This commit now work with PyPSA-Eur 0.1.0 (tested with commit
bb3477 from 14th April 2020).
Changes to line/link_widths/colors for plotting networks in PyPSA
0.17.0.
Other corrections to plotting code so it works with this version.
Include oil boilers in colors in config.yaml.
* prepare_sector_network:
- add link for oil boiler in function add_industry()
- add function for partitioning clusters into different heat node types
* config.yaml: add option for oil_boiler
* costs.csv: add costs for oil boiler
* changes for retrofitting
* changed Snakefile to work with new pypsa-eur version, change solve_network.py to clip also n.generators_t.p_min_pu
* removed retrofitting data files
Use s_nom_min for the reference point for the transmission
reinforcement not s_nom, since s_nom is now overwritten for LV > 1.0
(the old pyomo code kept the s_nom variable fixed in the pyomo model
rather than via pypsa setting s_nom_extendable = False, like the
nomopyomo code now does).
The legend scale of the H2 network electrolyzers is wrong. I don't yet
understand why. Possibly the cost scale in the other map is also wrong.
df.loc[idx[a,b,some_list],label] does NOT preserve the ordering of
some_list, but sorts it instead. Therefore the pattern:
df.loc[idx[a,b,s.index],label] = s.values
was mismatching the index and values.
Remove emissions from hydrogen production for ammonia (since H2 now
comes from electrolysis).
Allow process emissions from petrochemical production to be captured
(the carbon is not necessarily fossil, but could come from CCU).
With new pandas:
pd.Index([])|pd.MultiIndex(...)
returns a pd.Index, not a pd.MultiIndex, so just reversed:
pd.MultiIndex(...)|pd.Index([])
This returns a pd.MultiIndex.
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.
All urban central (i.e. district heating) is aggregated to the same
profile and bus.
The code is now written to cycle over each heating sector to add
demand and supply technologies, only changing what is necessary to
change, rather than just copying chunks of code and modifying
parameters there. This should make it easier to get an overview of
what's going on.
These are specified in data/heat_load_profile.csv.
The resulting heat_demand df has MultiIndex columns, where the first
level is ["sector use"], and the second level level is nodes.
Because there was insufficient solid biomass in 3-4 countries to
supply industry for it locally, and we need to account for transport
of solid biomass.
Should be replaced by transport cost links between countries.
Heat buses renamed to:
rural (for low-density areas where district heating not possible)
urban decentral (for high-density areas without district heating and
individual heating technologies) (used to be called "urban")
urban central (for high-density areas with district heating) (used to
be called "central")
District heating losses applied only to urban central.
Before both initial SOC and final SOC were set to be zero, which
prevents synthetic fuel transfer over the year boundary, and prevents
the use of fossil fuels for non-zero CO2 scenarios.
Now done properly with cyclic Store (prevents accumulation of fossil
fuels as a form of sequestration) and Generator (to imitate fossil
fuel extraction).
tech name must only appear, but not be identical to generator
carrier. This allows to use the name "offshore" for both "offshore-ac"
and "offshore-dc", but then "solar" also catches "solar thermal",
which is fine since for solar thermal potentials are np.inf, unless
limit is 0 since np.inf*0 is nan.
Remove non-renewable generator and storage units from electricity-only
base network, since they're added differently here with links.
Remove unncessary cruft from config.yaml which is not used by
PyPSA-Eur-Sec (e.g. renewable configuration parameters).
Rename "naptha" to correct "naphtha".
