def create_btheta_losses_dcopf_model(model_data,
relaxation_type=RelaxationType.SOC,
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'))
gen_attrs = md.attributes(element_type='generator')
bus_attrs = md.attributes(element_type='bus')
branch_attrs = md.attributes(element_type='branch')
load_attrs = md.attributes(element_type='load')
shunt_attrs = md.attributes(element_type='shunt')
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)
dva_initialize = {k: 0.0 for k in branch_attrs['names']}
libbranch.declare_var_dva(model,
branch_attrs['names'],
initialize=dva_initialize)
### 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()}
pf_bounds = {k: (-p_max[k], p_max[k]) for k in branches.keys()}
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])
pfl_bounds = {k: (0, p_max[k]**2) for k in branches.keys()}
pfl_init = {k: 0 for k in branches.keys()}
libbranch.declare_var_pf(model=model,
index_set=branch_attrs['names'],
initialize=pf_init,
bounds=pf_bounds)
libbranch.declare_var_pfl(model=model,
index_set=branch_attrs['names'],
initialize=pfl_init,
bounds=pfl_bounds)
### declare the angle difference constraint
libbranch.declare_eq_branch_dva(model=model,
index_set=branch_attrs['names'],
branches=branches)
### declare the branch power flow approximation constraints
libbranch.declare_eq_branch_power_btheta_approx(
model=model,
index_set=branch_attrs['names'],
branches=branches,
approximation_type=ApproximationType.BTHETA_LOSSES)
### declare the branch power loss approximation constraints
libbranch.declare_eq_branch_loss_btheta_approx(
model=model,
index_set=branch_attrs['names'],
branches=branches,
relaxation_type=relaxation_type)
### 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_LOSSES,
**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
def create_ptdf_losses_dcopf_model(model_data,
include_feasibility_slack=False,
ptdf_options=None,
pw_cost_model='delta'):
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'))
gen_attrs = md.attributes(element_type='generator')
bus_attrs = md.attributes(element_type='bus')
branch_attrs = md.attributes(element_type='branch')
load_attrs = md.attributes(element_type='load')
shunt_attrs = md.attributes(element_type='shunt')
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 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)
### declare net withdraw expression for use in PTDF power flows
libbus.declare_expr_p_net_withdraw_at_bus(
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,
)
### declare the current flows in the branches
p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
pfl_bounds = {k: (-p_max[k]**2, p_max[k]**2) for k in branches.keys()}
pfl_init = {k: 0 for k in branches.keys()}
## Do and store PTDF calculation
reference_bus = md.data['system']['reference_bus']
## We'll assume we have a solution to initialize from
base_point = BasePointType.SOLUTION
PTDF = ptdf_utils.PTDFLossesMatrix(branches, buses, reference_bus,
base_point, ptdf_options)
model._PTDF = PTDF
model._ptdf_options = ptdf_options
libbranch.declare_expr_pf(
model=model,
index_set=branch_attrs['names'],
)
libbranch.declare_var_pfl(model=model,
index_set=branch_attrs['names'],
initialize=pfl_init,
bounds=pfl_bounds)
### declare the branch power flow approximation constraints
libbranch.declare_eq_branch_power_ptdf_approx(
model=model,
index_set=branch_attrs['names'],
PTDF=PTDF,
abs_ptdf_tol=ptdf_options['abs_ptdf_tol'],
rel_ptdf_tol=ptdf_options['rel_ptdf_tol'],
)
### declare the branch power loss approximation constraints
libbranch.declare_eq_branch_loss_ptdf_approx(
model=model,
index_set=branch_attrs['names'],
PTDF=PTDF,
abs_ptdf_tol=ptdf_options['abs_ptdf_tol'],
rel_ptdf_tol=ptdf_options['rel_ptdf_tol'],
)
### declare the p balance
libbus.declare_eq_p_balance_ed(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,
include_losses=branch_attrs['names'],
**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.PTDF)
### 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
def _create_base_power_ac_model(model_data, 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'))
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)
bus_pairs = zip_items(branch_attrs['from_bus'], branch_attrs['to_bus'])
unique_bus_pairs = list(OrderedDict((val, None) for idx, val in bus_pairs.items()))
model = pe.ConcreteModel()
### declare (and fix) the loads at the buses
bus_p_loads, bus_q_loads = tx_utils.dict_of_bus_loads(buses, loads)
libbus.declare_var_pl(model, bus_attrs['names'], initialize=bus_p_loads)
libbus.declare_var_ql(model, bus_attrs['names'], initialize=bus_q_loads)
model.pl.fix()
model.ql.fix()
### declare the fixed shunts at the buses
bus_bs_fixed_shunts, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)
libbus.declare_var_vmsq(model=model,
index_set=bus_attrs['names'],
initialize={k: v**2 for k, v in bus_attrs['vm'].items()},
bounds=zip_items({k: v**2 for k, v in bus_attrs['v_min'].items()},
{k: v**2 for k, v in bus_attrs['v_max'].items()}))
libbranch.declare_var_c(model=model, index_set=unique_bus_pairs, initialize=1)
libbranch.declare_var_s(model=model, index_set=unique_bus_pairs, initialize=0)
### include the feasibility slack for the bus balances
p_rhs_kwargs = {}
q_rhs_kwargs = {}
if include_feasibility_slack:
p_marginal_slack_penalty, q_marginal_slack_penalty = _validate_and_extract_slack_penalties(md)
p_rhs_kwargs, q_rhs_kwargs, penalty_expr = _include_feasibility_slack(model, bus_attrs['names'],
bus_p_loads, bus_q_loads,
gens_by_bus, gen_attrs,
p_marginal_slack_penalty,
q_marginal_slack_penalty)
### declare the generator real and reactive 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'])
)
qg_init = {k: (gen_attrs['q_min'][k] + gen_attrs['q_max'][k]) / 2.0 for k in gen_attrs['qg']}
libgen.declare_var_qg(model, gen_attrs['names'], initialize=qg_init,
bounds=zip_items(gen_attrs['q_min'], gen_attrs['q_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']}
s_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
s_lbub = dict()
for k in branches.keys():
if s_max[k] is None:
s_lbub[k] = (None, None)
else:
s_lbub[k] = (-s_max[k],s_max[k])
pf_bounds = s_lbub
pt_bounds = s_lbub
qf_bounds = s_lbub
qt_bounds = s_lbub
pf_init = dict()
pt_init = dict()
qf_init = dict()
qt_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)
itr_init = tx_calc.calculate_itr(vr_init[from_bus], vj_init[from_bus], vr_init[to_bus],
vj_init[to_bus], y_matrix)
itj_init = tx_calc.calculate_itj(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])
pt_init[branch_name] = tx_calc.calculate_p(itr_init, itj_init, vr_init[to_bus], vj_init[to_bus])
qf_init[branch_name] = tx_calc.calculate_q(ifr_init, ifj_init, vr_init[from_bus], vj_init[from_bus])
qt_init[branch_name] = tx_calc.calculate_q(itr_init, itj_init, vr_init[to_bus], vj_init[to_bus])
libbranch.declare_var_pf(model=model,
index_set=branch_attrs['names'],
initialize=pf_init,
bounds=pf_bounds
)
libbranch.declare_var_pt(model=model,
index_set=branch_attrs['names'],
initialize=pt_init,
bounds=pt_bounds
)
libbranch.declare_var_qf(model=model,
index_set=branch_attrs['names'],
initialize=qf_init,
bounds=qf_bounds
)
libbranch.declare_var_qt(model=model,
index_set=branch_attrs['names'],
initialize=qt_init,
bounds=qt_bounds
)
### declare the branch power flow constraints
libbranch.declare_eq_branch_power(model=model,
index_set=branch_attrs['names'],
branches=branches
)
### declare the pq balances
libbus.declare_eq_p_balance(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,
**p_rhs_kwargs
)
libbus.declare_eq_q_balance(model=model,
index_set=bus_attrs['names'],
bus_q_loads=bus_q_loads,
gens_by_bus=gens_by_bus,
bus_bs_fixed_shunts=bus_bs_fixed_shunts,
inlet_branches_by_bus=inlet_branches_by_bus,
outlet_branches_by_bus=outlet_branches_by_bus,
**q_rhs_kwargs
)
### declare the thermal limits
libbranch.declare_ineq_s_branch_thermal_limit(model=model,
index_set=branch_attrs['names'],
branches=branches,
s_thermal_limits=s_max,
flow_type=FlowType.POWER
)
# declare angle difference limits on interconnected buses
libbranch.declare_ineq_angle_diff_branch_lbub_c_s(model=model,
index_set=branch_attrs['names'],
branches=branches
)
# 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)
q_costs = gen_attrs.get('q_cost', None)
if q_costs is not None:
pw_qg_cost_gens = list(libgen.pw_gen_generator(gen_attrs['names'], costs=q_costs))
if len(pw_qg_cost_gens) > 0:
if pw_cost_model == 'delta':
libgen.declare_var_delta_qg(model=model, index_set=pw_qg_cost_gens, q_costs=q_costs)
libgen.declare_qg_delta_qg_con(model=model, index_set=pw_qg_cost_gens, q_costs=q_costs)
else:
libgen.declare_var_qg_cost(model=model, index_set=pw_qg_cost_gens, q_costs=q_costs)
libgen.declare_piecewise_qg_cost_cons(model=model, index_set=pw_qg_cost_gens, q_costs=q_costs)
libgen.declare_expression_qg_operating_cost(model=model, index_set=gen_attrs['names'], q_costs=q_costs, pw_formulation=pw_cost_model)
obj_expr += sum(model.qg_operating_cost[gen_name] for gen_name in model.qg_operating_cost)
if include_feasibility_slack:
obj_expr += penalty_expr
model.obj = pe.Objective(expr=obj_expr)
return model, md
def create_scopf_model(model_data,
include_feasibility_slack=False,
base_point=BasePointType.FLATSTART,
ptdf_options=None,
pw_cost_model='delta'):
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_constraints(model, md, branches_idx,
ptdf_options, PTDF)
### 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 = pyo.Objective(expr=obj_expr)
return model, md
def create_riv_acopf_model(model_data,
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'))
gen_attrs = md.attributes(element_type='generator')
bus_attrs = md.attributes(element_type='bus')
branch_attrs = md.attributes(element_type='branch')
load_attrs = md.attributes(element_type='load')
shunt_attrs = md.attributes(element_type='shunt')
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, bus_q_loads = tx_utils.dict_of_bus_loads(buses, loads)
libbus.declare_var_pl(model, bus_attrs['names'], initialize=bus_p_loads)
libbus.declare_var_ql(model, bus_attrs['names'], initialize=bus_q_loads)
model.pl.fix()
model.ql.fix()
### declare the fixed shunts at the buses
bus_bs_fixed_shunts, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(
buses, shunts)
### declare the rectangular voltages
neg_v_max = map_items(op.neg, bus_attrs['v_max'])
vr_init = {
k: bus_attrs['vm'][k] * pe.cos(radians(bus_attrs['va'][k]))
for k in bus_attrs['vm']
}
libbus.declare_var_vr(model,
bus_attrs['names'],
initialize=vr_init,
bounds=zip_items(neg_v_max, bus_attrs['v_max']))
vj_init = {
k: bus_attrs['vm'][k] * pe.sin(radians(bus_attrs['va'][k]))
for k in bus_attrs['vm']
}
libbus.declare_var_vj(model,
bus_attrs['names'],
initialize=vj_init,
bounds=zip_items(neg_v_max, bus_attrs['v_max']))
### include the feasibility slack for the bus balances
p_rhs_kwargs = {}
q_rhs_kwargs = {}
if include_feasibility_slack:
p_marginal_slack_penalty, q_marginal_slack_penalty = _validate_and_extract_slack_penalties(
md)
p_rhs_kwargs, q_rhs_kwargs, penalty_expr = _include_feasibility_slack(
model, bus_attrs['names'], bus_p_loads, bus_q_loads, gens_by_bus,
gen_attrs, p_marginal_slack_penalty, q_marginal_slack_penalty)
### fix the reference bus
ref_bus = md.data['system']['reference_bus']
ref_angle = md.data['system']['reference_bus_angle']
if ref_angle != 0.0:
libbus.declare_eq_ref_bus_nonzero(model, ref_angle, ref_bus)
else:
model.vj[ref_bus].fix(0.0)
model.vr[ref_bus].setlb(0.0)
### declare the generator real and reactive 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']))
qg_init = {
k: (gen_attrs['q_min'][k] + gen_attrs['q_max'][k]) / 2.0
for k in gen_attrs['qg']
}
libgen.declare_var_qg(model,
gen_attrs['names'],
initialize=qg_init,
bounds=zip_items(gen_attrs['q_min'],
gen_attrs['q_max']))
### declare the current flows in the branches
branch_currents = tx_utils.dict_of_branch_currents(branches, buses)
s_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
if_bounds = dict()
it_bounds = dict()
ifr_init = dict()
ifj_init = dict()
itr_init = dict()
itj_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[branch_name] = tx_calc.calculate_ifr(vr_init[from_bus],
vj_init[from_bus],
vr_init[to_bus],
vj_init[to_bus],
y_matrix)
ifj_init[branch_name] = tx_calc.calculate_ifj(vr_init[from_bus],
vj_init[from_bus],
vr_init[to_bus],
vj_init[to_bus],
y_matrix)
itr_init[branch_name] = tx_calc.calculate_itr(vr_init[from_bus],
vj_init[from_bus],
vr_init[to_bus],
vj_init[to_bus],
y_matrix)
itj_init[branch_name] = tx_calc.calculate_itj(vr_init[from_bus],
vj_init[from_bus],
vr_init[to_bus],
vj_init[to_bus],
y_matrix)
if s_max[branch_name] is None:
if_bounds[branch_name] = (None, None)
it_bounds[branch_name] = (None, None)
else:
if_max = s_max[branch_name] / buses[branches[branch_name]
['from_bus']]['v_min']
it_max = s_max[branch_name] / buses[branches[branch_name]
['to_bus']]['v_min']
if_bounds[branch_name] = (-if_max, if_max)
it_bounds[branch_name] = (-it_max, it_max)
libbranch.declare_var_ifr(model=model,
index_set=branch_attrs['names'],
initialize=ifr_init,
bounds=if_bounds)
libbranch.declare_var_ifj(model=model,
index_set=branch_attrs['names'],
initialize=ifj_init,
bounds=if_bounds)
libbranch.declare_var_itr(model=model,
index_set=branch_attrs['names'],
initialize=itr_init,
bounds=it_bounds)
libbranch.declare_var_itj(model=model,
index_set=branch_attrs['names'],
initialize=itj_init,
bounds=it_bounds)
ir_init = dict()
ij_init = dict()
for bus_name, bus in buses.items():
ir_expr = sum([
ifr_init[branch_name]
for branch_name in outlet_branches_by_bus[bus_name]
])
ir_expr += sum([
itr_init[branch_name]
for branch_name in inlet_branches_by_bus[bus_name]
])
ij_expr = sum([
ifj_init[branch_name]
for branch_name in outlet_branches_by_bus[bus_name]
])
ij_expr += sum([
itj_init[branch_name]
for branch_name in inlet_branches_by_bus[bus_name]
])
if bus_gs_fixed_shunts[bus_name] != 0.0:
ir_expr += bus_gs_fixed_shunts[bus_name] * vr_init[bus_name]
ij_expr += bus_gs_fixed_shunts[bus_name] * vj_init[bus_name]
if bus_bs_fixed_shunts[bus_name] != 0.0:
ir_expr += bus_bs_fixed_shunts[bus_name] * vj_init[bus_name]
ij_expr += bus_bs_fixed_shunts[bus_name] * vr_init[bus_name]
ir_init[bus_name] = ir_expr
ij_init[bus_name] = ij_expr
# TODO: Implement better bounds (?) for these aggregated variables -- note, these are unbounded in old Egret
libbus.declare_var_ir_aggregation_at_bus(model=model,
index_set=bus_attrs['names'],
initialize=ir_init,
bounds=(None, None))
libbus.declare_var_ij_aggregation_at_bus(model=model,
index_set=bus_attrs['names'],
initialize=ij_init,
bounds=(None, None))
### declare the branch current flow constraints
libbranch.declare_eq_branch_current(model=model,
index_set=branch_attrs['names'],
branches=branches)
### declare the ir/ij_aggregation constraints
libbus.declare_eq_i_aggregation_at_bus(
model=model,
index_set=bus_attrs['names'],
bus_bs_fixed_shunts=bus_bs_fixed_shunts,
bus_gs_fixed_shunts=bus_gs_fixed_shunts,
inlet_branches_by_bus=inlet_branches_by_bus,
outlet_branches_by_bus=outlet_branches_by_bus)
### declare the pq balances
libbus.declare_eq_p_balance_with_i_aggregation(
model=model,
index_set=bus_attrs['names'],
bus_p_loads=bus_p_loads,
gens_by_bus=gens_by_bus,
**p_rhs_kwargs)
libbus.declare_eq_q_balance_with_i_aggregation(
model=model,
index_set=bus_attrs['names'],
bus_q_loads=bus_q_loads,
gens_by_bus=gens_by_bus,
**q_rhs_kwargs)
### declare the thermal limits
libbranch.declare_ineq_s_branch_thermal_limit(
model=model,
index_set=branch_attrs['names'],
branches=branches,
s_thermal_limits=s_max,
flow_type=FlowType.CURRENT)
### declare the voltage min and max inequalities
libbus.declare_ineq_vm_bus_lbub(model=model,
index_set=bus_attrs['names'],
buses=buses,
coordinate_type=CoordinateType.RECTANGULAR)
### declare angle difference limits on interconnected buses
libbranch.declare_ineq_angle_diff_branch_lbub(
model=model,
index_set=branch_attrs['names'],
branches=branches,
coordinate_type=CoordinateType.RECTANGULAR)
### 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)
q_costs = gen_attrs.get('q_cost', None)
if q_costs is not None:
pw_qg_cost_gens = list(
libgen.pw_gen_generator(gen_attrs['names'], costs=q_costs))
if len(pw_qg_cost_gens) > 0:
if pw_cost_model == 'delta':
libgen.declare_var_delta_qg(model=model,
index_set=pw_qg_cost_gens,
q_costs=q_costs)
libgen.declare_qg_delta_qg_con(model=model,
index_set=pw_qg_cost_gens,
q_costs=q_costs)
else:
libgen.declare_var_qg_cost(model=model,
index_set=pw_qg_cost_gens,
q_costs=q_costs)
libgen.declare_piecewise_qg_cost_cons(
model=model, index_set=pw_qg_cost_gens, q_costs=q_costs)
libgen.declare_expression_qg_operating_cost(
model=model,
index_set=gen_attrs['names'],
q_costs=q_costs,
pw_formulation=pw_cost_model)
obj_expr += sum(model.qg_operating_cost[gen_name]
for gen_name in model.qg_operating_cost)
if include_feasibility_slack:
obj_expr += penalty_expr
model.obj = pe.Objective(expr=obj_expr)
return model, md
def create_copperplate_dispatch_approx_model(model_data,
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'))
gen_attrs = md.attributes(element_type='generator')
bus_attrs = md.attributes(element_type='bus')
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 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(
model_data)
p_rhs_kwargs, penalty_expr = _include_system_feasibility_slack(
model, bus_p_loads, gen_attrs, p_marginal_slack_penalty)
### declare the p balance
libbus.declare_eq_p_balance_ed(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,
**p_rhs_kwargs)
### 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
