Switch to BDEW-based weekday/end space heating demand profiles

These are different for residential and services demand.

Also include Snakefile in config files copied for each run.

Use gurobi settings from gurobi support for speed.

Commented out settings for testing randomness for noise.

.gitignore

@@ -35,3 +35,4 @@ gurobi.log
 
 *.pyc
 /cutouts
+/tmp

Snakefile

@@ -178,7 +178,7 @@ rule prepare_sector_network:
         transport_name='data/transport_data.csv',
         biomass_potentials='data/biomass_potentials.csv',
         timezone_mappings='data/timezone_mappings.csv',
-        heat_profile="data/heat_load_profile.csv",
+        heat_profile="data/heat_load_profile_BDEW.csv",
         costs="data/costs.csv",
         clustered_pop_layout="resources/pop_layout_{network}_s{simpl}_{clusters}.csv",
         industrial_demand="resources/industrial_demand_{network}_s{simpl}_{clusters}.csv",
@@ -219,7 +219,7 @@ rule solve_network:
         memory="logs/" + config['run'] + "/{network}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_memory.log"
     benchmark: "benchmarks/solve_network/{network}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}"
     threads: 4
-    resources: mem=100000 #memory in MB; 40 GB enough for 45+B+I; 100 GB based on RESI usage for 128
+    resources: mem=50000 #memory in MB; 40 GB enough for 45+B+I; 100 GB based on RESI usage for 128
     # group: "solve" # with group, threads is ignored https://bitbucket.org/snakemake/snakemake/issues/971/group-job-description-does-not-contain
     script: "scripts/solve_network.py"
 

config.yaml

@@ -2,15 +2,15 @@ logging_level: INFO
 
 results_dir: 'results/'
 summary_dir: results
-run: '190728-space0p5'
+run: '190807-resserv_bdew'
 
 scenario:
   sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
   simpl: ['']
   lv: [1.0]#, 1.125, 1.25, 1.5, 2.0]# or opt
-  clusters: [128] #[90, 128, 181] #[45, 64, 90, 128, 181, 256] #, 362] # (2**np.r_[5.5:9:.5]).astype(int) minimum is 37
+  clusters: [50] #[90, 128, 181] #[45, 64, 90, 128, 181, 256] #, 362] # (2**np.r_[5.5:9:.5]).astype(int) minimum is 37
   opts: ['']  #for pypsa-eur
-  sector_opts: [Co2L0-3H-T-H-B-I-space0p5,Co2L0-3H-T-H-B-I-nodistrict-space0p5]#,Co2L0p1-3H-T-H-B-I,Co2L0p25-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#[Co2L0-3H-T-H-B-I-onwind0-solar3,Co2L0-3H-T-H-B-I-onwind0p125-solar3,Co2L0-3H-T-H-B-I-onwind0p25-solar3,Co2L0-3H-T-H-B-I-onwind0p50-solar3,Co2L0-3H-T-H-B-I-solar3]#,Co2L0-3H-T-H-B-I-onwind0p25-solar3]#,Co2L0p05-3H-T-H-B-I,Co2L0p10-3H-T-H-B-I,Co2L0p20-3H-T-H-B-I,Co2L0p30-3H-T-H-B-I,Co2L0p50-3H-T-H-B-I]#[Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0-3H-T-H,Co2L0p20-3H-T-H]   #Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p20-3H-T-HCo2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p30-3H-T-H,Co2L0p50-3H-T-H] #Co2L-3H,Co2L-3H-T,, LC-FL, LC-T, Ep-T, Co2L-T]
+  sector_opts: [Co2L0-3H-T-H-B-I]#,Co2L0p1-3H-T-H-B-I,Co2L0p25-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#[Co2L0-3H-T-H-B-I-onwind0-solar3,Co2L0-3H-T-H-B-I-onwind0p125-solar3,Co2L0-3H-T-H-B-I-onwind0p25-solar3,Co2L0-3H-T-H-B-I-onwind0p50-solar3,Co2L0-3H-T-H-B-I-solar3]#,Co2L0-3H-T-H-B-I-onwind0p25-solar3]#,Co2L0p05-3H-T-H-B-I,Co2L0p10-3H-T-H-B-I,Co2L0p20-3H-T-H-B-I,Co2L0p30-3H-T-H-B-I,Co2L0p50-3H-T-H-B-I]#[Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0-3H-T-H,Co2L0p20-3H-T-H]   #Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p20-3H-T-HCo2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p30-3H-T-H,Co2L0p50-3H-T-H] #Co2L-3H,Co2L-3H-T,, LC-FL, LC-T, Ep-T, Co2L-T]
   # Co2L will give default (5%); Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
 
 
@@ -116,6 +116,7 @@ costs:
 
 
 solving:
+  #tmpdir: "/mnt/lsdf/tom/playground/pypsa-eur-sec/tmp"
   options:
     formulation: kirchhoff
     clip_p_max_pu: 1.e-2
@@ -133,14 +134,18 @@ solving:
     method: 2 # barrier
     crossover: 0
     BarConvTol: 1.e-5
-    FeasibilityTol: 1.e-6
-  # solver:
-  #   name: cplex
-  #   threads: 4
-  #   lpmethod: 4 # barrier
-  #   solutiontype: 2 # non basic solution, ie no crossover
-  #   barrier.convergetol: 1.e-5
-  #   feasopt.tolerance: 1.e-6
+    Seed: 123
+    AggFill: 0
+    PreDual: 0
+    GURO_PAR_BARDENSETHRESH: 200
+    #FeasibilityTol: 1.e-6
+
+    #name: cplex
+    #threads: 4
+    #lpmethod: 4 # barrier
+    #solutiontype: 2 # non basic solution, ie no crossover
+    #barrier_convergetol: 1.e-5
+    #feasopt_tolerance: 1.e-6
 
 plotting:
   map:

data/heat_load_profile_BDEW.csv

@@ -0,0 +1,25 @@
+,residential space weekday,residential space weekend,services space weekday,services space weekend,residential water weekday,residential water weekend,services water weekday,services water weekend
+0,0.5437843306385036,0.5391846410003029,0.740230434593118,0.7918173557545402,1.0,1.0,1.0,1.0
+1,0.5690496225400243,0.5641534370440313,0.7642025524842398,0.7929627291950984,1.0,1.0,1.0,1.0
+2,0.5624023211873742,0.5575494117194042,0.8264420882344785,0.8961602364492307,1.0,1.0,1.0,1.0
+3,0.6120351867307156,0.6074588966300298,0.9338477492552973,1.066547622880321,1.0,1.0,1.0,1.0
+4,0.8210089232467712,0.8188451841881503,1.1288089786462463,1.2779268432155158,1.0,1.0,1.0,1.0
+5,1.2287073985428116,1.2315677844536332,1.3311522394966053,1.2808129834243316,1.0,1.0,1.0,1.0
+6,1.327953505819319,1.3349874311629708,1.3976491755316236,1.3076676145167292,1.0,1.0,1.0,1.0
+7,1.2533048874868005,1.2584095945395426,1.3529869654334066,1.239881414312941,1.0,1.0,1.0,1.0
+8,1.204661538907097,1.206562127967529,1.2631870820835946,1.157513929299677,1.0,1.0,1.0,1.0
+9,1.1511425365003825,1.152931252109671,1.183486516733693,1.1001631309844286,1.0,1.0,1.0,1.0
+10,1.0982914366923946,1.0987739728887453,1.1056637898031139,1.0553379006911972,1.0,1.0,1.0,1.0
+11,1.0602079991199889,1.0598534287519163,1.0536117591812475,0.9953570175561463,1.0,1.0,1.0,1.0
+12,1.0430483470403709,1.042552786631541,1.0075511014823457,0.9238971341830102,1.0,1.0,1.0,1.0
+13,1.023765876994618,1.0234573235486537,0.983633820661761,0.928978159404834,1.0,1.0,1.0,1.0
+14,1.0250355817085612,1.0241187665206792,0.973887563496691,0.9277637088455348,1.0,1.0,1.0,1.0
+15,1.0419068035344277,1.0407369052119213,0.968639109712126,0.940383626933661,1.0,1.0,1.0,1.0
+16,1.0886607269753739,1.0871365340901091,0.9776106671510321,0.9762628252848075,1.0,1.0,1.0,1.0
+17,1.1391891744979068,1.1377875788466947,0.9713068946564802,0.9923707220696051,1.0,1.0,1.0,1.0
+18,1.1813708458227477,1.1815796155786216,0.97710710371407,0.9822063279944322,1.0,1.0,1.0,1.0
+19,1.2048721952031847,1.2066686818939167,0.9620977486617706,0.9872726025741575,1.0,1.0,1.0,1.0
+20,1.1883594612741015,1.1911629803333679,0.9096499832485738,0.9736368622053816,1.0,1.0,1.0,1.0
+21,1.0841006081889941,1.0875548281900813,0.7954827338259405,0.8733383541170725,1.0,1.0,1.0,1.0
+22,0.8887378869444746,0.8893062174837649,0.7007233800713178,0.7753100551108082,1.0,1.0,1.0,1.0
+23,0.6584028044030574,0.6576606192147261,0.6910405618412271,0.756430842996538,1.0,1.0,1.0,1.0

scripts/copy_config.py

@@ -2,6 +2,7 @@
 from shutil import copy
 
 files = ["config.yaml",
+         "Snakefile",
          "scripts/solve_network.py",
          "scripts/prepare_sector_network.py"]
 

scripts/solve_network.py

@@ -21,8 +21,6 @@ from vresutils.benchmark import memory_logger
 
 
 
-
-
 #First tell PyPSA that links can have multiple outputs by
 #overriding the component_attrs. This can be done for
 #as many buses as you need with format busi for i = 2,3,4,5,....
@@ -73,9 +71,11 @@ def prepare_network(n, solve_opts=None):
             #if 'capital_cost' in t.df:
             #    t.df['capital_cost'] += 1e1 + 2.*(np.random.random(len(t.df)) - 0.5)
             if 'marginal_cost' in t.df:
+                np.random.seed(174)
                 t.df['marginal_cost'] += 1e-2 + 2e-3*(np.random.random(len(t.df)) - 0.5)
 
         for t in n.iterate_components(['Line', 'Link']):
+            np.random.seed(123)
             t.df['capital_cost'] += (1e-1 + 2e-2*(np.random.random(len(t.df)) - 0.5)) * t.df['length']
 
     if solve_opts.get('nhours'):
@@ -243,6 +243,7 @@ def solve_network(n, config=None, solver_log=None, opts=None):
                                      solver_options=solver_options,
                                      formulation=solve_opts['formulation'],
                                      extra_postprocessing=extra_postprocessing
+                                     #keep_files=True
                                      #free_memory={'pypsa'}
                                      )