry=all_shapes.geometry,
+        idx=all_shapes.idx,
+        type=all_shapes["type"],
+    )
+
+
 def base_network(
     eg_buses,
     eg_converters,
@@ -758,9 +782,150 @@ def base_network(
 
     n = _adjust_capacities_of_under_construction_branches(n, config)
 
+    _set_shapes(n, country_shapes, offshore_shapes)
+
     return n
 
 
+def voronoi_partition_pts(points, outline):
+    """
+    Compute the polygons of a voronoi partition of `points` within the polygon
+    `outline`. Taken from
+    https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py.
+
+    Attributes
+    ----------
+    points : Nx2 - ndarray[dtype=float]
+    outline : Polygon
+    Returns
+    -------
+    polygons : N - ndarray[dtype=Polygon|MultiPolygon]
+    """
+    points = np.asarray(points)
+
+    if len(points) == 1:
+        polygons = [outline]
+    else:
+        xmin, ymin = np.amin(points, axis=0)
+        xmax, ymax = np.amax(points, axis=0)
+        xspan = xmax - xmin
+        yspan = ymax - ymin
+
+        # to avoid any network positions outside all Voronoi cells, append
+        # the corners of a rectangle framing these points
+        vor = spatial.Voronoi(
+            np.vstack(
+                (
+                    points,
+                    [
+                        [xmin - 3.0 * xspan, ymin - 3.0 * yspan],
+                        [xmin - 3.0 * xspan, ymax + 3.0 * yspan],
+                        [xmax + 3.0 * xspan, ymin - 3.0 * yspan],
+                        [xmax + 3.0 * xspan, ymax + 3.0 * yspan],
+                    ],
+                )
+            )
+        )
+
+        polygons = []
+        for i in range(len(points)):
+            poly = Polygon(vor.vertices[vor.regions[vor.point_region[i]]])
+
+            if not poly.is_valid:
+                poly = poly.buffer(0)
+
+            with np.errstate(invalid="ignore"):
+                poly = poly.intersection(outline)
+
+            polygons.append(poly)
+
+    return polygons
+
+
+def build_bus_shapes(n, country_shapes, offshore_shapes, countries):
+    country_shapes = gpd.read_file(country_shapes).set_index("name")["geometry"]
+    offshore_shapes = gpd.read_file(offshore_shapes)
+    offshore_shapes = offshore_shapes.reindex(columns=REGION_COLS).set_index("name")[
+        "geometry"
+    ]
+
+    onshore_regions = []
+    offshore_regions = []
+
+    for country in countries:
+        c_b = n.buses.country == country
+
+        onshore_shape = country_shapes[country]
+        onshore_locs = (
+            n.buses.loc[c_b & n.buses.onshore_bus]
+            .sort_values(
+                by="substation_lv", ascending=False
+            )  # preference for substations
+            .drop_duplicates(subset=["x", "y"], keep="first")[["x", "y"]]
+        )
+        onshore_regions.append(
+            gpd.GeoDataFrame(
+                {
+                    "name": onshore_locs.index,
+                    "x": onshore_locs["x"],
+                    "y": onshore_locs["y"],
+                    "geometry": voronoi_partition_pts(
+                        onshore_locs.values, onshore_shape
+                    ),
+                    "country": country,
+                }
+            )
+        )
+
+        if country not in offshore_shapes.index:
+            continue
+        offshore_shape = offshore_shapes[country]
+        offshore_locs = n.buses.loc[c_b & n.buses.substation_off, ["x", "y"]]
+        offshore_regions_c = gpd.GeoDataFrame(
+            {
+                "name": offshore_locs.index,
+                "x": offshore_locs["x"],
+                "y": offshore_locs["y"],
+                "geometry": voronoi_partition_pts(offshore_locs.values, offshore_shape),
+                "country": country,
+            }
+        )
+        offshore_regions_c = offshore_regions_c.loc[offshore_regions_c.area > 1e-2]
+        offshore_regions.append(offshore_regions_c)
+
+    shapes = pd.concat(onshore_regions, ignore_index=True)
+
+    return onshore_regions, offshore_regions, shapes
+
+
+def append_bus_shapes(n, shapes, type):
+    """
+    Append shapes to the network. If shapes with the same component and type
+    already exist, they will be removed.
+
+    Parameters:
+        n (pypsa.Network): The network to which the shapes will be appended.
+        shapes (geopandas.GeoDataFrame): The shapes to be appended.
+        **kwargs: Additional keyword arguments used in `n.madd`.
+
+    Returns:
+        None
+    """
+    remove = n.shapes.query("component == 'Bus' and type == @type").index
+    n.mremove("Shape", remove)
+
+    offset = n.shapes.index.astype(int).max() + 1 if not n.shapes.empty else 0
+    shapes = shapes.rename(lambda x: int(x) + offset)
+    n.madd(
+        "Shape",
+        shapes.index,
+        geometry=shapes.geometry,
+        idx=shapes.name,
+        component="Bus",
+        type=type,
+    )
+
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
@@ -784,5 +949,22 @@ if __name__ == "__main__":
         snakemake.config,
     )
 
+    onshore_regions, offshore_regions, shapes = build_bus_shapes(
+        n,
+        snakemake.input.country_shapes,
+        snakemake.input.offshore_shapes,
+        snakemake.params.countries,
+    )
+
+    shapes.to_file(snakemake.output.regions_onshore)
+    append_bus_shapes(n, shapes, "onshore")
+
+    if offshore_regions:
+        shapes = pd.concat(offshore_regions, ignore_index=True)
+        shapes.to_file(snakemake.output.regions_offshore)
+        append_bus_shapes(n, shapes, "offshore")
+    else:
+        offshore_shapes.to_frame().to_file(snakemake.output.regions_offshore)
+
     n.meta = snakemake.config
-    n.export_to_netcdf(snakemake.output[0])
+    n.export_to_netcdf(snakemake.output.base_network)

scripts/build_bus_regions.py

@@ -1,184 +0,0 @@
-# -*- coding: utf-8 -*-
-# SPDX-FileCopyrightText: : 2017-2024 The PyPSA-Eur Authors
-#
-# SPDX-License-Identifier: MIT
-"""
-Creates Voronoi shapes for each bus representing both onshore and offshore
-regions.
-
-Relevant Settings
------------------
-
-.. code:: yaml
-
-    countries:
-
-.. seealso::
-    Documentation of the configuration file ``config/config.yaml`` at
-    :ref:`toplevel_cf`
-
-Inputs
-------
-
-- ``resources/country_shapes.geojson``: confer :ref:`shapes`
-- ``resources/offshore_shapes.geojson``: confer :ref:`shapes`
-- ``networks/base.nc``: confer :ref:`base`
-
-Outputs
--------
-
-- ``resources/regions_onshore.geojson``:
-
-    .. image:: img/regions_onshore.png
-        :scale: 33 %
-
-- ``resources/regions_offshore.geojson``:
-
-    .. image:: img/regions_offshore.png
-        :scale: 33 %
-
-Description
------------
-"""
-
-import logging
-
-import geopandas as gpd
-import numpy as np
-import pandas as pd
-import pypsa
-from _helpers import REGION_COLS, configure_logging, set_scenario_config
-from scipy.spatial import Voronoi
-from shapely.geometry import Polygon
-
-logger = logging.getLogger(__name__)
-
-
-def voronoi_partition_pts(points, outline):
-    """
-    Compute the polygons of a voronoi partition of `points` within the polygon
-    `outline`. Taken from
-    https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py.
-
-    Attributes
-    ----------
-    points : Nx2 - ndarray[dtype=float]
-    outline : Polygon
-    Returns
-    -------
-    polygons : N - ndarray[dtype=Polygon|MultiPolygon]
-    """
-    points = np.asarray(points)
-
-    if len(points) == 1:
-        polygons = [outline]
-    else:
-        xmin, ymin = np.amin(points, axis=0)
-        xmax, ymax = np.amax(points, axis=0)
-        xspan = xmax - xmin
-        yspan = ymax - ymin
-
-        # to avoid any network positions outside all Voronoi cells, append
-        # the corners of a rectangle framing these points
-        vor = Voronoi(
-            np.vstack(
-                (
-                    points,
-                    [
-                        [xmin - 3.0 * xspan, ymin - 3.0 * yspan],
-                        [xmin - 3.0 * xspan, ymax + 3.0 * yspan],
-                        [xmax + 3.0 * xspan, ymin - 3.0 * yspan],
-                        [xmax + 3.0 * xspan, ymax + 3.0 * yspan],
-                    ],
-                )
-            )
-        )
-
-        polygons = []
-        for i in range(len(points)):
-            poly = Polygon(vor.vertices[vor.regions[vor.point_region[i]]])
-
-            if not poly.is_valid:
-                poly = poly.buffer(0)
-
-            with np.errstate(invalid="ignore"):
-                poly = poly.intersection(outline)
-
-            polygons.append(poly)
-
-    return polygons
-
-
-if __name__ == "__main__":
-    if "snakemake" not in globals():
-        from _helpers import mock_snakemake
-
-        snakemake = mock_snakemake("build_bus_regions")
-    configure_logging(snakemake)
-    set_scenario_config(snakemake)
-
-    countries = snakemake.params.countries
-
-    n = pypsa.Network(snakemake.input.base_network)
-
-    country_shapes = gpd.read_file(snakemake.input.country_shapes).set_index("name")[
-        "geometry"
-    ]
-    offshore_shapes = gpd.read_file(snakemake.input.offshore_shapes)
-    offshore_shapes = offshore_shapes.reindex(columns=REGION_COLS).set_index("name")[
-        "geometry"
-    ]
-
-    onshore_regions = []
-    offshore_regions = []
-
-    for country in countries:
-        c_b = n.buses.country == country
-
-        onshore_shape = country_shapes[country]
-        onshore_locs = (
-            n.buses.loc[c_b & n.buses.onshore_bus]
-            .sort_values(
-                by="substation_lv", ascending=False
-            )  # preference for substations
-            .drop_duplicates(subset=["x", "y"], keep="first")[["x", "y"]]
-        )
-        onshore_regions.append(
-            gpd.GeoDataFrame(
-                {
-                    "name": onshore_locs.index,
-                    "x": onshore_locs["x"],
-                    "y": onshore_locs["y"],
-                    "geometry": voronoi_partition_pts(
-                        onshore_locs.values, onshore_shape
-                    ),
-                    "country": country,
-                }
-            )
-        )
-
-        if country not in offshore_shapes.index:
-            continue
-        offshore_shape = offshore_shapes[country]
-        offshore_locs = n.buses.loc[c_b & n.buses.substation_off, ["x", "y"]]
-        offshore_regions_c = gpd.GeoDataFrame(
-            {
-                "name": offshore_locs.index,
-                "x": offshore_locs["x"],
-                "y": offshore_locs["y"],
-                "geometry": voronoi_partition_pts(offshore_locs.values, offshore_shape),
-                "country": country,
-            }
-        )
-        offshore_regions_c = offshore_regions_c.loc[offshore_regions_c.area > 1e-2]
-        offshore_regions.append(offshore_regions_c)
-
-    pd.concat(onshore_regions, ignore_index=True).to_file(
-        snakemake.output.regions_onshore
-    )
-    if offshore_regions:
-        pd.concat(offshore_regions, ignore_index=True).to_file(
-            snakemake.output.regions_offshore
-        )
-    else:
-        offshore_shapes.to_frame().to_file(snakemake.output.regions_offshore)

scripts/build_electricity_demand.py

@@ -129,7 +129,7 @@ def copy_timeslice(load, cntry, start, stop, delta, fn_load=None):
             load.loc[start:stop, cntry] = load.loc[
                 start - delta : stop - delta, cntry
             ].values
-        elif fn_load is not None:
+        elif fn_load is not None and cntry in load:
             duration = pd.date_range(freq="h", start=start - delta, end=stop - delta)
             load_raw = load_timeseries(fn_load, duration, [cntry])
             load.loc[start:stop, cntry] = load_raw.loc[
@@ -311,6 +311,8 @@ if __name__ == "__main__":
         logger.info("Supplement missing data with synthetic data.")
         fn = snakemake.input.synthetic
         synthetic_load = pd.read_csv(fn, index_col=0, parse_dates=True)
+        # "UA" does not appear in synthetic load data
+        countries = list(set(countries) - set(["UA"]))
         synthetic_load = synthetic_load.loc[snapshots, countries]
         load = load.combine_first(synthetic_load)
 

scripts/build_hydro_profile.py

@@ -139,7 +139,10 @@ def approximate_missing_eia_stats(eia_stats, runoff_fn, countries):
     runoff.index = runoff.index.astype(int)
 
     # fix outliers; exceptional floods in 1977-1979 in ES & PT
-    runoff.loc[1978, ["ES", "PT"]] = runoff.loc[1979, ["ES", "PT"]]
+    if "ES" in runoff:
+        runoff.loc[1978, "ES"] = runoff.loc[1979, "ES"]
+    if "PT" in runoff:
+        runoff.loc[1978, "PT"] = runoff.loc[1979, "PT"]
 
     runoff_eia = runoff.loc[eia_stats.index]
 

scripts/cluster_network.py

@@ -135,6 +135,7 @@ import pypsa
 import seaborn as sns
 from _helpers import configure_logging, set_scenario_config, update_p_nom_max
 from add_electricity import load_costs
+from base_network import append_bus_shapes
 from packaging.version import Version, parse
 from pypsa.clustering.spatial import (
     busmap_by_greedy_modularity,
@@ -428,20 +429,27 @@ def clustering_for_n_clusters(
     return clustering
 
 
-def cluster_regions(busmaps, input=None, output=None):
+def cluster_regions(busmaps, regions):
+    """
+    Cluster regions based on busmaps and save the results to a file and to the
+    network.
+
+    Parameters:
+    - busmaps (list): A list of busmaps used for clustering.
+    - which (str): The type of regions to cluster.
+
+    Returns:
+    None
+    """
     busmap = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
-
-    for which in ("regions_onshore", "regions_offshore"):
-        regions = gpd.read_file(getattr(input, which))
-        regions = regions.reindex(columns=["name", "geometry"]).set_index("name")
-        regions_c = regions.dissolve(busmap)
-        regions_c.index.name = "name"
-        regions_c = regions_c.reset_index()
-        regions_c.to_file(getattr(output, which))
+    regions = regions.reindex(columns=["name", "geometry"]).set_index("name")
+    regions_c = regions.dissolve(busmap)
+    regions_c.index.name = "name"
+    return regions_c.reset_index()
 
 
-def plot_busmap_for_n_clusters(n, n_clusters, fn=None):
-    busmap = busmap_for_n_clusters(n, n_clusters)
+def plot_busmap_for_n_clusters(n, n_clusters, solver_name="scip", fn=None):
+    busmap = busmap_for_n_clusters(n, n_clusters, solver_name)
     cs = busmap.unique()
     cr = sns.color_palette("hls", len(cs))
     n.plot(bus_colors=busmap.map(dict(zip(cs, cr))))
@@ -538,21 +546,25 @@ if __name__ == "__main__":
             params.focus_weights,
         )
 
-    update_p_nom_max(clustering.network)
+    nc = clustering.network
+    update_p_nom_max(nc)
 
     if params.cluster_network.get("consider_efficiency_classes"):
         labels = [f" {label} efficiency" for label in ["low", "medium", "high"]]
-        nc = clustering.network
         nc.generators["carrier"] = nc.generators.carrier.replace(labels, "", regex=True)
 
-    clustering.network.meta = dict(
-        snakemake.config, **dict(wildcards=dict(snakemake.wildcards))
-    )
-    clustering.network.export_to_netcdf(snakemake.output.network)
     for attr in (
         "busmap",
         "linemap",
     ):  # also available: linemap_positive, linemap_negative
         getattr(clustering, attr).to_csv(snakemake.output[attr])
 
-    cluster_regions((clustering.busmap,), snakemake.input, snakemake.output)
+    nc.shapes = n.shapes.copy()
+    for which in ["regions_onshore", "regions_offshore"]:
+        regions = gpd.read_file(snakemake.input[which])
+        clustered_regions = cluster_regions((clustering.busmap,), regions)
+        clustered_regions.to_file(snakemake.output[which])
+        append_bus_shapes(nc, clustered_regions, type=which.split("_")[1])
+
+    nc.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
+    nc.export_to_netcdf(snakemake.output.network)

scripts/prepare_sector_network.py

@@ -97,7 +97,7 @@ def define_spatial(nodes, options):
         spatial.gas.industry = nodes + " gas for industry"
         spatial.gas.industry_cc = nodes + " gas for industry CC"
         spatial.gas.biogas_to_gas = nodes + " biogas to gas"
-        spatial.gas.biogas_to_gas_cc = nodes + "biogas to gas CC"
+        spatial.gas.biogas_to_gas_cc = nodes + " biogas to gas CC"
     else:
         spatial.gas.nodes = ["EU gas"]
         spatial.gas.locations = ["EU"]

scripts/retrieve_irena.py

@@ -1,108 +0,0 @@
-# -*- coding: utf-8 -*-
-# Copyright 2023 Thomas Gilon (Climact)
-# SPDX-FileCopyrightText: : 2017-2024 The PyPSA-Eur Authors
-#
-# SPDX-License-Identifier: MIT
-"""
-This rule downloads the existing capacities from `IRENASTAT <https://www.irena.org/Data/Downloads/IRENASTAT>`_ and extracts it in the ``data/existing_capacities`` sub-directory.
-
-**Relevant Settings**
-
-.. code:: yaml
-
-    enable:
-        retrieve_irena:
-
-.. seealso::
-    Documentation of the configuration file ``config.yaml`` at
-    :ref:`enable_cf`
-
-**Outputs**
-
-- ``data/existing_capacities``: existing capacities for offwind, onwind and solar
-
-"""
-
-import logging
-
-import pandas as pd
-from _helpers import configure_logging, set_scenario_config
-
-logger = logging.getLogger(__name__)
-
-REGIONS = [
-    "Albania",
-    "Austria",
-    "Belgium",
-    "Bosnia and Herzegovina",
-    "Bulgaria",
-    "Croatia",
-    "Czechia",
-    "Denmark",
-    "Estonia",
-    "Finland",
-    "France",
-    "Germany",
-    "Greece",
-    "Hungary",
-    "Ireland",
-    "Italy",
-    "Latvia",
-    "Lithuania",
-    "Luxembourg",
-    "Montenegro",
-    # "Netherlands",
-    "Netherlands (Kingdom of the)",
-    "North Macedonia",
-    "Norway",
-    "Poland",
-    "Portugal",
-    "Romania",
-    "Serbia",
-    "Slovakia",
-    "Slovenia",
-    "Spain",
-    "Sweden",
-    "Switzerland",
-    # "United Kingdom",
-    "United Kingdom of Great Britain and Northern Ireland (the)",
-]
-
-REGIONS_DICT = {
-    "Bosnia and Herzegovina": "Bosnia Herzg",
-    "Netherlands (Kingdom of the)": "Netherlands",
-    "United Kingdom of Great Britain and Northern Ireland (the)": "UK",
-}
-
-if __name__ == "__main__":
-    if "snakemake" not in globals():
-        from _helpers import mock_snakemake
-
-        snakemake = mock_snakemake("retrieve_irena")
-    configure_logging(snakemake)
-    set_scenario_config(snakemake)
-
-    irena_raw = pd.read_csv(
-        "https://pxweb.irena.org:443/sq/99e64b12-fe03-4a7b-92ea-a22cc3713b92",
-        skiprows=2,
-        index_col=[0, 1, 3],
-        encoding="latin-1",
-    )
-
-    var = "Installed electricity capacity (MW)"
-    irena = irena_raw[var].unstack(level=2).reset_index(level=1).replace(0, "")
-
-    irena = irena[irena.index.isin(REGIONS)]
-    irena.rename(index=REGIONS_DICT, inplace=True)
-
-    df_offwind = irena[irena.Technology.str.contains("Offshore")].drop(
-        columns=["Technology"]
-    )
-    df_onwind = irena[irena.Technology.str.contains("Onshore")].drop(
-        columns=["Technology"]
-    )
-    df_pv = irena[irena.Technology.str.contains("Solar")].drop(columns=["Technology"])
-
-    df_offwind.to_csv(snakemake.output["offwind"])
-    df_onwind.to_csv(snakemake.output["onwind"])
-    df_pv.to_csv(snakemake.output["solar"])

scripts/simplify_network.py

@@ -88,12 +88,14 @@ The rule :mod:`simplify_network` does up to four things:
 import logging
 from functools import reduce
 
+import geopandas as gpd
 import numpy as np
 import pandas as pd
 import pypsa
 import scipy as sp
 from _helpers import configure_logging, set_scenario_config, update_p_nom_max
 from add_electricity import load_costs
+from base_network import append_bus_shapes
 from cluster_network import cluster_regions, clustering_for_n_clusters
 from pypsa.clustering.spatial import (
     aggregateoneport,
@@ -207,7 +209,7 @@ def _compute_connection_costs_to_bus(
     return connection_costs_to_bus
 
 
-def _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus, output):
+def _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus):
     connection_costs = {}
     for tech in connection_costs_to_bus:
         tech_b = n.generators.carrier == tech
@@ -228,14 +230,12 @@ def _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus, out
                 )
             )
             connection_costs[tech] = costs
-    pd.DataFrame(connection_costs).to_csv(output.connection_costs)
 
 
 def _aggregate_and_move_components(
     n,
     busmap,
     connection_costs_to_bus,
-    output,
     aggregate_one_ports={"Load", "StorageUnit"},
     aggregation_strategies=dict(),
     exclude_carriers=None,
@@ -248,7 +248,7 @@ def _aggregate_and_move_components(
             if not df.empty:
                 import_series_from_dataframe(n, df, c, attr)
 
-    _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus, output)
+    _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus)
 
     generator_strategies = aggregation_strategies["generators"]
 
@@ -281,7 +281,6 @@ def simplify_links(
     length_factor,
     p_max_pu,
     exclude_carriers,
-    output,
     aggregation_strategies=dict(),
 ):
     ## Complex multi-node links are folded into end-points
@@ -406,7 +405,6 @@ def simplify_links(
         n,
         busmap,
         connection_costs_to_bus,
-        output,
         aggregation_strategies=aggregation_strategies,
         exclude_carriers=exclude_carriers,
     )
@@ -419,7 +417,6 @@ def remove_stubs(
     renewable_carriers,
     length_factor,
     simplify_network,
-    output,
     aggregation_strategies=dict(),
 ):
     logger.info("Removing stubs")
@@ -436,7 +433,6 @@ def remove_stubs(
         n,
         busmap,
         connection_costs_to_bus,
-        output,
         aggregation_strategies=aggregation_strategies,
         exclude_carriers=simplify_network["exclude_carriers"],
     )
@@ -556,7 +552,6 @@ if __name__ == "__main__":
         params.length_factor,
         params.p_max_pu,
         params.simplify_network["exclude_carriers"],
-        snakemake.output,
         params.aggregation_strategies,
     )
 
@@ -569,7 +564,6 @@ if __name__ == "__main__":
             params.renewable_carriers,
             params.length_factor,
             params.simplify_network,
-            snakemake.output,
             aggregation_strategies=params.aggregation_strategies,
         )
         busmaps.append(stub_map)
@@ -610,6 +604,7 @@ if __name__ == "__main__":
     n.lines.drop(remove, axis=1, errors="ignore", inplace=True)
 
     if snakemake.wildcards.simpl:
+        shapes = n.shapes
         n, cluster_map = cluster(
             n,
             int(snakemake.wildcards.simpl),
@@ -619,14 +614,19 @@ if __name__ == "__main__":
             params.simplify_network["feature"],
             params.aggregation_strategies,
         )
+        n.shapes = shapes
         busmaps.append(cluster_map)
 
     update_p_nom_max(n)
 
-    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
-    n.export_to_netcdf(snakemake.output.network)
-
     busmap_s = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
     busmap_s.to_csv(snakemake.output.busmap)
 
-    cluster_regions(busmaps, snakemake.input, snakemake.output)
+    for which in ["regions_onshore", "regions_offshore"]:
+        regions = gpd.read_file(snakemake.input[which])
+        clustered_regions = cluster_regions(busmaps, regions)
+        clustered_regions.to_file(snakemake.output[which])
+        append_bus_shapes(n, clustered_regions, type=which.split("_")[1])
+
+    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
+    n.export_to_netcdf(snakemake.output.network)

scripts/solve_network.py

@@ -159,6 +159,9 @@ def _add_land_use_constraint_m(n, planning_horizons, config):
     current_horizon = snakemake.wildcards.planning_horizons
 
     for carrier in ["solar", "onwind", "offwind-ac", "offwind-dc"]:
+        extendable_i = (n.generators.carrier == carrier) & n.generators.p_nom_extendable
+        n.generators.loc[extendable_i, "p_nom_min"] = 0
+
         existing = n.generators.loc[n.generators.carrier == carrier, "p_nom"]
         ind = list(
             {i.split(sep=" ")[0] + " " + i.split(sep=" ")[1] for i in existing.index}
@@ -180,6 +183,19 @@ def _add_land_use_constraint_m(n, planning_horizons, config):
                 sel_p_year
             ].rename(lambda x: x[:-4] + current_horizon)
 
+    # check if existing capacities are larger than technical potential
+    existing_large = n.generators[
+        n.generators["p_nom_min"] > n.generators["p_nom_max"]
+    ].index
+    if len(existing_large):
+        logger.warning(
+            f"Existing capacities larger than technical potential for {existing_large},\
+                        adjust technical potential to existing capacities"
+        )
+        n.generators.loc[existing_large, "p_nom_max"] = n.generators.loc[
+            existing_large, "p_nom_min"
+        ]
+
     n.generators.p_nom_max.clip(lower=0, inplace=True)