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import pytest
import pyomo.environ as pyo
# import src.topupopt.problems.esipp.utils as utils
from src.topupopt.data.misc.utils import generate_pseudo_unique_key
from src.topupopt.problems.esipp.problem import InfrastructurePlanningProblem
from src.topupopt.problems.esipp.network import Arcs, Network
from src.topupopt.problems.esipp.network import ArcsWithoutStaticLosses
from src.topupopt.problems.esipp.resource import ResourcePrice
# from src.topupopt.problems.esipp.utils import compute_cost_volume_metrics
from src.topupopt.problems.esipp.utils import statistics
from src.topupopt.problems.esipp.time import EconomicTimeFrame
# from src.topupopt.problems.esipp.converter import Converter
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from test_esipp import build_solve_ipp
# *****************************************************************************
# *****************************************************************************
class TestESIPPProblem:
# *************************************************************************
# *************************************************************************
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@pytest.mark.parametrize(
"use_sos_arcs, arc_sos_weight_key",
[(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_NONE),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_CAP),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_COST),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_SPEC_CAP),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_SPEC_COST),
(False, None)]
)
def test_single_network_single_arc_problem(self, use_sos_arcs, arc_sos_weight_key):
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# assessment
q = 0
tf = EconomicTimeFrame(
discount_rate=3.5/100,
reporting_periods={q: (0, 1)},
reporting_period_durations={q: (365 * 24 * 3600, 365 * 24 * 3600)},
time_intervals={q: (0, 1, 2)},
time_interval_durations={q: (1, 1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
# import node
node_IMP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
},
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
base_flow={(q, 0): 0.50, (q, 1): 0.00, (q, 2): 1.00},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
efficiency={qk: 0.5 for qk in tf.qk()},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# no sos, regular time intervals
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ipp = build_solve_ipp(
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use_sos_arcs=use_sos_arcs,
arc_sos_weight_key=arc_sos_weight_key,
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perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
time_frame=tf,
networks={"mynet": mynet},
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
simplify_problem=False,
)
# *********************************************************************
# *********************************************************************
# validation
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 24
assert ipp.results["Problem"][0]["Number of variables"] == 22
assert ipp.results["Problem"][0]["Number of nonzeros"] == 49
# the arc should be installed since it is required for feasibility
assert (
True
in ipp.networks["mynet"]
.edges[(node_IMP, node_A, 0)][Network.KEY_ARC_TECH]
.options_selected
)
# the flows should be 1.0, 0.0 and 2.0
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, q, 0)]),
1.0,
abs_tol=1e-6,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, q, 1)]),
0.0,
abs_tol=1e-6,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, q, 2)]),
2.0,
abs_tol=1e-6,
)
# arc amplitude should be two
assert math.isclose(
pyo.value(ipp.instance.var_v_amp_gllj[("mynet", node_IMP, node_A, 0)]),
2.0,
abs_tol=0.01,
)
# capex should be four
assert math.isclose(pyo.value(ipp.instance.var_capex), 4.0, abs_tol=1e-3)
# sdncf should be -5.7
assert math.isclose(pyo.value(ipp.instance.var_sdncf_q[q]), -5.7, abs_tol=1e-3)
# the objective function should be -9.7
assert math.isclose(pyo.value(ipp.instance.obj_f), -9.7, abs_tol=1e-3)
# *************************************************************************
# *************************************************************************
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def test_single_network_two_arcs_problem(self):
# TODO: test simplifying this problem
# assessment
q = 0
tf = EconomicTimeFrame(
discount_rate=3.5/100,
reporting_periods={q: (0, 1)},
reporting_period_durations={q: (365 * 24 * 3600, 365 * 24 * 3600)},
time_intervals={q: (0, 1, 2)},
time_interval_durations={q: (1, 1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
# import node
node_IMP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
}
)
# export node
node_EXP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_export_node(
node_key=node_EXP,
prices={
qpk: ResourcePrice(prices=0.5, volumes=None)
for qpk in tf.qpk()
}
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
base_flow={(q, 0): 0.50, (q, 1): -1.50, (q, 2): 1.00},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
efficiency={qk: 0.5 for qk in tf.qk()},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# arc AE
arc_tech_AE = Arcs(
name="any",
efficiency={qk: 0.8 for qk in tf.qk()},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_A, node_key_b=node_EXP, arcs=arc_tech_AE)
# no sos, regular time intervals
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ipp = build_solve_ipp(
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# use_sos_arcs=use_sos_arcs,
# arc_sos_weight_key=arc_sos_weight_key,
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perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
time_frame=tf,
networks={"mynet": mynet},
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
simplify_problem=False,
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 42
assert ipp.results["Problem"][0]["Number of variables"] == 40
assert ipp.results["Problem"][0]["Number of nonzeros"] == 95
# *********************************************************************
# *********************************************************************
# validation
# the arc should be installed since it is required for feasibility
assert (
True
in ipp.networks["mynet"]
.edges[(node_IMP, node_A, 0)][Network.KEY_ARC_TECH]
.options_selected
)
# flows
true_v_glljqk = {
("mynet", node_IMP, node_A, 0, q, 0): 1,
("mynet", node_IMP, node_A, 0, q, 1): 0,
("mynet", node_IMP, node_A, 0, q, 2): 2,
("mynet", node_A, node_EXP, 0, q, 0): 0,
("mynet", node_A, node_EXP, 0, q, 1): 1.5,
("mynet", node_A, node_EXP, 0, q, 2): 0
}
for key, v in true_v_glljqk.items():
assert math.isclose(pyo.value(ipp.instance.var_v_glljqk[key]), v, abs_tol=1e-6)
# arc amplitude should be two
assert math.isclose(
pyo.value(ipp.instance.var_v_amp_gllj[("mynet", node_IMP, node_A, 0)]),
2.0,
abs_tol=0.01,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_amp_gllj[("mynet", node_A, node_EXP, 0)]),
1.5,
abs_tol=0.01,
)
# capex should be four
assert math.isclose(pyo.value(ipp.instance.var_capex), 7.5, abs_tol=1e-3)
# sdncf should be -5.7+0.6*(0.966+0.934)
assert math.isclose(pyo.value(ipp.instance.var_sdncf_q[q]), -5.7+0.6*(0.966+0.934), abs_tol=1e-3)
# the objective function should be -9.7+0.6*(0.966+0.934)
assert math.isclose(pyo.value(ipp.instance.obj_f), -9.7+0.6*(0.966+0.934)-3.5, abs_tol=1e-3)
# *************************************************************************
# *************************************************************************
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@pytest.mark.parametrize(
"use_sos_arcs, arc_sos_weight_key",
[(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_NONE),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_CAP),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_COST),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_SPEC_CAP),
(True, InfrastructurePlanningProblem.SOS1_ARC_WEIGHTS_SPEC_COST),
(False, None)]
)
def test_single_network_single_arc_problem_simpler(self, use_sos_arcs, arc_sos_weight_key):
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# assessment
q = 0
tf = EconomicTimeFrame(
discount_rate=3.5/100,
reporting_periods={q: (0, 1)},
reporting_period_durations={q: (365 * 24 * 3600, 365 * 24 * 3600)},
time_intervals={q: (0, 1, 2)},
time_interval_durations={q: (1, 1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
# import node
node_IMP = "thatimpnode"
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
},
)
# other nodes
node_A = "thatnodea"
mynet.add_source_sink_node(
node_key=node_A,
# base_flow=[0.5, 0.0, 1.0],
base_flow={(q, 0): 0.50, (q, 1): 0.00, (q, 2): 1.00},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
efficiency={qk: 0.5 for qk in tf.qk()},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# no sos, regular time intervals
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ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
time_frame=tf,
networks={"mynet": mynet},
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
simplify_problem=True,
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 16 # 20
assert ipp.results["Problem"][0]["Number of variables"] == 15 # 19
assert ipp.results["Problem"][0]["Number of nonzeros"] == 28 # 36
# *********************************************************************
# *********************************************************************
# validation
# the arc should be installed since it is required for feasibility
assert (
True
in ipp.networks["mynet"]
.edges[(node_IMP, node_A, 0)][Network.KEY_ARC_TECH]
.options_selected
)
# capex should be four
assert math.isclose(pyo.value(ipp.instance.var_capex), 4.0, abs_tol=1e-3)
# the objective function should be -9.7
assert math.isclose(pyo.value(ipp.instance.obj_f), -9.7, abs_tol=1e-3)
# *************************************************************************
# *************************************************************************
def test_problem_two_scenarios(self):
# number_intraperiod_time_intervals = 4
nominal_discount_rate = 0.035
assessment_weights = {0: 0.7, 1: 0.3}
tf = EconomicTimeFrame(
discount_rate=nominal_discount_rate,
reporting_periods={0: (0, 1), 1: (0, 1, 2)},
reporting_period_durations={0: (1, 1), 1: (1, 1, 1)}, # does not matter
time_intervals={0: (0, 1, 2), 1: (0, 1)},
time_interval_durations={0: (1, 1, 1), 1: (1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
node_IMP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
},
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
base_flow={
(0, 0): 0.50,
(0, 1): 0.00,
(0, 2): 1.00,
(1, 0): 1.25,
(1, 1): 0.30,
},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
# efficiency=[0.5, 0.5, 0.5],
efficiency={(0, 0): 0.5, (0, 1): 0.5, (0, 2): 0.5, (1, 0): 0.5, (1, 1): 0.5},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# no sos, regular time intervals
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ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
networks={"mynet": mynet},
converters={},
time_frame=tf,
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
assessment_weights=assessment_weights,
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 42
assert ipp.results["Problem"][0]["Number of variables"] == 38
assert ipp.results["Problem"][0]["Number of nonzeros"] == 87
# *********************************************************************
# validation
# the arc should be installed since it is the only feasible solution
assert (
True
in ipp.networks["mynet"]
.edges[(node_IMP, node_A, 0)][Network.KEY_ARC_TECH]
.options_selected
)
# the flows should be 1.0, 0.0 and 2.0
true_v_glljqk = {
("mynet", node_IMP, node_A, 0, 0, 0): 1,
("mynet", node_IMP, node_A, 0, 0, 1): 0,
("mynet", node_IMP, node_A, 0, 0, 2): 2,
("mynet", node_IMP, node_A, 0, 1, 0): 2.5,
("mynet", node_IMP, node_A, 0, 1, 1): 0.6,
}
for key, v in true_v_glljqk.items():
assert math.isclose(pyo.value(ipp.instance.var_v_glljqk[key]), v, abs_tol=1e-6)
# arc amplitude should be two
assert math.isclose(
pyo.value(ipp.instance.var_v_amp_gllj[("mynet", node_IMP, node_A, 0)]),
2.5,
abs_tol=0.01,
)
# capex should be four
assert math.isclose(pyo.value(ipp.instance.var_capex), 4.5, abs_tol=1e-3)
# sdncf_q[0] should be -5.7
assert math.isclose(pyo.value(ipp.instance.var_sdncf_q[0]), -5.7, abs_tol=1e-3)
# the objective function should be -9.7
assert math.isclose(pyo.value(ipp.instance.obj_f), -11.096, abs_tol=3e-3)
# *************************************************************************
# *************************************************************************
def test_problem_two_scenarios_simpler(self):
# number_intraperiod_time_intervals = 4
nominal_discount_rate = 0.035
assessment_weights = {0: 0.7, 1: 0.3}
tf = EconomicTimeFrame(
discount_rate=nominal_discount_rate,
reporting_periods={0: (0, 1), 1: (0, 1, 2)},
reporting_period_durations={0: (1, 1), 1: (1, 1, 1)}, # does not matter
time_intervals={0: (0, 1, 2), 1: (0, 1)},
time_interval_durations={0: (1, 1, 1), 1: (1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
node_IMP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
},
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
base_flow={
(0, 0): 0.50,
(0, 1): 0.00,
(0, 2): 1.00,
(1, 0): 1.25,
(1, 1): 0.30,
},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
# efficiency=[0.5, 0.5, 0.5],
efficiency={(0, 0): 0.5, (0, 1): 0.5, (0, 2): 0.5, (1, 0): 0.5, (1, 1): 0.5},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# no sos, regular time intervals
Pedro L. Magalhães
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ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
networks={"mynet": mynet},
converters={},
time_frame=tf,
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
assessment_weights=assessment_weights,
simplify_problem=True
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 28 # 42
assert ipp.results["Problem"][0]["Number of variables"] == 25 # 38
assert ipp.results["Problem"][0]["Number of nonzeros"] == 51 # 87
# *********************************************************************
# validation
# capex should be 4.5
assert math.isclose(pyo.value(ipp.instance.var_capex), 4.5, abs_tol=1e-3)
# the objective function should be -11.096
assert math.isclose(pyo.value(ipp.instance.obj_f), -11.096, abs_tol=3e-3)
# *************************************************************************
# *************************************************************************
def test_problem_two_scenarios_two_discount_rates(self):
# two discount rates
assessment_weights = {0: 0.7, 1: 0.3}
tf = EconomicTimeFrame(
discount_rates_q={0: (0.035, 0.035), 1: (0.1, 0.1, 0.1)},
reporting_periods={0: (0, 1), 1: (0, 1, 2)},
reporting_period_durations={0: (1, 1), 1: (1, 1, 1)}, # does not matter
time_intervals={0: (0, 1, 2), 1: (0, 1)},
time_interval_durations={0: (1, 1, 1), 1: (1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
node_IMP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
},
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
base_flow={
(0, 0): 0.50,
(0, 1): 0.00,
(0, 2): 1.00,
(1, 0): 1.25,
(1, 1): 0.30,
},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
# efficiency=[0.5, 0.5, 0.5],
efficiency={(0, 0): 0.5, (0, 1): 0.5, (0, 2): 0.5, (1, 0): 0.5, (1, 1): 0.5},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# no sos, regular time intervals
Pedro L. Magalhães
committed
ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
networks={"mynet": mynet},
converters={},
time_frame=tf,
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
assessment_weights=assessment_weights,
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 42
assert ipp.results["Problem"][0]["Number of variables"] == 38
assert ipp.results["Problem"][0]["Number of nonzeros"] == 87
# *********************************************************************
# validation
# the arc should be installed since it is the only feasible solution
assert (
True
in ipp.networks["mynet"]
.edges[(node_IMP, node_A, 0)][Network.KEY_ARC_TECH]
.options_selected
)
# the flows should be 1.0, 0.0 and 2.0
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, 0, 0)]),
1.0,
abs_tol=1e-6,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, 0, 1)]),
0.0,
abs_tol=1e-6,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, 0, 2)]),
2.0,
abs_tol=1e-6,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, 1, 0)]),
2.5,
abs_tol=1e-6,
)
assert math.isclose(
pyo.value(ipp.instance.var_v_glljqk[("mynet", node_IMP, node_A, 0, 1, 1)]),
0.6,
abs_tol=1e-6,
)
# arc amplitude should be two
assert math.isclose(
pyo.value(ipp.instance.var_v_amp_gllj[("mynet", node_IMP, node_A, 0)]),
2.5,
abs_tol=0.01,
)
# capex should be 4.5
assert math.isclose(pyo.value(ipp.instance.var_capex), 4.5, abs_tol=1e-3)
# sdncf_q[0] should be -5.7
assert math.isclose(pyo.value(ipp.instance.var_sdncf_q[0]), -5.7, abs_tol=1e-3)
# the objective function should be -10.80213032963115
assert math.isclose(pyo.value(ipp.instance.obj_f), -10.80213032963115, abs_tol=3e-3)
# *************************************************************************
# *************************************************************************
def test_problem_two_scenarios_two_discount_rates_simpler(self):
# two discount rates
assessment_weights = {0: 0.7, 1: 0.3}
tf = EconomicTimeFrame(
discount_rates_q={0: (0.035, 0.035), 1: (0.1, 0.1, 0.1)},
reporting_periods={0: (0, 1), 1: (0, 1, 2)},
reporting_period_durations={0: (1, 1), 1: (1, 1, 1)}, # does not matter
time_intervals={0: (0, 1, 2), 1: (0, 1)},
time_interval_durations={0: (1, 1, 1), 1: (1, 1)},
)
# 2 nodes: one import, one regular
mynet = Network()
node_IMP = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=node_IMP,
prices={
qpk: ResourcePrice(prices=1.0, volumes=None)
for qpk in tf.qpk()
},
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
base_flow={
(0, 0): 0.50,
(0, 1): 0.00,
(0, 2): 1.00,
(1, 0): 1.25,
(1, 1): 0.30,
},
)
# arc IA
arc_tech_IA = Arcs(
name="any",
# efficiency=[0.5, 0.5, 0.5],
efficiency={(0, 0): 0.5, (0, 1): 0.5, (0, 2): 0.5, (1, 0): 0.5, (1, 1): 0.5},
efficiency_reverse=None,
static_loss=None,
capacity=[3],
minimum_cost=[2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
validate=False,
)
mynet.add_directed_arc(node_key_a=node_IMP, node_key_b=node_A, arcs=arc_tech_IA)
# no sos, regular time intervals
Pedro L. Magalhães
committed
ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
networks={"mynet": mynet},
converters={},
time_frame=tf,
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={},
assessment_weights=assessment_weights,
simplify_problem=True
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 28 # 42
assert ipp.results["Problem"][0]["Number of variables"] == 25 # 38
assert ipp.results["Problem"][0]["Number of nonzeros"] == 51 # 87
# *********************************************************************
# validation
# arc amplitude should be two
assert math.isclose(
pyo.value(ipp.instance.var_v_amp_gllj[("mynet", node_IMP, node_A, 0)]),
2.5,
abs_tol=0.01,
)
# capex should be four
assert math.isclose(pyo.value(ipp.instance.var_capex), 4.5, abs_tol=1e-3)
# sdncf_q[0] should be -5.7
# assert math.isclose(pyo.value(ipp.instance.var_sdncf_q[0]), -5.7, abs_tol=1e-3)
# the objective function should be -10.80213032963115 (or -10.8027723516153)
assert math.isclose(pyo.value(ipp.instance.obj_f), -10.80213032963115, abs_tol=3e-3)
# *************************************************************************
# *************************************************************************
# problem with two symmetrical nodes and one undirected arc
# problem with symmetrical nodes and one undirected arc with diff. tech.
# problem with symmetrical nodes and one undirected arc, irregular steps
# same problem as the previous one, except with interface variables
# problem with two symmetrical nodes and one undirected arc, w/ simple sos1
def test_isolated_undirected_network(self):
q = 0
tf = EconomicTimeFrame(
discount_rate=3.5/100,
reporting_periods={q: (0,)},
reporting_period_durations={q: (365 * 24 * 3600,)},
time_intervals={q: (0,1,2,3)},
time_interval_durations={q: (1,1,1,1)},
)
# 4 nodes: one import, one export, two supply/demand nodes
mynet = Network()
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
# base_flow=[1, -1, 0.5, -0.5],
base_flow={(0, 0): 1, (0, 1): -1, (0, 2): 0.5, (0, 3): -0.5},
)
node_B = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_B,
# base_flow=[-1, 1, -0.5, 0.5],
base_flow={(0, 0): -1, (0, 1): 1, (0, 2): -0.5, (0, 3): 0.5},
)
# add arcs
# undirected arc
arc_tech_AB = ArcsWithoutStaticLosses(
name="any",
# efficiency=[1, 1, 1, 1],
efficiency={(0, 0): 1, (0, 1): 1, (0, 2): 1, (0, 3): 1},
efficiency_reverse=None,
capacity=[0.5, 0.75, 1.0, 1.25, 1.5, 2.0],
minimum_cost=[10, 10.1, 10.2, 10.3, 10.4, 10.5],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
)
arc_key_AB_und = mynet.add_undirected_arc(
node_key_a=node_A, node_key_b=node_B, arcs=arc_tech_AB
)
# no sos, regular time intervals
Pedro L. Magalhães
committed
ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False, # True,
print_solver_output=False,
time_frame=tf,
networks={"mynet": mynet},
static_losses_mode=True, # just to reach a line,
mandatory_arcs=[],
max_number_parallel_arcs={}
)
assert ipp.has_peak_total_assessments() # TODO: make sure this is true
assert ipp.results["Problem"][0]["Number of constraints"] == 34
assert ipp.results["Problem"][0]["Number of variables"] == 28
assert ipp.results["Problem"][0]["Number of nonzeros"] == 105
# *********************************************************************
# *********************************************************************
# validation
# the arc should be installed since it is the only feasible solution
assert (
True
in ipp.networks["mynet"]
.edges[(node_A, node_B, arc_key_AB_und)][Network.KEY_ARC_TECH]
.options_selected
)
# there should be no opex (imports or exports), only capex from arcs
assert pyo.value(ipp.instance.var_sdncf_q[q]) == 0
assert pyo.value(ipp.instance.var_capex) > 0
assert (
pyo.value(
ipp.instance.var_capex_arc_gllj[("mynet", node_A, node_B, arc_key_AB_und)]
)
> 0
)
# *************************************************************************
# *************************************************************************
def test_isolated_undirected_network_diff_tech(self):
# time frame
q = 0
tf = EconomicTimeFrame(
discount_rate=3.5/100,
reporting_periods={q: (0,)},
reporting_period_durations={q: (365 * 24 * 3600,)},
time_intervals={q: (0,1,2,3)},
time_interval_durations={q: (1,1,1,1)},
)
# 4 nodes: one import, one export, two supply/demand nodes
mynet = Network()
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
# base_flow=[1, -1, 0.5, -0.5]
base_flow={(0, 0): 1, (0, 1): -1, (0, 2): 0.5, (0, 3): -0.5},
)
node_B = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_B,
# base_flow=[-1.25, 1, -0.625, 0.5]
base_flow={(0, 0): -1.25, (0, 1): 1.0, (0, 2): -0.625, (0, 3): 0.5},
)
# add arcs
# undirected arc
arc_tech_AB = ArcsWithoutStaticLosses(
name="any",
# efficiency=[0.8, 1.0, 0.8, 1.0],
efficiency={(0, 0): 0.8, (0, 1): 1.0, (0, 2): 0.8, (0, 3): 1.0},
efficiency_reverse=None,
capacity=[1.25, 2.5],
minimum_cost=[10, 15],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
)
arc_key_AB_und = mynet.add_undirected_arc(
node_key_a=node_A, node_key_b=node_B, arcs=arc_tech_AB
)
# no sos, regular time intervals
Pedro L. Magalhães
committed
ipp = build_solve_ipp(
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solver_options={},
perform_analysis=False,
plot_results=False,
print_solver_output=False,
time_frame=tf,
networks={"mynet": mynet},
static_losses_mode=InfrastructurePlanningProblem.STATIC_LOSS_MODE_DEP,
mandatory_arcs=[],
max_number_parallel_arcs={}
)
assert ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 34
assert ipp.results["Problem"][0]["Number of variables"] == 24
assert ipp.results["Problem"][0]["Number of nonzeros"] == 77
# *********************************************************************
# *********************************************************************
# validation
# the arc should be installed since it is the only feasible solution
assert (
True
in ipp.networks["mynet"]
.edges[(node_A, node_B, arc_key_AB_und)][Network.KEY_ARC_TECH]
.options_selected
)
# there should be no opex (imports or exports), only capex from arcs
assert pyo.value(ipp.instance.var_sdncf_q[q]) == 0
assert pyo.value(ipp.instance.var_capex) > 0
assert (
pyo.value(