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make_summary: Account for multi-links in supply* summaries

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Tom Brown 2019-12-06 17:40:20 +01:00
parent 80642ae9af
commit ec9b447949
1 changed files with 20 additions and 27 deletions
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47
scripts/make_summary.py
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@ -248,17 +248,13 @@ def calculate_energy(n,label,energy):
def calculate_supply(n,label,supply): def calculate_supply(n,label,supply):
"""calculate the max dispatch of each component at the buses where the loads are attached""" """calculate the max dispatch of each component at the buses aggregated by carrier"""
load_types = n.loads.carrier.value_counts().index bus_carriers = n.buses.carrier.unique()
for i in load_types: for i in bus_carriers:
bus_map = (n.buses.carrier == i)
buses = n.loads.bus[n.loads.carrier == i].values bus_map.at[""] = False
bus_map = pd.Series(False,index=n.buses.index)
bus_map.loc[buses] = True
for c in n.iterate_components(n.one_port_components): for c in n.iterate_components(n.one_port_components):
@ -275,9 +271,9 @@ def calculate_supply(n,label,supply):
for c in n.iterate_components(n.branch_components): for c in n.iterate_components(n.branch_components):
for end in ["0","1"]: for end in [col[3:] for col in c.df.columns if col[:3] == "bus"]:
items = c.df.index[c.df["bus" + end].map(bus_map)] items = c.df.index[c.df["bus" + end].map(bus_map,na_action=False)]
if len(items) == 0: if len(items) == 0:
continue continue
@ -285,23 +281,20 @@ def calculate_supply(n,label,supply):
#lots of sign compensation for direction and to do maximums #lots of sign compensation for direction and to do maximums
s = (-1)**(1-int(end))*((-1)**int(end)*c.pnl["p"+end][items]).max().groupby(c.df.loc[items,'carrier']).sum() s = (-1)**(1-int(end))*((-1)**int(end)*c.pnl["p"+end][items]).max().groupby(c.df.loc[items,'carrier']).sum()
supply = supply.reindex(pd.MultiIndex.from_product([[i],[c.list_name],s.index])|supply.index) supply = supply.reindex(pd.MultiIndex.from_product([[i],[c.list_name],s.index+end])|supply.index)
supply.loc[idx[i,c.list_name,list(s.index)],label] = s.values supply.loc[idx[i,c.list_name,list(s.index+end)],label] = s.values
return supply return supply
def calculate_supply_energy(n,label,supply_energy): def calculate_supply_energy(n,label,supply_energy):
"""calculate the total dispatch of each component at the buses where the loads are attached""" """calculate the total energy supply/consuption of each component at the buses aggregated by carrier"""
load_types = n.loads.carrier.value_counts().index
for i in load_types: bus_carriers = n.buses.carrier.unique()
buses = n.loads.bus[n.loads.carrier == i].values for i in bus_carriers:
bus_map = (n.buses.carrier == i)
bus_map = pd.Series(False,index=n.buses.index) bus_map.at[""] = False
bus_map.loc[buses] = True
for c in n.iterate_components(n.one_port_components): for c in n.iterate_components(n.one_port_components):
@ -310,7 +303,7 @@ def calculate_supply_energy(n,label,supply_energy):
if len(items) == 0: if len(items) == 0:
continue continue
s = c.pnl.p[items].sum().multiply(c.df.loc[items,'sign']).groupby(c.df.loc[items,'carrier']).sum() s = c.pnl.p[items].multiply(n.snapshot_weightings,axis=0).sum().multiply(c.df.loc[items,'sign']).groupby(c.df.loc[items,'carrier']).sum()
supply_energy = supply_energy.reindex(pd.MultiIndex.from_product([[i],[c.list_name],s.index])|supply_energy.index) supply_energy = supply_energy.reindex(pd.MultiIndex.from_product([[i],[c.list_name],s.index])|supply_energy.index)
supply_energy.loc[idx[i,c.list_name,list(s.index)],label] = s.values supply_energy.loc[idx[i,c.list_name,list(s.index)],label] = s.values
@ -318,17 +311,17 @@ def calculate_supply_energy(n,label,supply_energy):
for c in n.iterate_components(n.branch_components): for c in n.iterate_components(n.branch_components):
for end in ["0","1"]: for end in [col[3:] for col in c.df.columns if col[:3] == "bus"]:
items = c.df.index[c.df["bus" + end].map(bus_map)] items = c.df.index[c.df["bus" + str(end)].map(bus_map,na_action=False)]
if len(items) == 0: if len(items) == 0:
continue continue
s = (-1)*c.pnl["p"+end][items].sum().groupby(c.df.loc[items,'carrier']).sum() s = (-1)*c.pnl["p"+end][items].multiply(n.snapshot_weightings,axis=0).sum().groupby(c.df.loc[items,'carrier']).sum()
supply_energy = supply_energy.reindex(pd.MultiIndex.from_product([[i],[c.list_name],s.index])|supply_energy.index) supply_energy = supply_energy.reindex(pd.MultiIndex.from_product([[i],[c.list_name],s.index+end])|supply_energy.index)
supply_energy.loc[idx[i,c.list_name,list(s.index)],label] = s.values supply_energy.loc[idx[i,c.list_name,list(s.index+end)],label] = s.values
return supply_energy return supply_energy