Merge branch 'master' into post-merge-param
This commit is contained in:
commit
28d39680c6
@ -67,7 +67,7 @@ repos:
|
||||
|
||||
# Do YAML formatting (before the linter checks it for misses)
|
||||
- repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks
|
||||
rev: v2.8.0
|
||||
rev: v2.9.0
|
||||
hooks:
|
||||
- id: pretty-format-yaml
|
||||
args: [--autofix, --indent, "2", --preserve-quotes]
|
||||
|
@ -623,9 +623,9 @@ clustering:
|
||||
solving:
|
||||
#tmpdir: "path/to/tmp"
|
||||
options:
|
||||
formulation: kirchhoff
|
||||
clip_p_max_pu: 1.e-2
|
||||
load_shedding: false
|
||||
transmission_losses: 0
|
||||
noisy_costs: true
|
||||
skip_iterations: true
|
||||
track_iterations: false
|
||||
|
@ -1,7 +1,7 @@
|
||||
,Unit,Values,Description
|
||||
options,,,
|
||||
-- formulation,--,"Any of {'angles', 'kirchhoff', 'cycles', 'ptdf'}","Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is 'kirchhoff'. Explained in `this article <https://arxiv.org/abs/1704.01881>`_."
|
||||
-- load_shedding,bool/float,"{'true','false', float}","Add generators with very high marginal cost to simulate load shedding and avoid problem infeasibilities. If load shedding is a float, it denotes the marginal cost in EUR/kWh."
|
||||
-- transmission_losses,int,"[0-9]","Add piecewise linear approximation of transmission losses based on n tangents. Defaults to 0, which means losses are ignored."
|
||||
-- noisy_costs,bool,"{'true','false'}","Add random noise to marginal cost of generators by :math:`\mathcal{U}(0.009,0,011)` and capital cost of lines and links by :math:`\mathcal{U}(0.09,0,11)`."
|
||||
-- min_iterations,--,int,"Minimum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run."
|
||||
-- max_iterations,--,int,"Maximum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run."
|
||||
|
|
@ -23,6 +23,12 @@ Upcoming Release
|
||||
hydrogen fuel cell. Add switches for both re-electrification options under
|
||||
``sector: hydrogen_turbine:`` and ``sector: hydrogen_fuel_cell:``.
|
||||
|
||||
* Remove ``vresutils`` dependency.
|
||||
|
||||
* Add option to include a piecewise linear approximation of transmission losses,
|
||||
e.g. by setting ``solving: options: transmission_losses: 2`` for an
|
||||
approximation with two tangents.
|
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|
||||
PyPSA-Eur 0.8.0 (18th March 2023)
|
||||
=================================
|
||||
|
||||
|
@ -9,7 +9,6 @@ sphinxcontrib-bibtex
|
||||
myst-parser # recommark is deprecated, https://stackoverflow.com/a/71660856/13573820
|
||||
|
||||
pypsa
|
||||
vresutils>=0.3.1
|
||||
powerplantmatching>=0.5.5
|
||||
atlite>=0.2.9
|
||||
dask[distributed]
|
||||
|
@ -133,12 +133,12 @@ The coefficient of performance (COP) of air- and ground-sourced heat pumps depen
|
||||
For the sink water temperature Tsink we assume 55 °C [`Config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L207>`_ file]. For the time- and location-dependent source temperatures Tsource, we rely on the `ERA5 <https://doi.org/10.1002/qj.3803>`_ reanalysis weather data. The temperature differences are converted into COP time series using results from a regression analysis performed in the study by `Stafell et al. <https://pubs.rsc.org/en/content/articlelanding/2012/EE/c2ee22653g>`_. For air-sourced heat pumps (ASHP), we use the function:
|
||||
|
||||
.. math::
|
||||
COP (\Delta T) = 6.81 + 0.121\Delta T + 0.000630\Delta T^2
|
||||
COP (\Delta T) = 6.81 - 0.121\Delta T + 0.000630\Delta T^2
|
||||
|
||||
for ground-sourced heat pumps (GSHP), we use the function:
|
||||
|
||||
.. math::
|
||||
COP(\Delta T) = 8.77 + 0.150\Delta T + 0.000734\Delta T^2
|
||||
COP(\Delta T) = 8.77 - 0.150\Delta T + 0.000734\Delta T^2
|
||||
|
||||
**Resistive heaters**
|
||||
|
||||
|
@ -9,6 +9,6 @@ Support
|
||||
|
||||
* In case of code-related **questions**, please post on `stack overflow <https://stackoverflow.com/questions/tagged/pypsa>`_.
|
||||
* For non-programming related and more general questions please refer to the `mailing list <https://groups.google.com/group/pypsa>`_.
|
||||
* To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the [discord server](https://discord.gg/JTdvaEBb).
|
||||
* To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the `discord server <https://discord.gg/AnuJBk23FU>`_.
|
||||
* For **bugs and feature requests**, please use the `issue tracker <https://github.com/PyPSA/pypsa-eur/issues>`_.
|
||||
* We strongly welcome anyone interested in providing **contributions** to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on `Github <https://github.com/PyPSA/PyPSA>`_. For further information on how to contribute, please refer to :ref:`contributing`.
|
||||
|
@ -226,7 +226,7 @@ dependencies:
|
||||
- nspr=4.35
|
||||
- nss=3.88
|
||||
- numexpr=2.8.3
|
||||
- numpy=1.23.5
|
||||
- numpy=1.24
|
||||
- openjdk=17.0.3
|
||||
- openjpeg=2.5.0
|
||||
- openpyxl=3.1.0
|
||||
@ -378,4 +378,3 @@ dependencies:
|
||||
- highspy==1.5.0.dev0
|
||||
- pybind11==2.10.3
|
||||
- tsam==2.2.2
|
||||
- vresutils==0.3.1
|
||||
|
@ -10,7 +10,7 @@ dependencies:
|
||||
- python>=3.8
|
||||
- pip
|
||||
|
||||
- pypsa>=0.21.3
|
||||
- pypsa>=0.23
|
||||
- atlite>=0.2.9
|
||||
- dask
|
||||
|
||||
@ -25,7 +25,7 @@ dependencies:
|
||||
- pytables
|
||||
- lxml
|
||||
- powerplantmatching>=0.5.5
|
||||
- numpy<1.24
|
||||
- numpy
|
||||
- pandas>=1.4
|
||||
- geopandas>=0.11.0
|
||||
- xarray
|
||||
@ -55,5 +55,4 @@ dependencies:
|
||||
- rasterio!=1.2.10
|
||||
|
||||
- pip:
|
||||
- vresutils>=0.3.1
|
||||
- tsam>=1.1.0
|
||||
|
@ -16,8 +16,6 @@ rule solve_network:
|
||||
),
|
||||
python=LOGS
|
||||
+ "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_python.log",
|
||||
memory=LOGS
|
||||
+ "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_memory.log",
|
||||
benchmark:
|
||||
BENCHMARKS + "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
|
||||
threads: 4
|
||||
@ -45,8 +43,6 @@ rule solve_operations_network:
|
||||
),
|
||||
python=LOGS
|
||||
+ "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_python.log",
|
||||
memory=LOGS
|
||||
+ "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_memory.log",
|
||||
benchmark:
|
||||
(
|
||||
BENCHMARKS
|
||||
|
@ -100,8 +100,6 @@ rule solve_sector_network_myopic:
|
||||
+ "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_solver.log",
|
||||
python=LOGS
|
||||
+ "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log",
|
||||
memory=LOGS
|
||||
+ "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log",
|
||||
threads: 4
|
||||
resources:
|
||||
mem_mb=config["solving"]["mem"],
|
||||
|
@ -23,8 +23,6 @@ rule solve_sector_network:
|
||||
+ "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_solver.log",
|
||||
python=LOGS
|
||||
+ "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log",
|
||||
memory=LOGS
|
||||
+ "elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log",
|
||||
threads: config["solving"]["solver"].get("threads", 4)
|
||||
resources:
|
||||
mem_mb=config["solving"]["mem"],
|
||||
|
@ -85,16 +85,18 @@ It further adds extendable ``generators`` with **zero** capacity for
|
||||
"""
|
||||
|
||||
import logging
|
||||
from itertools import product
|
||||
|
||||
import geopandas as gpd
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import powerplantmatching as pm
|
||||
import pypsa
|
||||
import scipy.sparse as sparse
|
||||
import xarray as xr
|
||||
from _helpers import configure_logging, update_p_nom_max
|
||||
from powerplantmatching.export import map_country_bus
|
||||
from vresutils import transfer as vtransfer
|
||||
from shapely.prepared import prep
|
||||
|
||||
idx = pd.IndexSlice
|
||||
|
||||
@ -216,6 +218,21 @@ def load_powerplants(ppl_fn):
|
||||
)
|
||||
|
||||
|
||||
def shapes_to_shapes(orig, dest):
|
||||
"""
|
||||
Adopted from vresutils.transfer.Shapes2Shapes()
|
||||
"""
|
||||
orig_prepped = list(map(prep, orig))
|
||||
transfer = sparse.lil_matrix((len(dest), len(orig)), dtype=float)
|
||||
|
||||
for i, j in product(range(len(dest)), range(len(orig))):
|
||||
if orig_prepped[j].intersects(dest[i]):
|
||||
area = orig[j].intersection(dest[i]).area
|
||||
transfer[i, j] = area / dest[i].area
|
||||
|
||||
return transfer
|
||||
|
||||
|
||||
def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
|
||||
substation_lv_i = n.buses.index[n.buses["substation_lv"]]
|
||||
regions = gpd.read_file(regions).set_index("name").reindex(substation_lv_i)
|
||||
@ -232,9 +249,7 @@ def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
|
||||
return pd.DataFrame({group.index[0]: l})
|
||||
else:
|
||||
nuts3_cntry = nuts3.loc[nuts3.country == cntry]
|
||||
transfer = vtransfer.Shapes2Shapes(
|
||||
group, nuts3_cntry.geometry, normed=False
|
||||
).T.tocsr()
|
||||
transfer = shapes_to_shapes(group, nuts3_cntry.geometry).T.tocsr()
|
||||
gdp_n = pd.Series(
|
||||
transfer.dot(nuts3_cntry["gdp"].fillna(1.0).values), index=group.index
|
||||
)
|
||||
@ -403,7 +418,9 @@ def attach_conventional_generators(
|
||||
if f"conventional_{carrier}_{attr}" in conventional_inputs:
|
||||
# Values affecting generators of technology k country-specific
|
||||
# First map generator buses to countries; then map countries to p_max_pu
|
||||
values = pd.read_csv(values, index_col=0).iloc[:, 0]
|
||||
values = pd.read_csv(
|
||||
snakemake.input[f"conventional_{carrier}_{attr}"], index_col=0
|
||||
).iloc[:, 0]
|
||||
bus_values = n.buses.country.map(values)
|
||||
n.generators[attr].update(
|
||||
n.generators.loc[idx].bus.map(bus_values).dropna()
|
||||
|
@ -234,6 +234,7 @@ def nuts3(country_shapes, nuts3, nuts3pop, nuts3gdp, ch_cantons, ch_popgdp):
|
||||
manual = gpd.GeoDataFrame(
|
||||
[["BA1", "BA", 3871.0], ["RS1", "RS", 7210.0], ["AL1", "AL", 2893.0]],
|
||||
columns=["NUTS_ID", "country", "pop"],
|
||||
geometry=gpd.GeoSeries(),
|
||||
)
|
||||
manual["geometry"] = manual["country"].map(country_shapes)
|
||||
manual = manual.dropna()
|
||||
|
@ -22,13 +22,13 @@ from _helpers import (
|
||||
override_component_attrs,
|
||||
update_config_with_sector_opts,
|
||||
)
|
||||
from add_electricity import calculate_annuity
|
||||
from build_energy_totals import build_co2_totals, build_eea_co2, build_eurostat_co2
|
||||
from networkx.algorithms import complement
|
||||
from networkx.algorithms.connectivity.edge_augmentation import k_edge_augmentation
|
||||
from pypsa.geo import haversine_pts
|
||||
from pypsa.io import import_components_from_dataframe
|
||||
from scipy.stats import beta
|
||||
from vresutils.costdata import annuity
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@ -742,7 +742,7 @@ def prepare_costs(cost_file, params, nyears):
|
||||
costs = costs.fillna(params["fill_values"])
|
||||
|
||||
def annuity_factor(v):
|
||||
return annuity(v["lifetime"], v["discount rate"]) + v["FOM"] / 100
|
||||
return calculate_annuity(v["lifetime"], v["discount rate"]) + v["FOM"] / 100
|
||||
|
||||
costs["fixed"] = [
|
||||
annuity_factor(v) * v["investment"] * nyears for i, v in costs.iterrows()
|
||||
@ -851,7 +851,7 @@ def add_wave(n, wave_cost_factor):
|
||||
capacity = pd.Series({"Attenuator": 750, "F2HB": 1000, "MultiPA": 600})
|
||||
|
||||
# in EUR/MW
|
||||
annuity_factor = annuity(25, 0.07) + 0.03
|
||||
annuity_factor = calculate_annuity(25, 0.07) + 0.03
|
||||
costs = (
|
||||
1e6
|
||||
* wave_cost_factor
|
||||
|
@ -58,9 +58,8 @@ if __name__ == "__main__":
|
||||
else:
|
||||
url = "https://zenodo.org/record/3517935/files/pypsa-eur-data-bundle.tar.xz"
|
||||
|
||||
# Save locations
|
||||
tarball_fn = Path(f"{rootpath}/bundle.tar.xz")
|
||||
to_fn = Path(f"{rootpath}/data")
|
||||
to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent
|
||||
|
||||
logger.info(f"Downloading databundle from '{url}'.")
|
||||
disable_progress = snakemake.config["run"].get("disable_progressbar", False)
|
||||
|
@ -29,7 +29,7 @@ if __name__ == "__main__":
|
||||
|
||||
# Save locations
|
||||
zip_fn = Path(f"{rootpath}/IGGIELGN.zip")
|
||||
to_fn = Path(f"{rootpath}/data/gas_network/scigrid-gas")
|
||||
to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent
|
||||
|
||||
logger.info(f"Downloading databundle from '{url}'.")
|
||||
disable_progress = snakemake.config["run"].get("disable_progressbar", False)
|
||||
|
@ -10,23 +10,25 @@ import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
import os
|
||||
import sys
|
||||
import tarfile
|
||||
from pathlib import Path
|
||||
|
||||
# Add pypsa-eur scripts to path for import of _helpers
|
||||
sys.path.insert(0, os.getcwd() + "/../pypsa-eur/scripts")
|
||||
|
||||
from _helpers import configure_logging, progress_retrieve
|
||||
|
||||
if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
snakemake = mock_snakemake("retrieve_databundle")
|
||||
rootpath = ".."
|
||||
else:
|
||||
rootpath = "."
|
||||
configure_logging(snakemake)
|
||||
|
||||
url = "https://zenodo.org/record/5824485/files/pypsa-eur-sec-data-bundle.tar.gz"
|
||||
|
||||
tarball_fn = Path("sector-bundle.tar.gz")
|
||||
to_fn = Path("data")
|
||||
tarball_fn = Path(f"{rootpath}/sector-bundle.tar.gz")
|
||||
to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent
|
||||
|
||||
logger.info(f"Downloading databundle from '{url}'.")
|
||||
disable_progress = snakemake.config["run"].get("disable_progressbar", False)
|
||||
|
@ -38,7 +38,6 @@ from _helpers import (
|
||||
override_component_attrs,
|
||||
update_config_with_sector_opts,
|
||||
)
|
||||
from vresutils.benchmark import memory_logger
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
pypsa.pf.logger.setLevel(logging.WARNING)
|
||||
@ -601,6 +600,7 @@ def solve_network(n, config, opts="", **kwargs):
|
||||
track_iterations = cf_solving.get("track_iterations", False)
|
||||
min_iterations = cf_solving.get("min_iterations", 4)
|
||||
max_iterations = cf_solving.get("max_iterations", 6)
|
||||
transmission_losses = cf_solving.get("transmission_losses", 0)
|
||||
|
||||
# add to network for extra_functionality
|
||||
n.config = config
|
||||
@ -614,6 +614,7 @@ def solve_network(n, config, opts="", **kwargs):
|
||||
if skip_iterations:
|
||||
status, condition = n.optimize(
|
||||
solver_name=solver_name,
|
||||
transmission_losses=transmission_losses,
|
||||
extra_functionality=extra_functionality,
|
||||
**solver_options,
|
||||
**kwargs,
|
||||
@ -624,6 +625,7 @@ def solve_network(n, config, opts="", **kwargs):
|
||||
track_iterations=track_iterations,
|
||||
min_iterations=min_iterations,
|
||||
max_iterations=max_iterations,
|
||||
transmission_losses=transmission_losses,
|
||||
extra_functionality=extra_functionality,
|
||||
**solver_options,
|
||||
**kwargs,
|
||||
@ -667,13 +669,9 @@ if __name__ == "__main__":
|
||||
|
||||
np.random.seed(solve_opts.get("seed", 123))
|
||||
|
||||
fn = getattr(snakemake.log, "memory", None)
|
||||
with memory_logger(filename=fn, interval=30.0) as mem:
|
||||
if "overrides" in snakemake.input.keys():
|
||||
overrides = override_component_attrs(snakemake.input.overrides)
|
||||
n = pypsa.Network(
|
||||
snakemake.input.network, override_component_attrs=overrides
|
||||
)
|
||||
n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
|
||||
else:
|
||||
n = pypsa.Network(snakemake.input.network)
|
||||
|
||||
@ -685,5 +683,3 @@ if __name__ == "__main__":
|
||||
|
||||
n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
|
||||
n.export_to_netcdf(snakemake.output[0])
|
||||
|
||||
logger.info("Maximum memory usage: {}".format(mem.mem_usage))
|
||||
|
@ -17,7 +17,6 @@ from _helpers import (
|
||||
update_config_with_sector_opts,
|
||||
)
|
||||
from solve_network import prepare_network, solve_network
|
||||
from vresutils.benchmark import memory_logger
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@ -46,13 +45,9 @@ if __name__ == "__main__":
|
||||
|
||||
np.random.seed(solve_opts.get("seed", 123))
|
||||
|
||||
fn = getattr(snakemake.log, "memory", None)
|
||||
with memory_logger(filename=fn, interval=30.0) as mem:
|
||||
if "overrides" in snakemake.input:
|
||||
overrides = override_component_attrs(snakemake.input.overrides)
|
||||
n = pypsa.Network(
|
||||
snakemake.input.network, override_component_attrs=overrides
|
||||
)
|
||||
n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
|
||||
else:
|
||||
n = pypsa.Network(snakemake.input.network)
|
||||
|
||||
@ -64,5 +59,3 @@ if __name__ == "__main__":
|
||||
|
||||
n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
|
||||
n.export_to_netcdf(snakemake.output[0])
|
||||
|
||||
logger.info("Maximum memory usage: {}".format(mem.mem_usage))
|
||||
|
Loading…
Reference in New Issue
Block a user