"""
Copyright (C) 2013-2019 Calliope contributors listed in AUTHORS.
Licensed under the Apache 2.0 License (see LICENSE file).
conversion.py
~~~~~~~~~~~~~~~~~
Conversion technology constraints.
"""
import pyomo.core as po # pylint: disable=import-error
from calliope.backend.pyomo.util import \
get_param
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_constraint' in sets:
backend_model.balance_conversion_constraint = po.Constraint(
backend_model.loc_techs_balance_conversion_constraint, backend_model.timesteps,
rule=balance_conversion_constraint_rule
)
if 'loc_techs_cost_var_conversion_constraint' in sets:
backend_model.cost_var_conversion_constraint = po.Constraint(
backend_model.costs, backend_model.loc_techs_cost_var_conversion_constraint,
backend_model.timesteps,
rule=cost_var_conversion_constraint_rule
)
[docs]def balance_conversion_constraint_rule(backend_model, loc_tech, timestep):
"""
Balance energy carrier consumption and production
.. container:: scrolling-wrapper
.. math::
-1 * \\boldsymbol{carrier_{con}}(loc::tech::carrier, timestep)
\\times \\eta_{energy}(loc::tech, timestep)
= \\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)
\\times \\eta_{energy}(loc::tech, timestep)
\\quad \\forall loc::tech \\in locs::techs_{conversion},
\\forall timestep \\in timesteps
"""
model_data_dict = backend_model.__calliope_model_data['data']
loc_tech_carrier_out = model_data_dict['lookup_loc_techs_conversion'][('out', loc_tech)]
loc_tech_carrier_in = model_data_dict['lookup_loc_techs_conversion'][('in', loc_tech)]
energy_eff = get_param(backend_model, 'energy_eff', (loc_tech, timestep))
return (
backend_model.carrier_prod[loc_tech_carrier_out, timestep] == -1 *
backend_model.carrier_con[loc_tech_carrier_in, timestep] * energy_eff
)
[docs]def cost_var_conversion_constraint_rule(backend_model, cost, loc_tech, timestep):
"""
Add time-varying conversion technology costs
.. container:: scrolling-wrapper
.. math::
\\boldsymbol{cost_{var}}(loc::tech, cost, timestep) =
\\boldsymbol{carrier_{prod}}(loc::tech::carrier, timestep)
\\times timestep_{weight}(timestep) \\times cost_{om, prod}(loc::tech, cost, timestep)
+
\\boldsymbol{carrier_{con}}(loc::tech::carrier, 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
weight = backend_model.timestep_weights[timestep]
loc_tech_carrier_in = (
model_data_dict['data']['lookup_loc_techs_conversion'][('in', loc_tech)]
)
loc_tech_carrier_out = (
model_data_dict['data']['lookup_loc_techs_conversion'][('out', loc_tech)]
)
cost_om_prod = get_param(backend_model, 'cost_om_prod',
(cost, loc_tech, timestep))
cost_om_con = get_param(backend_model, 'cost_om_con',
(cost, loc_tech, timestep))
if po.value(cost_om_prod):
cost_prod = (cost_om_prod * weight *
backend_model.carrier_prod[loc_tech_carrier_out, timestep])
else:
cost_prod = 0
if po.value(cost_om_con):
cost_con = (cost_om_con * weight * -1 *
backend_model.carrier_con[loc_tech_carrier_in, timestep])
else:
cost_con = 0
backend_model.cost_var_rhs[cost, loc_tech, timestep] = cost_prod + cost_con
return (backend_model.cost_var[cost, loc_tech, timestep] ==
backend_model.cost_var_rhs[cost, loc_tech, timestep])