def create_scopf_model(model_data,
include_feasibility_slack=False,
base_point=BasePointType.FLATSTART,
ptdf_options=None):
ptdf_options = lpu.populate_default_ptdf_options(ptdf_options)
baseMVA = model_data.data['system']['baseMVA']
lpu.check_and_scale_ptdf_options(ptdf_options, baseMVA)
md = model_data.clone_in_service()
tx_utils.scale_ModelData_to_pu(md, inplace=True)
gens = dict(md.elements(element_type='generator'))
buses = dict(md.elements(element_type='bus'))
branches = dict(md.elements(element_type='branch'))
loads = dict(md.elements(element_type='load'))
shunts = dict(md.elements(element_type='shunt'))
dc_branches = dict(md.elements(element_type='dc_branch'))
contingencies = dict(md.elements(element_type='contingency'))
gen_attrs = md.attributes(element_type='generator')
## to keep things in order
buses_idx = tuple(buses.keys())
branches_idx = tuple(branches.keys())
inlet_branches_by_bus, outlet_branches_by_bus = \
tx_utils.inlet_outlet_branches_by_bus(branches, buses)
gens_by_bus = tx_utils.gens_by_bus(buses, gens)
model = pyo.ConcreteModel()
### declare (and fix) the loads at the buses
bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)
libbus.declare_var_pl(model, buses_idx, initialize=bus_p_loads)
model.pl.fix()
### declare the fixed shunts at the buses
_, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)
### declare the generator real power
pg_init = {
k: (gen_attrs['p_min'][k] + gen_attrs['p_max'][k]) / 2.0
for k in gen_attrs['pg']
}
libgen.declare_var_pg(model,
gen_attrs['names'],
initialize=pg_init,
bounds=zip_items(gen_attrs['p_min'],
gen_attrs['p_max']))
### include the feasibility slack for the system balance
p_rhs_kwargs = {}
if include_feasibility_slack:
p_marginal_slack_penalty = _validate_and_extract_slack_penalty(md)
p_rhs_kwargs, penalty_expr = _include_system_feasibility_slack(
model, bus_p_loads, gen_attrs, p_marginal_slack_penalty)
if dc_branches:
dcpf_bounds = dict()
for k, k_dict in dc_branches.items():
kp_max = k_dict['rating_long_term']
if kp_max is None:
dcpf_bounds[k] = (None, None)
else:
dcpf_bounds[k] = (-kp_max, kp_max)
libbranch.declare_var_dcpf(
model=model,
index_set=dc_branches.keys(),
initialize=0.,
bounds=dcpf_bounds,
)
dc_inlet_branches_by_bus, dc_outlet_branches_by_bus = \
tx_utils.inlet_outlet_branches_by_bus(dc_branches, buses)
else:
dc_inlet_branches_by_bus = None
dc_outlet_branches_by_bus = None
### declare the p balance
libbus.declare_eq_p_balance_ed(model=model,
index_set=buses_idx,
bus_p_loads=bus_p_loads,
gens_by_bus=gens_by_bus,
bus_gs_fixed_shunts=bus_gs_fixed_shunts,
**p_rhs_kwargs)
### declare net withdraw expression for use in PTDF power flows
libbus.declare_expr_p_net_withdraw_at_bus(
model=model,
index_set=buses_idx,
bus_p_loads=bus_p_loads,
gens_by_bus=gens_by_bus,
bus_gs_fixed_shunts=bus_gs_fixed_shunts,
dc_inlet_branches_by_bus=dc_inlet_branches_by_bus,
dc_outlet_branches_by_bus=dc_outlet_branches_by_bus,
)
### add "blank" power flow expressions
libbranch.declare_expr_pf(
model=model,
index_set=branches_idx,
)
### add "blank" power flow expressions
model._contingencies = pyo.Set(initialize=contingencies.keys())
model._branches = pyo.Set(initialize=branches_idx)
### NOTE: important that this not be dense, we'll add elements
### as we find violations
model._contingency_set = pyo.Set(within=model._contingencies *
model._branches)
model.pfc = pyo.Expression(model._contingency_set)
## Do and store PTDF calculation
reference_bus = md.data['system']['reference_bus']
PTDF = ptdf_utils.VirtualPTDFMatrix(branches, buses, reference_bus, base_point, ptdf_options,\
contingencies=contingencies, branches_keys=branches_idx, buses_keys=buses_idx)
model._PTDF = PTDF
model._ptdf_options = ptdf_options
if not ptdf_options['lazy']:
raise RuntimeError("scopf only supports lazy constraint generation")
### add "blank" real power flow limits
libbranch.declare_ineq_p_branch_thermal_bounds(
model=model,
index_set=branches_idx,
branches=branches,
p_thermal_limits=None,
approximation_type=None,
)
### add "blank" real power flow limits
libbranch.declare_ineq_p_contingency_branch_thermal_bounds(
model=model,
index_set=model._contingency_set,
pc_thermal_limits=None,
approximation_type=None,
)
### add helpers for tracking monitored branches
lpu.add_monitored_flow_tracker(model)
### add initial branches to monitored set
lpu.add_initial_monitored_branches(model, branches, branches_idx,
ptdf_options, PTDF)
### declare the generator cost objective
libgen.declare_expression_pgqg_operating_cost(model=model,
index_set=gen_attrs['names'],
p_costs=gen_attrs['p_cost'])
obj_expr = sum(model.pg_operating_cost[gen_name]
for gen_name in model.pg_operating_cost)
if include_feasibility_slack:
obj_expr += penalty_expr
model.obj = pyo.Objective(expr=obj_expr)
return model, md
def create_btheta_dcopf_model(model_data, include_angle_diff_limits=False, include_feasibility_slack=False, pw_cost_model='delta'):
md = model_data.clone_in_service()
tx_utils.scale_ModelData_to_pu(md, inplace = True)
gens = dict(md.elements(element_type='generator'))
buses = dict(md.elements(element_type='bus'))
branches = dict(md.elements(element_type='branch'))
loads = dict(md.elements(element_type='load'))
shunts = dict(md.elements(element_type='shunt'))
dc_branches = dict(md.elements(element_type='dc_branch'))
gen_attrs = md.attributes(element_type='generator')
bus_attrs = md.attributes(element_type='bus')
branch_attrs = md.attributes(element_type='branch')
inlet_branches_by_bus, outlet_branches_by_bus = \
tx_utils.inlet_outlet_branches_by_bus(branches, buses)
gens_by_bus = tx_utils.gens_by_bus(buses, gens)
model = pe.ConcreteModel()
### declare (and fix) the loads at the buses
bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)
libbus.declare_var_pl(model, bus_attrs['names'], initialize=bus_p_loads)
model.pl.fix()
### declare the fixed shunts at the buses
_, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)
### declare the polar voltages
va_bounds = {k: (-pi, pi) for k in bus_attrs['va']}
libbus.declare_var_va(model, bus_attrs['names'],
initialize=tx_utils.radians_from_degrees_dict(bus_attrs['va']),
bounds=va_bounds
)
### include the feasibility slack for the bus balances
p_rhs_kwargs = {}
penalty_expr = None
if include_feasibility_slack:
p_marginal_slack_penalty = _validate_and_extract_slack_penalty(md)
p_rhs_kwargs, penalty_expr = _include_feasibility_slack(model, bus_attrs['names'], bus_p_loads,
gens_by_bus, gen_attrs, p_marginal_slack_penalty)
### fix the reference bus
ref_bus = md.data['system']['reference_bus']
ref_angle = md.data['system']['reference_bus_angle']
model.va[ref_bus].fix(radians(ref_angle))
### declare the generator real power
pg_init = {k: (gen_attrs['p_min'][k] + gen_attrs['p_max'][k]) / 2.0 for k in gen_attrs['pg']}
libgen.declare_var_pg(model, gen_attrs['names'], initialize=pg_init,
bounds=zip_items(gen_attrs['p_min'], gen_attrs['p_max'])
)
### declare the current flows in the branches
vr_init = {k: bus_attrs['vm'][k] * pe.cos(radians(bus_attrs['va'][k])) for k in bus_attrs['vm']}
vj_init = {k: bus_attrs['vm'][k] * pe.sin(radians(bus_attrs['va'][k])) for k in bus_attrs['vm']}
p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
p_lbub = dict()
for k in branches.keys():
k_pmax = p_max[k]
if k_pmax is None:
p_lbub[k] = (None, None)
else:
p_lbub[k] = (-k_pmax,k_pmax)
pf_bounds = p_lbub
pf_init = dict()
for branch_name, branch in branches.items():
from_bus = branch['from_bus']
to_bus = branch['to_bus']
y_matrix = tx_calc.calculate_y_matrix_from_branch(branch)
ifr_init = tx_calc.calculate_ifr(vr_init[from_bus], vj_init[from_bus], vr_init[to_bus],
vj_init[to_bus], y_matrix)
ifj_init = tx_calc.calculate_ifj(vr_init[from_bus], vj_init[from_bus], vr_init[to_bus],
vj_init[to_bus], y_matrix)
pf_init[branch_name] = tx_calc.calculate_p(ifr_init, ifj_init, vr_init[from_bus], vj_init[from_bus])
libbranch.declare_var_pf(model=model,
index_set=branch_attrs['names'],
initialize=pf_init,
bounds=pf_bounds
)
if dc_branches:
dcpf_bounds = dict()
for k, k_dict in dc_branches.items():
kp_max = k_dict['rating_long_term']
if kp_max is None:
dcpf_bounds[k] = (None, None)
else:
dcpf_bounds[k] = (-kp_max, kp_max)
libbranch.declare_var_dcpf(model=model,
index_set=dc_branches.keys(),
initialize=0.,
bounds=dcpf_bounds,
)
dc_inlet_branches_by_bus, dc_outlet_branches_by_bus = \
tx_utils.inlet_outlet_branches_by_bus(dc_branches, buses)
else:
dc_inlet_branches_by_bus = None
dc_outlet_branches_by_bus = None
### declare the branch power flow approximation constraints
libbranch.declare_eq_branch_power_btheta_approx(model=model,
index_set=branch_attrs['names'],
branches=branches
)
### declare the p balance
libbus.declare_eq_p_balance_dc_approx(model=model,
index_set=bus_attrs['names'],
bus_p_loads=bus_p_loads,
gens_by_bus=gens_by_bus,
bus_gs_fixed_shunts=bus_gs_fixed_shunts,
inlet_branches_by_bus=inlet_branches_by_bus,
outlet_branches_by_bus=outlet_branches_by_bus,
approximation_type=ApproximationType.BTHETA,
dc_inlet_branches_by_bus=dc_inlet_branches_by_bus,
dc_outlet_branches_by_bus=dc_outlet_branches_by_bus,
**p_rhs_kwargs
)
### declare the real power flow limits
libbranch.declare_ineq_p_branch_thermal_lbub(model=model,
index_set=branch_attrs['names'],
branches=branches,
p_thermal_limits=p_max,
approximation_type=ApproximationType.BTHETA
)
### declare angle difference limits on interconnected buses
if include_angle_diff_limits:
libbranch.declare_ineq_angle_diff_branch_lbub(model=model,
index_set=branch_attrs['names'],
branches=branches,
coordinate_type=CoordinateType.POLAR
)
# declare the generator cost objective
p_costs = gen_attrs['p_cost']
pw_pg_cost_gens = list(libgen.pw_gen_generator(gen_attrs['names'], costs=p_costs))
if len(pw_pg_cost_gens) > 0:
if pw_cost_model == 'delta':
libgen.declare_var_delta_pg(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
libgen.declare_pg_delta_pg_con(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
else:
libgen.declare_var_pg_cost(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
libgen.declare_piecewise_pg_cost_cons(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
libgen.declare_expression_pg_operating_cost(model=model, index_set=gen_attrs['names'], p_costs=p_costs, pw_formulation=pw_cost_model)
obj_expr = sum(model.pg_operating_cost[gen_name] for gen_name in model.pg_operating_cost)
if include_feasibility_slack:
obj_expr += penalty_expr
model.obj = pe.Objective(expr=obj_expr)
return model, md