def _include_feasibility_slack(model, bus_names, bus_p_loads, bus_q_loads,
gens_by_bus, gen_attrs,
p_marginal_slack_penalty, q_marginal_slack_penalty):
import egret.model_library.decl as decl
p_over_gen_bounds = {k: (0, tx_utils.over_gen_limit(bus_p_loads[k], gens_by_bus[k], gen_attrs['p_max'])) for k in bus_names}
decl.declare_var('p_over_generation', model=model, index_set=bus_names,
initialize=0., bounds=p_over_gen_bounds
)
p_load_shed_bounds = {k: (0, tx_utils.load_shed_limit(bus_p_loads[k], gens_by_bus[k], gen_attrs['p_min'])) for k in bus_names}
decl.declare_var('p_load_shed', model=model, index_set=bus_names,
initialize=0., bounds=p_load_shed_bounds
)
q_over_gen_bounds = {k: (0, tx_utils.over_gen_limit(bus_q_loads[k], gens_by_bus[k], gen_attrs['q_max'])) for k in bus_names}
decl.declare_var('q_over_generation', model=model, index_set=bus_names,
initialize=0., bounds=q_over_gen_bounds
)
q_load_shed_bounds = {k: (0, tx_utils.load_shed_limit(bus_q_loads[k], gens_by_bus[k], gen_attrs['q_min'])) for k in bus_names}
decl.declare_var('q_load_shed', model=model, index_set=bus_names,
initialize=0., bounds=q_load_shed_bounds
)
p_rhs_kwargs = {'include_feasibility_load_shed':'p_load_shed', 'include_feasibility_over_generation':'p_over_generation'}
q_rhs_kwargs = {'include_feasibility_load_shed':'q_load_shed', 'include_feasibility_over_generation':'q_over_generation'}
penalty_expr = sum(p_marginal_slack_penalty * (model.p_over_generation[bus_name] + model.p_load_shed[bus_name])
+ q_marginal_slack_penalty * (model.q_over_generation[bus_name] + model.q_load_shed[bus_name])
for bus_name in bus_names)
return p_rhs_kwargs, q_rhs_kwargs, penalty_expr
def _include_system_feasibility_slack(model, bus_p_loads, gen_attrs,
p_marginal_slack_penalty):
import egret.model_library.decl as decl
load = sum(bus_p_loads.values())
over_gen_bounds = (0,
tx_utils.over_gen_limit(load, gen_attrs['names'],
gen_attrs['p_max']))
decl.declare_var('p_over_generation',
model=model,
index_set=None,
initialize=0.,
bounds=over_gen_bounds)
load_shed_bounds = (0,
tx_utils.load_shed_limit(load, gen_attrs['names'],
gen_attrs['p_min']))
decl.declare_var('p_load_shed',
model=model,
index_set=None,
initialize=0.,
bounds=load_shed_bounds)
p_rhs_kwargs = {
'include_feasibility_load_shed': 'p_load_shed',
'include_feasibility_over_generation': 'p_over_generation'
}
penalty_expr = p_marginal_slack_penalty * (model.p_load_shed +
model.p_over_generation)
return p_rhs_kwargs, penalty_expr
