Merge pull request #149 from PyPSA/dh-share
Include today's district heating share for myopic optimisation
This commit is contained in:
Fabian Neumann
GitHub
commit
fb601cc051
@ -159,6 +159,7 @@ rule build_energy_totals:
|
||||
co2="data/eea/UNFCCC_v23.csv",
|
||||
swiss="data/switzerland-sfoe/switzerland-new_format.csv",
|
||||
idees="data/jrc-idees-2015",
|
||||
district_heat_share='data/district_heat_share.csv',
|
||||
eurostat=input_eurostat
|
||||
output:
|
||||
energy_name='resources/energy_totals.csv',
|
||||
|
||||
@ -141,8 +141,16 @@ existing_capacities:
|
||||
|
||||
|
||||
sector:
|
||||
central: true
|
||||
central_fraction: 0.6
|
||||
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
|
||||
# progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
|
||||
progress:
|
||||
2020: 0.0
|
||||
2030: 0.3
|
||||
2040: 0.6
|
||||
2050: 1.0
|
||||
district_heating_loss: 0.15
|
||||
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
|
||||
transport_heating_deadband_upper: 20.
|
||||
@ -151,7 +159,6 @@ sector:
|
||||
ICE_upper_degree_factor: 1.6
|
||||
EV_lower_degree_factor: 0.98
|
||||
EV_upper_degree_factor: 0.63
|
||||
district_heating_loss: 0.15
|
||||
bev_dsm: true #turns on EV battery
|
||||
bev_availability: 0.5 #How many cars do smart charging
|
||||
bev_energy: 0.05 #average battery size in MWh
|
||||
|
||||
34
data/district_heat_share.csv
Normal file
34
data/district_heat_share.csv
Normal file
@ -0,0 +1,34 @@
|
||||
country,share to satisfy heat demand (residential) in percent,capacity[MWth]
|
||||
AT,14,11200
|
||||
BG,16,6162
|
||||
BA,8,
|
||||
HR,6.3,2221
|
||||
CZ,40,
|
||||
DK,65,
|
||||
FI,38,23390
|
||||
FR,5,
|
||||
DE,13.8,
|
||||
HU,7.92875588637399,8549
|
||||
IS,90,8079000
|
||||
IE,0.8,
|
||||
IT,3,8727
|
||||
LV,73,2254
|
||||
LT,56,
|
||||
MK,23.7745607009008,636
|
||||
NO,4,3400
|
||||
PL,42,54912
|
||||
PT,0.070754716981132,34
|
||||
RS,25,5821
|
||||
SI,8.86,1739
|
||||
ES,0.251589260787732,1273
|
||||
SE,50.4,
|
||||
UK,2,
|
||||
BY,70,
|
||||
EE,52,5406
|
||||
KO,3,207
|
||||
RO,23,9962
|
||||
SK,54,15000
|
||||
NL,4,9800
|
||||
CH,4,2792
|
||||
AL,0,
|
||||
ME,0,
|
||||
|
@ -25,3 +25,6 @@ Comparative level investment,comparative_level_investment.csv,Eurostat,https://e
|
||||
Electricity taxes,electricity_taxes_eu.csv,Eurostat,https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nrg_pc_204&lang=en
|
||||
Building topologies and corresponding standard values,tabula-calculator-calcsetbuilding.csv,unknown,https://episcope.eu/fileadmin/tabula/public/calc/tabula-calculator.xlsx
|
||||
Retrofitting thermal envelope costs for Germany,retro_cost_germany.csv,unkown,https://www.iwu.de/forschung/handlungslogiken/kosten-energierelevanter-bau-und-anlagenteile-bei-modernisierung/
|
||||
District heating most countries,jrc-idees-2015/,CC BY 4.0,https://ec.europa.eu/jrc/en/potencia/jrc-idees,,
|
||||
District heating missing countries,district_heat_share.csv,unkown,https://www.euroheat.org/knowledge-hub/country-profiles,,
|
||||
|
||||
|
||||
|
Can't render this file because it has a wrong number of fields in line 28.
|
@ -88,6 +88,7 @@ Future release
|
||||
* Compatibility with ``xarray`` version 0.19.
|
||||
* Separate basic chemicals into HVC, 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 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>`_].
|
||||
|
||||
PyPSA-Eur-Sec 0.5.0 (21st May 2021)
|
||||
===================================
|
||||
|
||||
@ -212,6 +212,12 @@ def idees_per_country(ct, year):
|
||||
assert df.index[47] == "Electricity"
|
||||
ct_totals["electricity residential"] = df[47]
|
||||
|
||||
assert df.index[46] == "Derived heat"
|
||||
ct_totals["Derived heat residential"] = df[46]
|
||||
|
||||
assert df.index[50] == 'Thermal uses'
|
||||
ct_totals["thermal uses residential"] = df[50]
|
||||
|
||||
# services
|
||||
|
||||
df = pd.read_excel(fn_services, "SER_hh_fec", index_col=0)[year]
|
||||
@ -239,6 +245,12 @@ def idees_per_country(ct, year):
|
||||
assert df.index[50] == "Electricity"
|
||||
ct_totals["electricity services"] = df[50]
|
||||
|
||||
assert df.index[49] == "Derived heat"
|
||||
ct_totals["derived heat services"] = df[49]
|
||||
|
||||
assert df.index[53] == 'Thermal uses'
|
||||
ct_totals["thermal uses services"] = df[53]
|
||||
|
||||
# transport
|
||||
|
||||
df = pd.read_excel(fn_transport, "TrRoad_ene", index_col=0)[year]
|
||||
@ -342,6 +354,7 @@ def build_idees(countries, year):
|
||||
with mp.Pool(processes=nprocesses) as pool:
|
||||
totals_list = list(tqdm(pool.imap(func, countries), **tqdm_kwargs))
|
||||
|
||||
|
||||
totals = pd.concat(totals_list, axis=1)
|
||||
|
||||
# convert ktoe to TWh
|
||||
@ -351,6 +364,13 @@ def build_idees(countries, year):
|
||||
# convert TWh/100km to kWh/km
|
||||
totals.loc["passenger car efficiency"] *= 10
|
||||
|
||||
# district heating share
|
||||
district_heat = totals.loc[["derived heat residential",
|
||||
"derived heat services"]].sum()
|
||||
total_heat = totals.loc[["thermal uses residential",
|
||||
"thermal uses services"]].sum()
|
||||
totals.loc["district heat share"] = district_heat.div(total_heat)
|
||||
|
||||
return totals.T
|
||||
|
||||
|
||||
@ -502,6 +522,14 @@ def build_energy_totals(countries, eurostat, swiss, idees):
|
||||
ratio = df.at["BA", "total residential"] / df.at["RS", "total residential"]
|
||||
df.loc['BA', missing] = ratio * df.loc["RS", missing]
|
||||
|
||||
# Missing district heating share
|
||||
dh_share = pd.read_csv(snakemake.input.district_heat_share,
|
||||
index_col=0, usecols=[0, 1])
|
||||
# make conservative assumption and take minimum from both data sets
|
||||
df["district heat share"] = (pd.concat([df["district heat share"],
|
||||
dh_share.reindex(index=df.index)/100],
|
||||
axis=1).min(axis=1))
|
||||
|
||||
return df
|
||||
|
||||
|
||||
|
||||
@ -489,8 +489,7 @@ def add_dac(n, costs):
|
||||
efficiency3 = -(costs.at['direct air capture', 'heat-input'] - costs.at['direct air capture', 'compression-heat-output'])
|
||||
|
||||
n.madd("Link",
|
||||
locations,
|
||||
suffix=" DAC",
|
||||
heat_buses.str.replace(" heat", " DAC"),
|
||||
bus0="co2 atmosphere",
|
||||
bus1=spatial.co2.df.loc[locations, "nodes"].values,
|
||||
bus2=locations.values,
|
||||
@ -636,6 +635,8 @@ def prepare_data(n):
|
||||
|
||||
nodal_energy_totals = energy_totals.loc[pop_layout.ct].fillna(0.)
|
||||
nodal_energy_totals.index = pop_layout.index
|
||||
# district heat share not weighted by population
|
||||
district_heat_share = nodal_energy_totals["district heat share"].round(2)
|
||||
nodal_energy_totals = nodal_energy_totals.multiply(pop_layout.fraction, axis=0)
|
||||
|
||||
# copy forward the daily average heat demand into each hour, so it can be multipled by the intraday profile
|
||||
@ -758,7 +759,7 @@ def prepare_data(n):
|
||||
)
|
||||
|
||||
|
||||
return nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data
|
||||
return nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data, district_heat_share
|
||||
|
||||
|
||||
# TODO checkout PyPSA-Eur script
|
||||
@ -1336,12 +1337,11 @@ def add_heat(n, costs):
|
||||
|
||||
sectors = ["residential", "services"]
|
||||
|
||||
nodes = create_nodes_for_heat_sector()
|
||||
|
||||
nodes, dist_fraction, urban_fraction = create_nodes_for_heat_sector()
|
||||
|
||||
#NB: must add costs of central heating afterwards (EUR 400 / kWpeak, 50a, 1% FOM from Fraunhofer ISE)
|
||||
|
||||
urban_fraction = options['central_fraction'] * pop_layout["urban"] / pop_layout[["urban", "rural"]].sum(axis=1)
|
||||
|
||||
# exogenously reduce space heat demand
|
||||
if options["reduce_space_heat_exogenously"]:
|
||||
dE = get(options["reduce_space_heat_exogenously_factor"], investment_year)
|
||||
@ -1372,15 +1372,22 @@ def add_heat(n, costs):
|
||||
## Add heat load
|
||||
|
||||
for sector in sectors:
|
||||
# heat demand weighting
|
||||
if "rural" in name:
|
||||
factor = 1 - urban_fraction[nodes[name]]
|
||||
elif "urban" in name:
|
||||
factor = urban_fraction[nodes[name]]
|
||||
elif "urban central" in name:
|
||||
factor = dist_fraction[nodes[name]]
|
||||
elif "urban decentral" in name:
|
||||
factor = urban_fraction[nodes[name]] - \
|
||||
dist_fraction[nodes[name]]
|
||||
else:
|
||||
raise NotImplementedError(f" {name} not in " f"heat systems: {heat_systems}")
|
||||
|
||||
if sector in name:
|
||||
heat_load = heat_demand[[sector + " water",sector + " space"]].groupby(level=1,axis=1).sum()[nodes[name]].multiply(factor)
|
||||
|
||||
if name == "urban central":
|
||||
heat_load = heat_demand.groupby(level=1,axis=1).sum()[nodes[name]].multiply(urban_fraction[nodes[name]] * (1 + options['district_heating_loss']))
|
||||
heat_load = heat_demand.groupby(level=1,axis=1).sum()[nodes[name]].multiply(factor * (1 + options['district_heating']['district_heating_loss']))
|
||||
|
||||
n.madd("Load",
|
||||
nodes[name],
|
||||
@ -1661,23 +1668,39 @@ def create_nodes_for_heat_sector():
|
||||
# urban are areas with high heating density
|
||||
# urban can be split into district heating (central) and individual heating (decentral)
|
||||
|
||||
ct_urban = pop_layout.urban.groupby(pop_layout.ct).sum()
|
||||
# distribution of urban population within a country
|
||||
pop_layout["urban_ct_fraction"] = pop_layout.urban / pop_layout.ct.map(ct_urban.get)
|
||||
|
||||
sectors = ["residential", "services"]
|
||||
|
||||
nodes = {}
|
||||
urban_fraction = pop_layout.urban / pop_layout[["rural", "urban"]].sum(axis=1)
|
||||
|
||||
for sector in sectors:
|
||||
nodes[sector + " rural"] = pop_layout.index
|
||||
|
||||
if options["central"]:
|
||||
# TODO: this looks hardcoded, move to config
|
||||
urban_decentral_ct = pd.Index(["ES", "GR", "PT", "IT", "BG"])
|
||||
nodes[sector + " urban decentral"] = pop_layout.index[pop_layout.ct.isin(urban_decentral_ct)]
|
||||
else:
|
||||
nodes[sector + " urban decentral"] = pop_layout.index
|
||||
|
||||
# for central nodes, residential and services are aggregated
|
||||
nodes["urban central"] = pop_layout.index.symmetric_difference(nodes["residential urban decentral"])
|
||||
# maximum potential of urban demand covered by district heating
|
||||
central_fraction = options['district_heating']["potential"]
|
||||
# district heating share at each node
|
||||
dist_fraction_node = district_heat_share * pop_layout["urban_ct_fraction"] / pop_layout["fraction"]
|
||||
nodes["urban central"] = dist_fraction_node.index
|
||||
# if district heating share larger than urban fraction -> set urban
|
||||
# fraction to district heating share
|
||||
urban_fraction = pd.concat([urban_fraction, dist_fraction_node],
|
||||
axis=1).max(axis=1)
|
||||
# difference of max potential and today's share of district heating
|
||||
diff = (urban_fraction * central_fraction) - dist_fraction_node
|
||||
progress = get(options["district_heating"]["potential"], investment_year)
|
||||
dist_fraction_node += diff * progress
|
||||
print(
|
||||
"The current district heating share compared to the maximum",
|
||||
f"possible is increased by a progress factor of\n{progress}",
|
||||
f"resulting in a district heating share of\n{dist_fraction_node}"
|
||||
)
|
||||
|
||||
return nodes
|
||||
return nodes, dist_fraction_node, urban_fraction
|
||||
|
||||
|
||||
def add_biomass(n, costs):
|
||||
@ -1993,7 +2016,7 @@ def add_industry(n, costs):
|
||||
|
||||
if options["oil_boilers"]:
|
||||
|
||||
nodes_heat = create_nodes_for_heat_sector()
|
||||
nodes_heat = create_nodes_for_heat_sector()[0]
|
||||
|
||||
for name in ["residential rural", "services rural", "residential urban decentral", "services urban decentral"]:
|
||||
|
||||
@ -2191,18 +2214,18 @@ def limit_individual_line_extension(n, maxext):
|
||||
hvdc = n.links.index[n.links.carrier == 'DC']
|
||||
n.links.loc[hvdc, 'p_nom_max'] = n.links.loc[hvdc, 'p_nom'] + maxext
|
||||
|
||||
|
||||
#%%
|
||||
if __name__ == "__main__":
|
||||
if 'snakemake' not in globals():
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake(
|
||||
'prepare_sector_network',
|
||||
simpl='',
|
||||
clusters="45",
|
||||
opts="",
|
||||
clusters="37",
|
||||
lv=1.0,
|
||||
opts='',
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
|
||||
planning_horizons="2030",
|
||||
planning_horizons="2020",
|
||||
)
|
||||
|
||||
logging.basicConfig(level=snakemake.config['logging_level'])
|
||||
@ -2254,10 +2277,10 @@ if __name__ == "__main__":
|
||||
if o == "biomasstransport":
|
||||
options["biomass_transport"] = True
|
||||
|
||||
nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data = prepare_data(n)
|
||||
nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data, district_heat_share = prepare_data(n)
|
||||
|
||||
if "nodistrict" in opts:
|
||||
options["central"] = False
|
||||
options["district_heating"]["progress"] = 0.0
|
||||
|
||||
if "T" in opts:
|
||||
add_land_transport(n, costs)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user