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solve_network.py: Remove hacked installation of conda libraries

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Tom Brown 2020-03-04 18:10:57 +01:00
parent ab401907b2
commit 5dc572c35e
4 changed files with 6 additions and 20 deletions
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7
README.md
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@ -40,11 +40,8 @@ projects % git clone git@github.com:nworbmot/pypsa-eur-sec.git
The requirements are the same as
[PyPSA-Eur](https://github.com/PyPSA/pypsa-eur), but for
`solve_network.py` in addition you need `gurobipy` and version 0.16.0
or greater of PyPSA in order to use the `nomopyomo` framework. These
libraries are currently imported "by hand" at the start of the
`solve_network.py` script.
`solve_network.py` in addition you need `gurobipy` and version 0.16.1
or greater of PyPSA in order to use the `nomopyomo` framework.
## Data requirements

4
Snakefile
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@ -172,7 +172,7 @@ rule build_industrial_demand:
rule prepare_sector_network:
input:
network=pypsaeur('networks/{network}_s{simpl}_{clusters}_ec_lv{lv}_{opts}.nc'),
network=pypsaeur('networks/{network}_s{simpl}_{clusters}_lv{lv}_{opts}.nc'),
energy_totals_name='data/energy_totals.csv',
co2_totals_name='data/co2_totals.csv',
transport_name='data/transport_data.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=20000 #memory in MB; 40 GB enough for 45+B+I; 100 GB based on RESI usage for 128
resources: mem=100000 #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"

4
config.yaml
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@ -2,7 +2,7 @@ logging_level: INFO
results_dir: 'results/'
summary_dir: results
run: '191222-181-lv'
run: '200126-181-lv-solar3'
scenario:
sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
@ -10,7 +10,7 @@ scenario:
lv: [1.0, 1.125, 1.25, 1.5, 2.0]# or opt
clusters: [181] #[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]#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]#,Co2L0p2-3H-T-H-B-I,Co2L0p5-3H-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]
sector_opts: [Co2L0-3H-T-H-B-I-solar3]#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]#,Co2L0p2-3H-T-H-B-I,Co2L0p5-3H-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

11
scripts/solve_network.py
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@ -1,14 +1,3 @@
import os
os.system("conda install -y -c gurobi gurobi=8.1.0")
os.system("conda install -y -c conda-forge pypsa=0.16.1")
#import sys
#sys.path = ["pypsa"] + sys.path
import numpy as np
import pandas as pd