def add_EQ_constraints(n, o, scaling=1e-1):
float_regex = "[0-9]*\.?[0-9]+"
level = float(re.findall(float_regex, o)[0])
if o[-1] == 'c':
ggrouper = n.generators.bus.map(n.buses.country)
lgrouper = n.loads.bus.map(n.buses.country)
sgrouper = n.storage_units.bus.map(n.buses.country)
else:
ggrouper = n.generators.bus
lgrouper = n.loads.bus
sgrouper = n.storage_units.bus
load = n.snapshot_weightings @ \
n.loads_t.p_set.groupby(lgrouper, axis=1).sum()
inflow = n.snapshot_weightings @ \
n.storage_units_t.inflow.groupby(sgrouper, axis=1).sum()
inflow = inflow.reindex(load.index).fillna(0.)
rhs = scaling * ( level * load - inflow )
lhs_gen = linexpr((n.snapshot_weightings * scaling,
get_var(n, "Generator", "p").T)
).T.groupby(ggrouper, axis=1).apply(join_exprs)
lhs_spill = linexpr((-n.snapshot_weightings * scaling,
get_var(n, "StorageUnit", "spill").T)
).T.groupby(sgrouper, axis=1).apply(join_exprs)
lhs_spill = lhs_spill.reindex(lhs_gen.index).fillna("")
lhs = lhs_gen + lhs_spill
define_constraints(n, lhs, ">=", rhs, "equity", "min")
def add_CCL_constraints(n, config):
agg_p_nom_limits = config['electricity'].get('agg_p_nom_limits')
try:
agg_p_nom_minmax = pd.read_csv(agg_p_nom_limits,
index_col=list(range(2)))
except IOError:
logger.exception("Need to specify the path to a .csv file containing "
"aggregate capacity limits per country in "
"config['electricity']['agg_p_nom_limit'].")
logger.info("Adding per carrier generation capacity constraints for "
"individual countries")
gen_country = n.generators.bus.map(n.buses.country)
# cc means country and carrier
p_nom_per_cc = (pd.DataFrame(
{'p_nom': linexpr((1, get_var(n, 'Generator', 'p_nom'))),
'country': gen_country, 'carrier': n.generators.carrier})
.dropna(subset=['p_nom'])
.groupby(['country', 'carrier']).p_nom
.apply(join_exprs))
minimum = agg_p_nom_minmax['min'].dropna()
if not minimum.empty:
minconstraint = define_constraints(n, p_nom_per_cc[minimum.index],
'>=', minimum, 'agg_p_nom', 'min')
maximum = agg_p_nom_minmax['max'].dropna()
if not maximum.empty:
maxconstraint = define_constraints(n, p_nom_per_cc[maximum.index],
'<=', maximum, 'agg_p_nom', 'max')
def add_BAU_constraints(n, config):
mincaps = pd.Series(config['electricity']['BAU_mincapacities'])
lhs = (linexpr(
(1, get_var(n, 'Generator',
'p_nom'))).groupby(n.generators.carrier).apply(join_exprs))
define_constraints(n, lhs, '>=', mincaps[lhs.index], 'Carrier',
'bau_mincaps')
def add_BAU_constraints(n, config):
mincaps = pd.Series(config["electricity"]["BAU_mincapacities"])
lhs = (linexpr(
(1, get_var(n, "Generator",
"p_nom"))).groupby(n.generators.carrier).apply(join_exprs))
define_constraints(n, lhs, ">=", mincaps[lhs.index], "Carrier",
"bau_mincaps")
def add_CCL_constraints(n, config):
agg_p_nom_limits = config["electricity"].get("agg_p_nom_limits")
try:
agg_p_nom_minmax = pd.read_csv(agg_p_nom_limits,
index_col=list(range(2)))
except IOError:
logger.exception("Need to specify the path to a .csv file containing "
"aggregate capacity limits per country in "
"config['electricity']['agg_p_nom_limit'].")
logger.info("Adding per carrier generation capacity constraints for "
"individual countries")
gen_country = n.generators.bus.map(n.buses.country)
# cc means country and carrier
p_nom_per_cc = (pd.DataFrame({
"p_nom":
linexpr((1, get_var(n, "Generator", "p_nom"))),
"country":
gen_country,
"carrier":
n.generators.carrier,
}).dropna(subset=["p_nom"]).groupby(["country",
"carrier"]).p_nom.apply(join_exprs))
minimum = agg_p_nom_minmax["min"].dropna()
if not minimum.empty:
minconstraint = define_constraints(n, p_nom_per_cc[minimum.index],
">=", minimum, "agg_p_nom", "min")
maximum = agg_p_nom_minmax["max"].dropna()
if not maximum.empty:
maxconstraint = define_constraints(n, p_nom_per_cc[maximum.index],
"<=", maximum, "agg_p_nom", "max")
def add_battery_constraints(n):
nodes = n.buses.index[n.buses.carrier == "battery"]
if nodes.empty or ('Link', 'p_nom') not in n.variables.index:
return
link_p_nom = get_var(n, "Link", "p_nom")
lhs = linexpr((1,link_p_nom[nodes + " charger"]),
(-n.links.loc[nodes + " discharger", "efficiency"].values,
link_p_nom[nodes + " discharger"].values))
define_constraints(n, lhs, "=", 0, 'Link', 'charger_ratio')
def add_SAFE_constraints(n, config):
peakdemand = (1. + config['electricity']['SAFE_reservemargin']) *\
n.loads_t.p_set.sum(axis=1).max()
conv_techs = config['plotting']['conv_techs']
exist_conv_caps = n.generators.query('~p_nom_extendable & carrier in @conv_techs')\
.p_nom.sum()
ext_gens_i = n.generators.query('carrier in @conv_techs & p_nom_extendable').index
lhs = linexpr((1, get_var(n, 'Generator', 'p_nom')[ext_gens_i])).sum()
rhs = peakdemand - exist_conv_caps
define_constraints(n, lhs, '>=', rhs, 'Safe', 'mintotalcap')
def add_SAFE_constraints(n, config):
peakdemand = (1.0 + config["electricity"]["SAFE_reservemargin"]
) * n.loads_t.p_set.sum(axis=1).max()
conv_techs = config["plotting"]["conv_techs"]
exist_conv_caps = n.generators.query(
"~p_nom_extendable & carrier in @conv_techs").p_nom.sum()
ext_gens_i = n.generators.query(
"carrier in @conv_techs & p_nom_extendable").index
lhs = linexpr((1, get_var(n, "Generator", "p_nom")[ext_gens_i])).sum()
rhs = peakdemand - exist_conv_caps
define_constraints(n, lhs, ">=", rhs, "Safe", "mintotalcap")
