Source code for calliope.backend.pyomo.constraints.conversion_plus
"""
Copyright (C) since 2013 Calliope contributors listed in AUTHORS.
Licensed under the Apache 2.0 License (see LICENSE file).
conversion_plus.py
~~~~~~~~~~~~~~~~~~
Conversion plus technology constraints.
"""
import pyomo.core as po # pylint: disable=import-error
from calliope.backend.pyomo.util import (
get_param,
split_comma_list,
get_conversion_plus_io,
)
ORDER = 20 # order in which to invoke constraints relative to other constraint files
def load_constraints(backend_model):
sets = backend_model.__calliope_model_data["sets"]
if "loc_techs_balance_conversion_plus_primary_constraint" in sets:
backend_model.balance_conversion_plus_primary_constraint = po.Constraint(
backend_model.loc_techs_balance_conversion_plus_primary_constraint,
backend_model.timesteps,
rule=balance_conversion_plus_primary_constraint_rule,
)
if "loc_techs_carrier_production_max_conversion_plus_constraint" in sets:
backend_model.carrier_production_max_conversion_plus_constraint = po.Constraint(
backend_model.loc_techs_carrier_production_max_conversion_plus_constraint,
backend_model.timesteps,
rule=carrier_production_max_conversion_plus_constraint_rule,
)
if "loc_techs_carrier_production_min_conversion_plus_constraint" in sets:
backend_model.carrier_production_min_conversion_plus_constraint = po.Constraint(
backend_model.loc_techs_carrier_production_min_conversion_plus_constraint,
backend_model.timesteps,
rule=carrier_production_min_conversion_plus_constraint_rule,
)
if "loc_techs_cost_var_conversion_plus_constraint" in sets:
backend_model.cost_var_conversion_plus_constraint = po.Constraint(
backend_model.costs,
backend_model.loc_techs_cost_var_conversion_plus_constraint,
backend_model.timesteps,
rule=cost_var_conversion_plus_constraint_rule,
)
if "loc_techs_balance_conversion_plus_in_2_constraint" in sets:
backend_model.balance_conversion_plus_in_2_constraint = po.Constraint(
["in_2"],
backend_model.loc_techs_balance_conversion_plus_in_2_constraint,
backend_model.timesteps,
rule=balance_conversion_plus_tiers_constraint_rule,
)
if "loc_techs_balance_conversion_plus_in_3_constraint" in sets:
backend_model.balance_conversion_plus_in_3_constraint = po.Constraint(
["in_3"],
backend_model.loc_techs_balance_conversion_plus_in_3_constraint,
backend_model.timesteps,
rule=balance_conversion_plus_tiers_constraint_rule,
)
if "loc_techs_balance_conversion_plus_out_2_constraint" in sets:
backend_model.balance_conversion_plus_out_2_constraint = po.Constraint(
["out_2"],
backend_model.loc_techs_balance_conversion_plus_out_2_constraint,
backend_model.timesteps,
rule=balance_conversion_plus_tiers_constraint_rule,
)
if "loc_techs_balance_conversion_plus_out_3_constraint" in sets:
backend_model.balance_conversion_plus_out_3_constraint = po.Constraint(
["out_3"],
backend_model.loc_techs_balance_conversion_plus_out_3_constraint,
backend_model.timesteps,
rule=balance_conversion_plus_tiers_constraint_rule,
)
if "loc_tech_carrier_tiers_conversion_plus_zero_ratio_constraint" in sets:
backend_model.conversion_plus_prod_con_to_zero_constraint = po.Constraint(
backend_model.loc_tech_carrier_tiers_conversion_plus_zero_ratio_constraint,
backend_model.timesteps,
rule=conversion_plus_prod_con_to_zero_constraint_rule,
)
[docs]def balance_conversion_plus_primary_constraint_rule(backend_model, loc_tech, timestep):
"""
Balance energy carrier consumption and production for carrier_in and carrier_out
.. container:: scrolling-wrapper
.. math::
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{out}}
\\frac{\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)}{
carrier\\_ratio(loc::tech::carrier, `out')} =
-1 * \\sum_{loc::tech::carrier \\in loc::tech::carriers_{in}} (
\\boldsymbol{carrier_{con}}(loc::tech::carrier, timestep)
* carrier\\_ratio(loc::tech::carrier, `in') * \\eta_{energy}(loc::tech, timestep))
\\quad \\forall loc::tech \\in loc::techs_{conversion^{+}}, \\forall timestep \\in timesteps
"""
model_data_dict = backend_model.__calliope_model_data["data"]
loc_tech_carriers_out = split_comma_list(
model_data_dict["lookup_loc_techs_conversion_plus"]["out", loc_tech]
)
loc_tech_carriers_in = split_comma_list(
model_data_dict["lookup_loc_techs_conversion_plus"]["in", loc_tech]
)
energy_eff = get_param(backend_model, "energy_eff", (loc_tech, timestep))
carrier_prod = []
for loc_tech_carrier in loc_tech_carriers_out:
carrier_ratio = get_param(
backend_model, "carrier_ratios", ("out", loc_tech_carrier, timestep)
)
if po.value(carrier_ratio) != 0:
carrier_prod.append(
backend_model.carrier_prod[loc_tech_carrier, timestep] / carrier_ratio
)
carrier_con = sum(
backend_model.carrier_con[loc_tech_carrier, timestep]
* get_param(backend_model, "carrier_ratios", ("in", loc_tech_carrier, timestep))
for loc_tech_carrier in loc_tech_carriers_in
)
return sum(carrier_prod) == -1 * carrier_con * energy_eff
[docs]def carrier_production_max_conversion_plus_constraint_rule(
backend_model, loc_tech, timestep
):
"""
Set maximum conversion_plus carrier production.
.. container:: scrolling-wrapper
.. math::
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{out}}
\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)
\\leq \\boldsymbol{energy_{cap}}(loc::tech) \\times timestep\\_resolution(timestep)
\\quad \\forall loc::tech \\in loc::techs_{conversion^{+}},
\\forall timestep \\in timesteps
"""
model_data_dict = backend_model.__calliope_model_data["data"]
timestep_resolution = backend_model.timestep_resolution[timestep]
loc_tech_carriers_out = split_comma_list(
model_data_dict["lookup_loc_techs_conversion_plus"]["out", loc_tech]
)
carrier_prod = sum(
backend_model.carrier_prod[loc_tech_carrier, timestep]
for loc_tech_carrier in loc_tech_carriers_out
)
return carrier_prod <= timestep_resolution * backend_model.energy_cap[loc_tech]
[docs]def carrier_production_min_conversion_plus_constraint_rule(
backend_model, loc_tech, timestep
):
"""
Set minimum conversion_plus carrier production.
.. container:: scrolling-wrapper
.. math::
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{out}}
\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)
\\leq \\boldsymbol{energy_{cap}}(loc::tech) \\times timestep\\_resolution(timestep)
\\times energy_{cap, min use}(loc::tech)
\\quad \\forall loc::tech \\in loc::techs_{conversion^{+}},
\\forall timestep \\in timesteps
"""
model_data_dict = backend_model.__calliope_model_data["data"]
timestep_resolution = backend_model.timestep_resolution[timestep]
min_use = get_param(backend_model, "energy_cap_min_use", (loc_tech, timestep))
loc_tech_carriers_out = split_comma_list(
model_data_dict["lookup_loc_techs_conversion_plus"]["out", loc_tech]
)
carrier_prod = sum(
backend_model.carrier_prod[loc_tech_carrier, timestep]
for loc_tech_carrier in loc_tech_carriers_out
)
return carrier_prod >= (
timestep_resolution * backend_model.energy_cap[loc_tech] * min_use
)
[docs]def cost_var_conversion_plus_constraint_rule(backend_model, cost, loc_tech, timestep):
"""
Add time-varying conversion_plus technology costs
.. container:: scrolling-wrapper
.. math::
\\boldsymbol{cost_{var}}(loc::tech, cost, timestep) =
\\boldsymbol{carrier_{prod}}(loc::tech::carrier_{primary}, timestep)
\\times timestep_{weight}(timestep) \\times cost_{om, prod}(loc::tech, cost, timestep)
+
\\boldsymbol{carrier_{con}}(loc::tech::carrier_{primary}, timestep)
\\times timestep_{weight}(timestep) \\times cost_{om, con}(loc::tech, cost, timestep)
\\quad \\forall loc::tech \\in loc::techs_{cost_{var}, conversion^{+}}
"""
model_data_dict = backend_model.__calliope_model_data["data"]
weight = backend_model.timestep_weights[timestep]
loc_tech_carrier_con = model_data_dict["lookup_primary_loc_tech_carriers_in"][
loc_tech
]
loc_tech_carrier_prod = model_data_dict["lookup_primary_loc_tech_carriers_out"][
loc_tech
]
var_cost = 0
if loc_tech_carrier_prod in backend_model.loc_tech_carriers_prod:
cost_om_prod = get_param(
backend_model, "cost_om_prod", (cost, loc_tech, timestep)
)
if cost_om_prod:
var_cost += (
cost_om_prod
* weight
* backend_model.carrier_prod[loc_tech_carrier_prod, timestep]
)
if loc_tech_carrier_con in backend_model.loc_tech_carriers_con:
cost_om_con = get_param(
backend_model, "cost_om_con", (cost, loc_tech, timestep)
)
if cost_om_con:
var_cost += (
cost_om_con
* weight
* -1
* backend_model.carrier_con[loc_tech_carrier_con, timestep]
)
backend_model.cost_var_rhs[cost, loc_tech, timestep] = var_cost
return (
backend_model.cost_var[cost, loc_tech, timestep]
== backend_model.cost_var_rhs[cost, loc_tech, timestep]
)
[docs]def balance_conversion_plus_tiers_constraint_rule(
backend_model, tier, loc_tech, timestep
):
"""
Force all carrier_in_2/carrier_in_3 and carrier_out_2/carrier_out_3 to follow
carrier_in and carrier_out (respectively).
If `tier` in ['out_2', 'out_3']:
.. container:: scrolling-wrapper
.. math::
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{out}} (
\\frac{\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)}{
carrier\\_ratio(loc::tech::carrier, `out')} =
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{tier}} (
\\frac{\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)}{
carrier\\_ratio(loc::tech::carrier, tier)}
\\quad \\forall \\text { tier } \\in [`out_2', `out_3'], \\forall loc::tech
\\in loc::techs_{conversion^{+}}, \\forall timestep \\in timesteps
If `tier` in ['in_2', 'in_3']:
.. container:: scrolling-wrapper
.. math::
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{in}}
\\frac{\\boldsymbol{carrier_{con}}(loc::tech::carrier, timestep)}{
carrier\\_ratio(loc::tech::carrier, `in')} =
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{tier}}
\\frac{\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)}{
carrier\\_ratio(loc::tech::carrier, tier)}
\\quad \\forall \\text{ tier } \\in [`in_2', `in_3'], \\forall loc::tech
\\in loc::techs_{conversion^{+}}, \\forall timestep \\in timesteps
"""
primary_tier, decision_variable = get_conversion_plus_io(backend_model, tier)
model_data_dict = backend_model.__calliope_model_data["data"]
loc_tech_carriers_1 = split_comma_list(
model_data_dict["lookup_loc_techs_conversion_plus"][primary_tier, loc_tech]
)
loc_tech_carriers_2 = split_comma_list(
model_data_dict["lookup_loc_techs_conversion_plus"][tier, loc_tech]
)
c_1 = []
c_2 = []
for loc_tech_carrier in loc_tech_carriers_1:
carrier_ratio_1 = get_param(
backend_model, "carrier_ratios", (primary_tier, loc_tech_carrier, timestep)
)
if po.value(carrier_ratio_1) != 0:
c_1.append(decision_variable[loc_tech_carrier, timestep] / carrier_ratio_1)
for loc_tech_carrier in loc_tech_carriers_2:
carrier_ratio_2 = get_param(
backend_model, "carrier_ratios", (tier, loc_tech_carrier, timestep)
)
if po.value(carrier_ratio_2) != 0:
c_2.append(decision_variable[loc_tech_carrier, timestep] / carrier_ratio_2)
if len(c_2) == 0:
return po.Constraint.Skip
else:
return sum(c_1) == sum(c_2)
[docs]def conversion_plus_prod_con_to_zero_constraint_rule(
backend_model, loc_tech_carrier_tier, timestep
):
"""
Force any carrier production or consumption for a conversion plus technology to
zero in timesteps where its carrier_ratio is zero
"""
loc_tech_carrier, tier = loc_tech_carrier_tier.rsplit("::", 1)
primary_tier, decision_variable = get_conversion_plus_io(backend_model, tier)
carrier_ratio = get_param(
backend_model, "carrier_ratios", (tier, loc_tech_carrier, timestep)
)
if po.value(carrier_ratio) == 0:
return decision_variable[loc_tech_carrier, timestep] == 0
else:
return po.Constraint.Skip