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Merge pull request #174 from PyPSA/release-v0.6

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Preparation of release v0.6
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Fabian Neumann 2021-10-04 17:47:06 +02:00 committed by GitHub
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3
.gitignore vendored
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@ -11,11 +11,8 @@ gurobi.log
/benchmarks /benchmarks
/logs /logs
/notebooks /notebooks
/data/timezone_mappings.csv
/data/urban_percent.csv
/data/links_p_nom.csv /data/links_p_nom.csv
/data/*totals.csv /data/*totals.csv
/data/*Jensen.csv
/data/biomass* /data/biomass*
/data/emobility/ /data/emobility/
/data/eea* /data/eea*

128
config.default.yaml
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@ -1,4 +1,4 @@
version: 0.5.0 version: 0.6.0
logging_level: INFO logging_level: INFO
@ -45,14 +45,14 @@ scenario:
# CO2 budget as a fraction of 1990 emissions # CO2 budget as a fraction of 1990 emissions
# this is over-ridden if CO2Lx is set in sector_opts # this is over-ridden if CO2Lx is set in sector_opts
# this is also over-ridden if cb is set in sector_opts # this is also over-ridden if cb is set in sector_opts
co2_budget: # co2_budget:
2020: 0.7011648746 # 2020: 0.7011648746
2025: 0.5241935484 # 2025: 0.5241935484
2030: 0.2970430108 # 2030: 0.2970430108
2035: 0.1500896057 # 2035: 0.1500896057
2040: 0.0712365591 # 2040: 0.0712365591
2045: 0.0322580645 # 2045: 0.0322580645
2050: 0 # 2050: 0
# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec # snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
snapshots: snapshots:
@ -146,11 +146,11 @@ sector:
potential: 0.6 # maximum fraction of urban demand which can be supplied by district heating potential: 0.6 # maximum fraction of urban demand which can be supplied by district heating
# increase of today's district heating demand to potential maximum district heating share # increase of today's district heating demand to potential maximum district heating share
# progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating # progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
progress: progress: 1
2020: 0.0 # 2020: 0.0
2030: 0.3 # 2030: 0.3
2040: 0.6 # 2040: 0.6
2050: 1.0 # 2050: 1.0
district_heating_loss: 0.15 district_heating_loss: 0.15
bev_dsm_restriction_value: 0.75 #Set to 0 for no restriction on BEV DSM bev_dsm_restriction_value: 0.75 #Set to 0 for no restriction on BEV DSM
bev_dsm_restriction_time: 7 #Time at which SOC of BEV has to be dsm_restriction_value bev_dsm_restriction_time: 7 #Time at which SOC of BEV has to be dsm_restriction_value
@ -170,16 +170,16 @@ sector:
bev_avail_mean: 0.8 bev_avail_mean: 0.8
v2g: true #allows feed-in to grid from EV battery v2g: true #allows feed-in to grid from EV battery
#what is not EV or FCEV is oil-fuelled ICE #what is not EV or FCEV is oil-fuelled ICE
land_transport_fuel_cell_share: # 1 means all FCEVs land_transport_fuel_cell_share: 0.15 # 1 means all FCEVs
2020: 0 # 2020: 0
2030: 0.05 # 2030: 0.05
2040: 0.1 # 2040: 0.1
2050: 0.15 # 2050: 0.15
land_transport_electric_share: # 1 means all EVs land_transport_electric_share: 0.85 # 1 means all EVs
2020: 0 # 2020: 0
2030: 0.25 # 2030: 0.25
2040: 0.6 # 2040: 0.6
2050: 0.85 # 2050: 0.85
transport_fuel_cell_efficiency: 0.5 transport_fuel_cell_efficiency: 0.5
transport_internal_combustion_efficiency: 0.3 transport_internal_combustion_efficiency: 0.3
agriculture_machinery_electric_share: 0 agriculture_machinery_electric_share: 0
@ -187,29 +187,29 @@ sector:
agriculture_machinery_electric_efficiency: 0.3 # electricity per use agriculture_machinery_electric_efficiency: 0.3 # electricity per use
shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011 shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
shipping_hydrogen_share: # 1 means all hydrogen FC shipping_hydrogen_share: 1 # 1 means all hydrogen FC
2020: 0 # 2020: 0
2025: 0 # 2025: 0
2030: 0.05 # 2030: 0.05
2035: 0.15 # 2035: 0.15
2040: 0.3 # 2040: 0.3
2045: 0.6 # 2045: 0.6
2050: 1 # 2050: 1
time_dep_hp_cop: true #time dependent heat pump coefficient of performance time_dep_hp_cop: true #time dependent heat pump coefficient of performance
heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
# conservatively high to cover hot water and space heating in poorly-insulated buildings # conservatively high to cover hot water and space heating in poorly-insulated buildings
reduce_space_heat_exogenously: true # reduces space heat demand by a given factor (applied before losses in DH) reduce_space_heat_exogenously: true # reduces space heat demand by a given factor (applied before losses in DH)
# this can represent e.g. building renovation, building demolition, or if # this can represent e.g. building renovation, building demolition, or if
# the factor is negative: increasing floor area, increased thermal comfort, population growth # the factor is negative: increasing floor area, increased thermal comfort, population growth
reduce_space_heat_exogenously_factor: # per unit reduction in space heat demand reduce_space_heat_exogenously_factor: 0.29 # per unit reduction in space heat demand
# the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221 # the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
2020: 0.10 # this results in a space heat demand reduction of 10% # 2020: 0.10 # this results in a space heat demand reduction of 10%
2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita # 2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita
2030: 0.09 # 2030: 0.09
2035: 0.11 # 2035: 0.11
2040: 0.16 # 2040: 0.16
2045: 0.21 # 2045: 0.21
2050: 0.29 # 2050: 0.29
retrofitting : # co-optimises building renovation to reduce space heat demand retrofitting : # co-optimises building renovation to reduce space heat demand
retro_endogen: false # co-optimise space heat savings retro_endogen: false # co-optimise space heat savings
cost_factor: 1.0 # weight costs for building renovation cost_factor: 1.0 # weight costs for building renovation
@ -251,32 +251,32 @@ sector:
industry: industry:
St_primary_fraction: # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6 St_primary_fraction: 0.3 # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
2020: 0.6 # 2020: 0.6
2025: 0.55 # 2025: 0.55
2030: 0.5 # 2030: 0.5
2035: 0.45 # 2035: 0.45
2040: 0.4 # 2040: 0.4
2045: 0.35 # 2045: 0.35
2050: 0.3 # 2050: 0.3
DRI_fraction: # fraction of the primary route converted to DRI + EAF DRI_fraction: 1 # fraction of the primary route converted to DRI + EAF
2020: 0 # 2020: 0
2025: 0 # 2025: 0
2030: 0.05 # 2030: 0.05
2035: 0.2 # 2035: 0.2
2040: 0.4 # 2040: 0.4
2045: 0.7 # 2045: 0.7
2050: 1 # 2050: 1
H2_DRI: 1.7 #H2 consumption in Direct Reduced Iron (DRI), MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279 H2_DRI: 1.7 #H2 consumption in Direct Reduced Iron (DRI), MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
elec_DRI: 0.322 #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf elec_DRI: 0.322 #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf
Al_primary_fraction: # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4 Al_primary_fraction: 0.2 # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
2020: 0.4 # 2020: 0.4
2025: 0.375 # 2025: 0.375
2030: 0.35 # 2030: 0.35
2035: 0.325 # 2035: 0.325
2040: 0.3 # 2040: 0.3
2045: 0.25 # 2045: 0.25
2050: 0.2 # 2050: 0.2
MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf
MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3 MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy) MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)

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data/heat_load_profile_DK_AdamJensen.csv Normal file
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@ -0,0 +1,25 @@
hour,weekday,weekend
0,0.9181438689,0.9421512708
1,0.9172359071,0.9400891069
2,0.9269464481,0.9461062015
3,0.9415047932,0.9535084941
4,0.9656299507,0.9651094993
5,1.0221166443,0.9834676747
6,1.1553090493,1.0124171051
7,1.2093411031,1.0446615927
8,1.1470295942,1.088203419
9,1.0877191341,1.1110334576
10,1.0418327372,1.0926752822
11,1.0062977133,1.055488209
12,0.9837030359,1.0251266112
13,0.9667570278,0.9990015154
14,0.9548320932,0.9782897278
15,0.9509232061,0.9698167237
16,0.9636973319,0.974288587
17,0.9799372563,0.9886456216
18,1.0046501848,1.0084159643
19,1.0079452419,1.0171243296
20,0.9860566481,0.9994722379
21,0.9705228074,0.982761591
22,0.9586485819,0.9698167237
23,0.9335023778,0.9515079292
1 hour weekday weekend
2 0 0.9181438689 0.9421512708
3 1 0.9172359071 0.9400891069
4 2 0.9269464481 0.9461062015
5 3 0.9415047932 0.9535084941
6 4 0.9656299507 0.9651094993
7 5 1.0221166443 0.9834676747
8 6 1.1553090493 1.0124171051
9 7 1.2093411031 1.0446615927
10 8 1.1470295942 1.088203419
11 9 1.0877191341 1.1110334576
12 10 1.0418327372 1.0926752822
13 11 1.0062977133 1.055488209
14 12 0.9837030359 1.0251266112
15 13 0.9667570278 0.9990015154
16 14 0.9548320932 0.9782897278
17 15 0.9509232061 0.9698167237
18 16 0.9636973319 0.974288587
19 17 0.9799372563 0.9886456216
20 18 1.0046501848 1.0084159643
21 19 1.0079452419 1.0171243296
22 20 0.9860566481 0.9994722379
23 21 0.9705228074 0.982761591
24 22 0.9586485819 0.9698167237
25 23 0.9335023778 0.9515079292

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data/urban_percent.csv Normal file
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@ -0,0 +1,30 @@
AT,66
BA,40
BE,98
BG,74
CH,74
CZ,73
DE,75
DK,88
EE,68
ES,80
FI,84
FR,80
GB,83
GR,78
HR,59
HU,71
IE,63
IT,69
LT,67
LU,90
LV,67
NL,90
NO,80
PL,61
PT,63
RO,55
RS,56
SE,86
SI,50
SK,54
1 AT 66
2 BA 40
3 BE 98
4 BG 74
5 CH 74
6 CZ 73
7 DE 75
8 DK 88
9 EE 68
10 ES 80
11 FI 84
12 FR 80
13 GB 83
14 GR 78
15 HR 59
16 HU 71
17 IE 63
18 IT 69
19 LT 67
20 LU 90
21 LV 67
22 NL 90
23 NO 80
24 PL 61
25 PT 63
26 RO 55
27 RS 56
28 SE 86
29 SI 50
30 SK 54

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doc/conf.py
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@ -56,23 +56,23 @@ source_suffix = '.rst'
# The encoding of source files. # The encoding of source files.
#source_encoding = 'utf-8-sig' #source_encoding = 'utf-8-sig'
progress
# The master toctree document. # The master toctree document.
master_doc = 'index' master_doc = 'index'
# General information about the project. # General information about the project.
project = u'PyPSA-Eur-Sec' project = u'PyPSA-Eur-Sec'
copyright = u'2019-2020 Tom Brown (KIT), Marta Victoria (Aarhus University), Lisa Zeyen (KIT)' copyright = u'2019-2021 Tom Brown (KIT, TUB), Marta Victoria (Aarhus University), Lisa Zeyen (KIT, TUB), Fabian Neumann (TUB)'
author = u'2019-2020 Tom Brown (KIT), Marta Victoria (Aarhus University), Lisa Zeyen (KIT)' author = u'2019-2021 Tom Brown (KIT, TUB), Marta Victoria (Aarhus University), Lisa Zeyen (KIT, TUB), Fabian Neumann (TUB)'
# The version info for the project you're documenting, acts as replacement for # The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the # |version| and |release|, also used in various other places throughout the
# built documents. # built documents.
# #
# The short X.Y version. # The short X.Y version.
version = u'0.5' version = u'0.6'
# The full version, including alpha/beta/rc tags. # The full version, including alpha/beta/rc tags.
release = u'0.5.0' release = u'0.6.0'
# The language for content autogenerated by Sphinx. Refer to documentation # The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages. # for a list of supported languages.

1
doc/data.csv
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@ -7,7 +7,6 @@ EEA emission statistics,eea/UNFCCC_v23.csv,EEA standard re-use policy,https://ww
Eurostat Energy Balances,eurostat-energy_balances-*/,Eurostat,https://ec.europa.eu/eurostat/web/energy/data/energy-balances Eurostat Energy Balances,eurostat-energy_balances-*/,Eurostat,https://ec.europa.eu/eurostat/web/energy/data/energy-balances
Swiss energy statistics from Swiss Federal Office of Energy,switzerland-sfoe/,unknown,http://www.bfe.admin.ch/themen/00526/00541/00542/02167/index.html?dossier_id=02169 Swiss energy statistics from Swiss Federal Office of Energy,switzerland-sfoe/,unknown,http://www.bfe.admin.ch/themen/00526/00541/00542/02167/index.html?dossier_id=02169
BASt emobility statistics,emobility/,unknown,http://www.bast.de/DE/Verkehrstechnik/Fachthemen/v2-verkehrszaehlung/Stundenwerte.html?nn=626916 BASt emobility statistics,emobility/,unknown,http://www.bast.de/DE/Verkehrstechnik/Fachthemen/v2-verkehrszaehlung/Stundenwerte.html?nn=626916
timezone mappings,timezone_mappings.csv,CC BY 4.0,Tom Brown
BDEW heating profile,heat_load_profile_BDEW.csv,unknown,https://github.com/oemof/demandlib BDEW heating profile,heat_load_profile_BDEW.csv,unknown,https://github.com/oemof/demandlib
heating profiles for Aarhus,heat_load_profile_DK_AdamJensen.csv,unknown,Adam Jensen MA thesis at Aarhus University heating profiles for Aarhus,heat_load_profile_DK_AdamJensen.csv,unknown,Adam Jensen MA thesis at Aarhus University
George Lavidas wind/wave costs,WindWaveWEC_GLTB.xlsx,unknown,George Lavidas George Lavidas wind/wave costs,WindWaveWEC_GLTB.xlsx,unknown,George Lavidas

1 description file/folder licence source
7 Eurostat Energy Balances eurostat-energy_balances-*/ Eurostat https://ec.europa.eu/eurostat/web/energy/data/energy-balances
8 Swiss energy statistics from Swiss Federal Office of Energy switzerland-sfoe/ unknown http://www.bfe.admin.ch/themen/00526/00541/00542/02167/index.html?dossier_id=02169
9 BASt emobility statistics emobility/ unknown http://www.bast.de/DE/Verkehrstechnik/Fachthemen/v2-verkehrszaehlung/Stundenwerte.html?nn=626916
timezone mappings timezone_mappings.csv CC BY 4.0 Tom Brown
10 BDEW heating profile heat_load_profile_BDEW.csv unknown https://github.com/oemof/demandlib
11 heating profiles for Aarhus heat_load_profile_DK_AdamJensen.csv unknown Adam Jensen MA thesis at Aarhus University
12 George Lavidas wind/wave costs WindWaveWEC_GLTB.xlsx unknown George Lavidas

10
doc/installation.rst
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@ -66,15 +66,15 @@ Data requirements
================= =================
Small data files are included directly in the git repository, while Small data files are included directly in the git repository, while
larger ones are archived in a data bundle. The data bundle's size is larger ones are archived in a data bundle on zenodo (`10.5281/zenodo.5546517 <https://doi.org/10.5281/zenodo.5546517>`_).
around 640 MB. The data bundle's size is around 640 MB.
To download and extract the data bundle on the command line: To download and extract the data bundle on the command line:
.. code:: bash .. code:: bash
`
projects/pypsa-eur-sec/data % wget "https://nworbmot.org/pypsa-eur-sec-data-bundle-210418.tar.gz" projects/pypsa-eur-sec/data % wget "https://zenodo.org/record/5546517/files/pypsa-eur-sec-data-bundle.tar.gz"
projects/pypsa-eur-sec/data % tar xvzf pypsa-eur-sec-data-bundle-210418.tar.gz projects/pypsa-eur-sec/data % tar xvzf pypsa-eur-sec-data-bundle.tar.gz
The data licences and sources are given in the following table. The data licences and sources are given in the following table.

205
doc/release_notes.rst
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@ -6,94 +6,193 @@ Future release
============== ==============
.. note:: .. note::
This unreleased version currently requires the master branches of PyPSA, PyPSA-Eur, and the technology-data repository. This unreleased version currently may require the master branches of PyPSA, PyPSA-Eur, and the technology-data repository.
PyPSA-Eur-Sec 0.6.0 (4 October 2021)
====================================
This release includes
improvements regarding the basic chemical production,
the addition of plastics recycling,
the addition of the agriculture, forestry and fishing sector,
more regionally resolved biomass potentials,
CO2 pipeline transport and storage, and
more options in setting exogenous transition paths,
besides many performance improvements.
This release is known to work with `PyPSA-Eur
<https://github.com/PyPSA/pypsa-eur>`_ Version 0.4.0, `Technology Data
<https://github.com/PyPSA/technology-data>`_ Version 0.3.0 and
`PyPSA <https://github.com/PyPSA/PyPSA>`_ Version 0.18.0.
Please note that the data bundle has also been updated.
**General**
* With this release, we change the license from copyleft GPLv3 to the more * With this release, we change the license from copyleft GPLv3 to the more
liberal MIT license with the consent of all contributors. liberal MIT license with the consent of all contributors.
**New features and functionality**
* Distinguish costs for home battery storage and inverter from utility-scale
battery costs.
* Separate basic chemicals into HVC (high-value chemicals), chlorine, methanol and ammonia
[`#166 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/166>`_].
* Add option to specify reuse, primary production, and mechanical and chemical
recycling fraction of platics
[`#166 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/166>`_].
* Include energy demands and CO2 emissions for the agriculture, forestry and fishing sector.
It is included by default through the option ``A`` in the ``sector_opts`` wildcard.
Part of the emissions (1.A.4.c) was previously assigned to "industry non-elec" in the ``co2_totals.csv``.
Hence, excluding the agriculture sector will now lead to a tighter CO2 limit.
Energy demands are taken from the JRC IDEES database (missing countries filled with eurostat data)
and are split into
electricity (lighting, ventilation, specific electricity uses, pumping devices (electric)),
heat (specific heat uses, low enthalpy heat)
machinery oil (motor drives, farming machine drives, pumping devices (diesel)).
Heat demand is assigned at "services rural heat" buses.
Electricity demands are added to low-voltage buses.
Time series for demands are constant and distributed inside countries by population
[`#147 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/147>`_].
* Include today's district heating shares in myopic optimisation and add option
to specify exogenous path for district heating share increase under ``sector:
district_heating:`` [`#149 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/149>`_].
* Added option for hydrogen liquefaction costs for hydrogen demand in shipping.
This introduces a new ``H2 liquid`` bus at each location. It is activated via
``sector: shipping_hydrogen_liquefaction: true``.
* The share of shipping transformed into hydrogen fuel cell can be now defined
for different years in the ``config.yaml`` file. The carbon emission from the
remaining share is treated as a negative load on the atmospheric carbon dioxide
bus, just like aviation and land transport emissions.
* The transformation of the Steel and Aluminium production can be now defined
for different years in the ``config.yaml`` file.
* Include the option to alter the maximum energy capacity of a store via the
``carrier+factor`` in the ``{sector_opts}`` wildcard. This can be useful for
sensitivity analyses. Example: ``co2 stored+e2`` multiplies the ``e_nom_max`` by
factor 2. In this example, ``e_nom_max`` represents the CO2 sequestration
potential in Europe.
* Use `JRC ENSPRESO database <https://data.jrc.ec.europa.eu/dataset/74ed5a04-7d74-4807-9eab-b94774309d9f>`_ to
spatially disaggregate biomass potentials to PyPSA-Eur regions based on
overlaps with NUTS2 regions from ENSPRESO (proportional to area) (`#151
<https://github.com/PyPSA/pypsa-eur-sec/pull/151>`_).
* Add option to regionally disaggregate biomass potential to individual nodes
(previously given per country, then distributed by population density within)
and allow the transport of solid biomass. The transport costs are determined
based on the `JRC-EU-Times Bioenergy report
<http://dx.doi.org/10.2790/01017>`_ in the new optional rule
``build_biomass_transport_costs``. Biomass transport can be activated with the
setting ``sector: biomass_transport: true``.
* Add option to regionally resolve CO2 storage and add CO2 pipeline transport
because geological storage potential,
CO2 utilisation sites and CO2 capture sites may be separated. The CO2 network
is built from zero based on the topology of the electricity grid (greenfield).
Pipelines are assumed to be bidirectional and lossless. Furthermore, neither
retrofitting of natural gas pipelines (required pressures are too high, 80-160
bar vs <80 bar) nor other modes of CO2 transport (by ship, road or rail) are
considered. The regional representation of CO2 is activated with the config
setting ``sector: co2_network: true`` but is deactivated by default. The
global limit for CO2 sequestration now applies to the sum of all CO2 stores
via an ``extra_functionality`` constraint.
* The myopic option can now be used together with different clustering for the
generators and the network. The existing renewable capacities are split evenly
among the regions in every country [`#144 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/144>`_].
* Add optional function to use ``geopy`` to locate entries of the Hotmaps
database of industrial sites with missing location based on city and country,
which reduces missing entries by half. It can be activated by setting
``industry: hotmaps_locate_missing: true``, takes a few minutes longer, and
should only be used if spatial resolution is coarser than city level.
**Performance and Structure**
* Extended use of ``multiprocessing`` for much better performance * Extended use of ``multiprocessing`` for much better performance
(from up to 20 minutes to less than one minute). (from up to 20 minutes to less than one minute).
* Compatibility with ``atlite>=0.2``. Older versions of ``atlite`` will no longer work.
* Handle most input files (or base directories) via ``snakemake.input``. * Handle most input files (or base directories) via ``snakemake.input``.
* Use of ``mock_snakemake`` from PyPSA-Eur. * Use of ``mock_snakemake`` from PyPSA-Eur.
* Update ``solve_network`` rule to match implementation in PyPSA-Eur by using ``n.ilopf()`` and remove outdated code using ``pyomo``.
Allows the new setting to skip iterated impedance updates with ``solving: options: skip_iterations: true``. * Update ``solve_network`` rule to match implementation in PyPSA-Eur by using
``n.ilopf()`` and remove outdated code using ``pyomo``.
Allows the new setting to skip iterated impedance updates with ``solving:
options: skip_iterations: true``.
* The component attributes that are to be overridden are now stored in the folder * The component attributes that are to be overridden are now stored in the folder
``data/override_component_attrs`` analogous to ``pypsa/component_attrs``. ``data/override_component_attrs`` analogous to ``pypsa/component_attrs``.
This reduces verbosity and also allows circumventing the ``n.madd()`` hack This reduces verbosity and also allows circumventing the ``n.madd()`` hack
for individual components with non-default attributes. for individual components with non-default attributes.
This data is also tracked in the Snakefile. This data is also tracked in the Snakefile.
A function ``helper.override_component_attrs`` was added that loads this data A function ``helper.override_component_attrs`` was added that loads this data
and can pass the overridden component attributes into ``pypsa.Network()``: and can pass the overridden component attributes into ``pypsa.Network()``.
>>> from helper import override_component_attrs
>>> overrides = override_component_attrs(snakemake.input.overrides)
>>> n = pypsa.Network("mynetwork.nc", override_component_attrs=overrides)
* Add various parameters to ``config.default.yaml`` which were previously hardcoded inside the scripts * Add various parameters to ``config.default.yaml`` which were previously hardcoded inside the scripts
(e.g. energy reference years, BEV settings, solar thermal collector models, geomap colours). (e.g. energy reference years, BEV settings, solar thermal collector models, geomap colours).
* Removed stale industry demand rules ``build_industrial_energy_demand_per_country`` * Removed stale industry demand rules ``build_industrial_energy_demand_per_country``
and ``build_industrial_demand``. These are superseded with more regionally resolved rules. and ``build_industrial_demand``. These are superseded with more regionally resolved rules.
* Use simpler and shorter ``gdf.sjoin()`` function to allocate industrial sites * Use simpler and shorter ``gdf.sjoin()`` function to allocate industrial sites
from the Hotmaps database to onshore regions. from the Hotmaps database to onshore regions.
This change also fixes a bug: This change also fixes a bug:
The previous version allocated sites to the closest bus, The previous version allocated sites to the closest bus,
but at country borders (where Voronoi cells are distorted by the borders), but at country borders (where Voronoi cells are distorted by the borders),
this had resulted in e.g. a Spanish site close to the French border this had resulted in e.g. a Spanish site close to the French border
being wrongly allocated to the French bus if the bus center was closer. being wrongly allocated to the French bus if the bus center was closer.
* Bugfix: Corrected calculation of "gas for industry" carbon capture efficiency.
* Retrofitting rule is now only triggered if endogeneously optimised. * Retrofitting rule is now only triggered if endogeneously optimised.
* Show progress in build rules with ``tqdm`` progress bars. * Show progress in build rules with ``tqdm`` progress bars.
* Reduced verbosity of ``Snakefile`` through directory prefixes. * Reduced verbosity of ``Snakefile`` through directory prefixes.
* Improve legibility of ``config.default.yaml`` and remove unused options. * Improve legibility of ``config.default.yaml`` and remove unused options.
* Add optional function to use ``geopy`` to locate entries of the Hotmaps database of industrial sites
with missing location based on city and country, which reduces missing entries by half. It can be
activated by setting ``industry: hotmaps_locate_missing: true``, takes a few minutes longer,
and should only be used if spatial resolution is coarser than city level.
* Use the country-specific time zone mappings from ``pytz`` rather than a manual mapping. * Use the country-specific time zone mappings from ``pytz`` rather than a manual mapping.
* A function ``add_carrier_buses()`` was added to the ``prepare_network`` rule to reduce code duplication. * A function ``add_carrier_buses()`` was added to the ``prepare_network`` rule to reduce code duplication.
* In the ``prepare_network`` rule the cost and potential adjustment was moved into an * In the ``prepare_network`` rule the cost and potential adjustment was moved into an
own function ``maybe_adjust_costs_and_potentials()``. own function ``maybe_adjust_costs_and_potentials()``.
* Use ``matplotlibrc`` to set the default plotting style and backend``.
* Use ``matplotlibrc`` to set the default plotting style and backend.
* Added benchmark files for each rule. * Added benchmark files for each rule.
* Implements changes to ``n.snapshot_weightings`` in upcoming PyPSA version (cf. `PyPSA/#227 <https://github.com/PyPSA/PyPSA/pull/227>`_).
* New dependencies: ``tqdm``, ``atlite>=0.2.4``, ``pytz`` and ``geopy`` (optional).
These are included in the environment specifications of PyPSA-Eur.
* Consistent use of ``__main__`` block and further unspecific code cleaning. * Consistent use of ``__main__`` block and further unspecific code cleaning.
* Distinguish costs for home battery storage and inverter from utility-scale battery costs.
* Add option to regionally resolve CO2 storage and add CO2 pipeline transport because geological storage potential, * Updated data bundle and moved data bundle to zenodo.org (`10.5281/zenodo.5546517 <https://doi.org/10.5281/zenodo.5546517>`_).
CO2 utilisation sites and CO2 capture sites may be separated.
The CO2 network is built from zero based on the topology of the electricity grid (greenfield).
Pipelines are assumed to be bidirectional and lossless. **Bugfixes and Compatibility**
Furthermore, neither retrofitting of natural gas pipelines (required pressures are too high, 80-160 bar vs <80 bar)
nor other modes of CO2 transport (by ship, road or rail) are considered. * Compatibility with ``atlite>=0.2``. Older versions of ``atlite`` will no longer work.
The regional representation of CO2 is activated with the config setting ``sector: co2_network: true`` but is deactivated by default.
The global limit for CO2 sequestration now applies to the sum of all CO2 stores via an ``extra_functionality`` constraint. * Corrected calculation of "gas for industry" carbon capture efficiency.
* Added option for hydrogen liquefaction costs for hydrogen demand in shipping.
This introduces a new ``H2 liquid`` bus at each location. * Implemented changes to ``n.snapshot_weightings`` in PyPSA v0.18.0.
It is activated via ``sector: shipping_hydrogen_liquefaction: true``.
* The share of shipping transformed into hydrogen fuel cell can be now defined for different years in the ``config.yaml`` file. The carbon emission from the remaining share is treated as a negative load on the atmospheric carbon dioxide bus, just like aviation and land transport emissions.
* The transformation of the Steel and Aluminium production can be now defined for different years in the ``config.yaml`` file.
* Include the option to alter the maximum energy capacity of a store via the ``carrier+factor`` in the ``{sector_opts}`` wildcard. This can be useful for sensitivity analyses. Example: ``co2 stored+e2`` multiplies the ``e_nom_max`` by factor 2. In this example, ``e_nom_max`` represents the CO2 sequestration potential in Europe.
* Add option to regionally disaggregate biomass potential to individual nodes
(currently given per country, then distributed by population density within)
and allow the transport of solid biomass.
The transport costs are determined based on the `JRC-EU-Times Bioenergy report <http://dx.doi.org/10.2790/01017>`_
in the new optional rule ``build_biomass_transport_costs``.
Biomass transport can be activated with the setting ``sector: biomass_transport: true``.
* Use `JRC ENSPRESO database <https://data.jrc.ec.europa.eu/dataset/74ed5a04-7d74-4807-9eab-b94774309d9f>`_ to
spatially disaggregate biomass potentials to PyPSA-Eur regions based on overlaps with NUTS2 regions from ENSPRESO
(proportional to area) (`#151 <https://github.com/PyPSA/pypsa-eur-sec/pull/151>`_).
* Compatibility with ``xarray`` version 0.19. * Compatibility with ``xarray`` version 0.19.
* Added option to include emissions and energy demands of agriculture, forestry and fishing sector via the letter ``A`` in the ``{sector_opts}`` wildcard.
Demands are separated into electricity, heat and oil for machinery. * New dependencies: ``tqdm``, ``atlite>=0.2.4``, ``pytz`` and ``geopy`` (optional).
Fuel-switching for machinery from oil to electricity can be set exogenously in the ``config.yaml`` These are included in the environment specifications of PyPSA-Eur v0.3.0.
`#147 <https://github.com/PyPSA/PyPSA/pull/147>`_.
* Separate basic chemicals into HVC, chlorine, methanol and ammonia [`#166 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/166>`_]. Many thanks to all who contributed to this release!
* Add option to specify reuse, primary production, and mechanical and chemical recycling fraction of platics [`#166 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/166>`_].
* Include today's district heating shares in myopic optimisation and add option to specify exogenous path for district heating share increase under ``sector: district_heating:`` [`#149 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/149>`_].
* The myopic option can now be used together with different clustering for the generators and the network. The existing renewable capacities are split evenly among the regions in every country [`#144 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/144>`_].
PyPSA-Eur-Sec 0.5.0 (21st May 2021) PyPSA-Eur-Sec 0.5.0 (21st May 2021)
=================================== ===================================
@ -274,4 +373,4 @@ To make a new release of the data bundle, make an archive of the files in ``data
.. code:: bash .. code:: bash
data % tar pczf pypsa-eur-sec-data-bundle-YYMMDD.tar.gz eea/UNFCCC_v23.csv switzerland-sfoe biomass eurostat-energy_balances-* jrc-idees-2015 emobility urban_percent.csv timezone_mappings.csv heat_load_profile_DK_AdamJensen.csv WindWaveWEC_GLTB.xlsx myb1-2017-nitro.xls Industrial_Database.csv retro/tabula-calculator-calcsetbuilding.csv data % tar pczf pypsa-eur-sec-data-bundle.tar.gz eea/UNFCCC_v23.csv switzerland-sfoe biomass eurostat-energy_balances-* jrc-idees-2015 emobility WindWaveWEC_GLTB.xlsx myb1-2017-nitro.xls Industrial_Database.csv retro/tabula-calculator-calcsetbuilding.csv nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson

2
scripts/prepare_sector_network.py
View File

@ -1697,7 +1697,7 @@ def create_nodes_for_heat_sector():
axis=1).max(axis=1) axis=1).max(axis=1)
# difference of max potential and today's share of district heating # difference of max potential and today's share of district heating
diff = (urban_fraction * central_fraction) - dist_fraction_node diff = (urban_fraction * central_fraction) - dist_fraction_node
progress = get(options["district_heating"]["potential"], investment_year) progress = get(options["district_heating"]["progress"], investment_year)
dist_fraction_node += diff * progress dist_fraction_node += diff * progress
print( print(
"The current district heating share compared to the maximum", "The current district heating share compared to the maximum",