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first step towards agriculture, forestry and fishing

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This commit is contained in:
Fabian Neumann 2021-07-06 18:32:35 +02:00
parent b2872cc6b0
commit 67ee6cb86e
3 changed files with 115 additions and 9 deletions
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3
config.default.yaml
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@ -173,6 +173,9 @@ sector:
2050: 0.85
transport_fuel_cell_efficiency: 0.5
transport_internal_combustion_efficiency: 0.3
agriculture_machinery_electric_share: 0.12 # approximately as today
agriculture_machinery_fuel_efficiency: 0.7 # for conversion of fuel oil to use
agriculture_machinery_electric_efficiency: 0.3 # for conversion of electricity to use
shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
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

42
scripts/build_energy_totals.py
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@ -117,6 +117,7 @@ to_ipcc = {
"total energy": "1 - Energy",
"industrial processes": "2 - Industrial Processes and Product Use",
"agriculture": "3 - Agriculture",
"agriculture, forestry and fishing": '1.A.4.c - Agriculture/Forestry/Fishing',
"LULUCF": "4 - Land Use, Land-Use Change and Forestry",
"waste management": "5 - Waste management",
"other": "6 - Other Sector",
@ -182,7 +183,7 @@ def idees_per_country(ct, year):
ct_idees = idees_rename.get(ct, ct)
fn_residential = f"{base_dir}/JRC-IDEES-2015_Residential_{ct_idees}.xlsx"
fn_services = f"{base_dir}/JRC-IDEES-2015_Tertiary_{ct_idees}.xlsx"
fn_tertiary = f"{base_dir}/JRC-IDEES-2015_Tertiary_{ct_idees}.xlsx"
fn_transport = f"{base_dir}/JRC-IDEES-2015_Transport_{ct_idees}.xlsx"
# residential
@ -214,7 +215,7 @@ def idees_per_country(ct, year):
# services
df = pd.read_excel(fn_services, "SER_hh_fec", index_col=0)[year]
df = pd.read_excel(fn_tertiary, "SER_hh_fec", index_col=0)[year]
ct_totals["total services space"] = df["Space heating"]
@ -231,7 +232,7 @@ def idees_per_country(ct, year):
assert df.index[31] == "Electricity"
ct_totals["electricity services cooking"] = df[31]
df = pd.read_excel(fn_services, "SER_summary", index_col=0)[year]
df = pd.read_excel(fn_tertiary, "SER_summary", index_col=0)[year]
row = "Energy consumption by fuel - Eurostat structure (ktoe)"
ct_totals["total services"] = df[row]
@ -239,6 +240,34 @@ def idees_per_country(ct, year):
assert df.index[50] == "Electricity"
ct_totals["electricity services"] = df[50]
# agriculture, forestry and fishing
start = "Detailed split of energy consumption (ktoe)"
end = "Market shares of energy uses (%)"
df = pd.read_excel(fn_tertiary, "AGR_fec", index_col=0).loc[start:end, year]
rows = [
"Lighting",
"Ventilation",
"Specific electricity uses",
"Pumping devices (electric)"
]
ct_totals["total agriculture electricity"] = df[rows].sum()
rows = ["Specific heat uses", "Low enthalpy heat"]
ct_totals["total agriculture heat"] = df[rows].sum()
rows = [
"Motor drives",
"Farming machine drives (diesel oil incl. biofuels)",
"Pumping devices (diesel oil incl. biofuels)",
]
ct_totals["total agriculture machinery"] = df[rows].sum()
row = ["Agriculture, forestry and fishing"]
ct_totals["total agriculture"] = df[row]
# transport
df = pd.read_excel(fn_transport, "TrRoad_ene", index_col=0)[year]
@ -540,10 +569,13 @@ def build_eea_co2(year=1990):
"international aviation",
"domestic navigation",
"international navigation",
"agriculture, forstry and fishing"
]
emissions["industrial non-elec"] = emissions["total energy"] - emissions[to_subtract].sum(axis=1)
to_drop = ["total energy", "total wL", "total woL"]
emissions["agriculture"] += emissions["agriculture, forestry and fishing"]
to_drop = ["total energy", "total wL", "total woL", "agriculture, forestry and fishing"]
emissions.drop(columns=to_drop, inplace=True)
# convert from Gg to Mt
@ -588,7 +620,7 @@ def build_co2_totals(countries, eea_co2, eurostat_co2):
# does not include industrial process emissions or fuel processing/refining
"industrial non-elec": (ct, "+", "Industry"),
# does not include non-energy emissions
"agriculture": (ct, "+", "+", "Agriculture / Forestry"),
"agriculture": (eurostat_co2.index.get_level_values(0) == 'NL') & eurostat_co2.index.isin(["Agriculture / Forestry", "Fishing"], level=3),
}
for i, mi in mappings.items():

79
scripts/prepare_sector_network.py
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@ -42,6 +42,10 @@ def emission_sectors_from_opts(opts):
"domestic navigation",
"international navigation"
]
if "A" in opts:
sectors += [
"agriulture"
]
return sectors
@ -728,8 +732,9 @@ def insert_electricity_distribution_grid(n, costs):
capital_cost=costs.at['electricity distribution grid', 'fixed'] * cost_factor
)
# this catches regular electricity load and "industry electricity"
loads = n.loads.index[n.loads.carrier.str.contains("electricity")]
# this catches regular electricity load and "industry electricity" and
# "agriculture machinery electric" and "agriculture electricity"
loads = n.loads.index[n.loads.carrier.str.contains("electric")]
n.loads.loc[loads, "bus"] += " low voltage"
bevs = n.links.index[n.links.carrier == "BEV charger"]
@ -1163,8 +1168,8 @@ def add_land_transport(n, costs):
co2 = ice_share / ice_efficiency * transport[nodes].sum().sum() / 8760 * costs.at["oil", 'CO2 intensity']
n.madd("Load",
["land transport oil emissions"],
n.add("Load",
"land transport oil emissions",
bus="co2 atmosphere",
carrier="land transport oil emissions",
p_set=-co2
@ -1901,6 +1906,69 @@ def add_waste_heat(n):
n.links.loc[urban_central + " H2 Fuel Cell", "efficiency2"] = 0.95 - n.links.loc[urban_central + " H2 Fuel Cell", "efficiency"]
def add_agriculture(n, costs):
nodes = pop_layout.index
# electricity
n.madd("Load",
nodes,
suffix=" agriculture electricity",
bus=nodes,
carrier='agriculture electricity',
p_set=nodal_energy_totals.loc[nodes, "total agriculture electricity"] / 8760
)
# heat
n.madd("Load",
nodes,
suffix=" agriculture heat",
bus=nodes + " services rural heat",
carrier="agriculture heat",
p_set=nodal_energy_totals.loc[nodes, "total agriculture heat"] / 8760
)
# machinery
electric_share = get(options["agriculture_machinery_electric_share"], investment_year)
assert electric_share <= 1.
ice_share = 1 - electric_share
machinery_nodal_energy = nodal_energy_totals.loc[nodes, "total agriculture machinery"]
if electric_share > 0:
efficiency_gain = options["agriculture_machinery_fuel_efficiency"] / options["agriculture_machinery_electric_efficiency"]
n.add("Load",
nodes,
suffix=" agriculture machinery electric",
bus=nodes,
carrier="agriculture machinery electric",
p_set=electric_share * efficiency_gain * machinery_nodal_energy / 8760,
)
if ice_share > 0:
n.add("Load",
"agriculture machinery oil",
bus="EU oil",
carrier="agriculture machinery oil",
p_set=ice_share * machinery_nodal_energy / 8760
)
co2 = ice_share * machinery_nodal_energy / 8760 * costs.at["oil", 'CO2 intensity']
n.add("Load",
"agriculture machinery oil emissions",
bus="co2 atmosphere",
carrier="agriculture machinery oil emissions",
p_set=-co2
)
def decentral(n):
"""Removes the electricity transmission system."""
n.lines.drop(n.lines.index, inplace=True)
@ -2027,6 +2095,9 @@ if __name__ == "__main__":
if "I" in opts and "H" in opts:
add_waste_heat(n)
if "A" in opts: # requires H and I
add_agriculture(n, costs)
if options['dac']:
add_dac(n, costs)