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remove unnecessary variables when adding endogenously retrofitting

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This commit is contained in:
lisazeyen 2020-10-21 19:19:38 +02:00
parent 1e2895023b
commit 63f1e99c8b
1 changed files with 48 additions and 72 deletions
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120
scripts/prepare_sector_network.py
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@ -1287,24 +1287,18 @@ def add_heat(network):
if options['retrofitting']['retro_endogen']: if options['retrofitting']['retro_endogen']:
print("adding retrofitting endogenously") print("adding retrofitting endogenously")
# resample heat demand to not overestimate retrofitting # resample heat demand to not overestimate retrofitting
heat_demand_r = heat_demand.resample(opts[1]).mean() heat_demand_r = heat_demand.resample(opts[1]).mean()
# get space heat demand
space_heat_demand = pd.concat([heat_demand_r["residential space"],
heat_demand_r["services space"]],
axis=1)
# costs and floor area per country # costs and floor area per country
retro_cost = pd.read_csv(snakemake.input.retro_cost_energy, retro_cost = pd.read_csv(snakemake.input.retro_cost_energy,
index_col=[0, 1], skipinitialspace=True, index_col=[0, 1], skipinitialspace=True,
header=[0, 1]) header=[0, 1])
floor_area = pd.read_csv(snakemake.input.floor_area, index_col=[0, 1]) floor_area = pd.read_csv(snakemake.input.floor_area, index_col=[0, 1])
index = pd.MultiIndex.from_product([pop_layout.index, sectors + ["tot"]]) network.add("Carrier", "retrofitting")
square_metres = pd.DataFrame(np.nan, index=index, columns=["m²"])
# weighting for share of space heat demand # share of space heat demand
w_space = {} w_space = {}
for sector in sectors: for sector in sectors:
w_space[sector] = heat_demand_r[sector + " space"] / \ w_space[sector] = heat_demand_r[sector + " space"] / \
@ -1313,79 +1307,61 @@ def add_heat(network):
heat_demand_r["residential space"]) / heat_demand_r["residential space"]) /
heat_demand_r.groupby(level=[1], axis=1).sum()) heat_demand_r.groupby(level=[1], axis=1).sum())
network.add("Carrier", "retrofitting")
for node in list(heat_demand.columns.levels[1]): for name in network.loads[network.loads.carrier.isin([x + " heat" for x in heat_systems])].index:
retro_nodes = pd.Index([node])
space_heat_demand_node = space_heat_demand[retro_nodes]
space_heat_demand_node.columns = sectors
ct = node[:2]
square_metres = (pop_layout.loc[node].fraction
* floor_area.loc[ct, "value"] * 10**6)
for carrier in heat_systems:
name = node + " " + carrier + " heat"
if (name in list(network.loads_t.p_set.columns)):
# if "urban central" in carrier: ct = name[:2]
# f = dist_fraction[node] node = name[:5]
# elif "urban decentral" in carrier:
# f = urban_fraction[node] - dist_fraction[node]
if "urban" in carrier:
f = urban_fraction[node]
else:
f = 1 - urban_fraction[node]
if f == 0: f = urban_fraction[node] if "urban" in name else (urban_fraction[node])
continue if f == 0:
continue
# get sector (residential/services) or "tot" for "urban central"
sec = [x if x in name else "tot" for x in sectors][0]
if "residential" in carrier: # get square meters at node urban/rural
sec = "residential" square_metres_node = ((pop_layout.loc[node].fraction
elif "services" in carrier: * floor_area.loc[ct, "value"] * 10**6).loc[sec] * f)
sec = "services" # total heat demand at node
else: demand = (network.loads_t.p_set[name].resample(opts[1])
sec = "tot" .mean())
# space heat demand at node
space_heat_demand = demand * w_space[sec][node]
# p_max_pu/p_min_pu of retrofitting generators
space_pu = (space_heat_demand / space_heat_demand.max()).to_frame(name=node)
square_metres_c = (square_metres.loc[sec] * f) # maximum heat savings at node
# weighting instead of taking space heat demand to dE = retro_cost.loc[(ct, sec), ("dE")]
# allow simulatounsly exogenous and optimised # get p_nom_max for different retrofitting strengths
# retrofitting dE_diff = abs(dE.diff()).fillna(1-dE.iloc[0])
demand = (network.loads_t.p_set[name].resample(opts[1]) # convert costs per m^2 to costs per MW
.mean()) capital_cost = retro_cost.loc[(ct, sec), ("cost")] * square_metres_node / \
space_heat_demand_c = demand * w_space[sec][node] ((1 - dE) * space_heat_demand.max())
space_peak_c = space_heat_demand_c.max()
if space_peak_c == 0:
continue
space_pu_c = (space_heat_demand_c /
space_peak_c).to_frame(name=node)
dE = retro_cost.loc[(ct, sec), ("dE")] strengths = retro_cost.columns.levels[1]
dE_diff = abs(dE.diff()).fillna(1-dE.iloc[0])
cost_c = retro_cost.loc[(ct, sec), ("cost")]
capital_cost = cost_c * square_metres_c / \
((1 - dE) * space_peak_c)
steps = retro_cost.cost.columns
if (capital_cost.diff() < 0).sum():
print(
"warning, costs are not linear for ", ct, " ", sec)
s = capital_cost[(capital_cost.diff() < 0)].index
steps = steps.drop(s)
space_pu_c = (space_pu_c.reindex(index=heat_demand.index) # check that stronger retrofitting has higher costs per MWh than lower retrofitting
.fillna(method="ffill")) if (capital_cost.diff() < 0).sum():
for strength in steps: print(
network.madd( "warning, costs are not linear for ", ct, " ", sec)
'Generator', s = capital_cost[(capital_cost.diff() < 0)].index
retro_nodes, strengths = strengths.drop(s)
suffix=' retrofitting ' + strength + " " + carrier,
bus=node + " " + carrier + " heat", # reindex back to hourly resolution
strength=' retrofitting ' + strength, space_pu = (space_pu.reindex(index=heat_demand.index)
type=carrier, .fillna(method="ffill"))
for strength in strengths:
network.madd('Generator',
[node],
suffix=' retrofitting ' + strength + " " + name[6::],
bus=name,
carrier="retrofitting", carrier="retrofitting",
p_nom_extendable=True, p_nom_extendable=True,
p_nom_max=dE_diff[strength] * space_peak_c, p_nom_max=dE_diff[strength] * space_heat_demand.max(),
dE=dE_diff[strength], dE=dE_diff[strength],
p_max_pu=space_pu_c, p_max_pu=space_pu,
p_min_pu=space_pu_c, p_min_pu=space_pu,
country=ct, country=ct,
capital_cost=capital_cost[strength] * options['retrofitting']['cost_factor']) capital_cost=capital_cost[strength] * options['retrofitting']['cost_factor'])