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allowing a factor to alter the cost or p_nom_max via the config file

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This substitutes the previous way of doing it. Now, to multiply the reference p_nom_max by 3, one should include in the config file 'solar+p3' (instead of the previous solarx3)
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martavp 2021-01-14 13:49:17 +01:00
parent 0eb69365eb
commit 2555b66ba9
2 changed files with 4 additions and 2 deletions
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5
config.default.yaml
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@ -15,14 +15,15 @@ scenario:
lv: [1.0,1.5] # allowed transmission line volume expansion, can be any float >= 1.0 (today) or "opt"
clusters: [45,50] # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
opts: [''] # only relevant for PyPSA-Eur
sector_opts: [Co2L0-3H-T-H-B-I-solar3-dist1] # this is where the main scenario settings are
sector_opts: [Co2L0-3H-T-H-B-I-solar+p3-dist1] # this is where the main scenario settings are
# to really understand the options here, look in scripts/prepare_sector_network.py
# Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
# Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
# xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
# single letters are sectors: T for land transport, H for building heating,
# B for biomass supply, I for industry, shipping and aviation
# solarx or onwindx changes the available installable potential by factor x
# solar+c0.5 reduces the capital cost of solar to 50\% of reference value
# solar+p3 multiplies the available installable potential by factor 3
# dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
# for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative
# emissions throughout the transition path in the timeframe determined by the

1
doc/release_notes.rst
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@ -5,6 +5,7 @@ Release Notes
Future release
===================
*For the myopic option, a carbon budget and a type of decay (exponential or beta) can be selected in the config file to distribute the budget across the planning_horizons.
*Added an option to alter the capital cost or maximum capacity of carriers by a factor via ``carrier+factor`` in the ``{opts}`` wildcard. This can be useful for exploring uncertain cost parameters. Example: ``solar+c0.5`` reduces the capital cost of solar to 50\% of original values. Similarly ``solar+p3`` multiplies the p_nom_max by 3.
PyPSA-Eur-Sec 0.4.0 (11th December 2020)
=========================================