def test_update_vertices():
# TEST_UPDATE_VERTICES() - test method update_vertices(), which for this
# base class of LocalAssetModel does practically nothing and must be
# redefined by child classes that represent flesible assets.
print('Running LocalAssetModel.test_update_vertices()')
pf = 'pass'
# Create a test Market object.
test_market = Market
# Create and store a TimeInterval object.
dt = datetime.now() # datetime that may be used for most datetime arguments
time_interval = TimeInterval(dt, timedelta(hours=1), test_market, dt, dt)
test_market.timeIntervals = [time_interval]
# Create a test LocalAssetModel object.
test_model = LocalAssetModel()
# Create and store a scheduled power IntervalValue in the active time interval.
test_model.scheduledPowers = [
IntervalValue(test_model, time_interval, test_market, MeasurementType.ScheduledPower, 50)]
# Create a LocalAsset object and its maximum and minimum powers.
test_object = LocalAsset()
test_object.maximumPower = 200
test_object.minimumPower = 0
# Have the LocalAsset model and object cross reference one another.
test_object.model = test_model
test_model.object = test_object
## TEST 1
print('- Test 1: Basic operation')
test_model.update_vertices(test_market)
print(' - the method ran without errors')
if len(test_model.activeVertices) != 1:
pf = 'fail'
print(' - there is an unexpected number of active vertices')
else:
print(' - the expected number of active vertices was found')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_calculate_reserve_margin():
# TEST_LAM_CALCULATE_RESERVE_MARGIN() - a LocalAssetModel ("LAM") class
# method NOTE: Reserve margins are introduced but not fully integrated into
# code in early template versions.
# CASES:
# 1. uses hard maximum if no active vertices exist
# 2. vertices exist
# 2.1 uses maximum vertex power if it is less than hard power constraint
# 2.2 uses hard constraint if it is less than maximum vertex power
# 2.3 upper flex power is greater than scheduled power assigns correct
# positive reserve margin
# 2.4 upperflex power less than scheduled power assigns zero value to
# reserve margin.
print('Running LocalAssetModel.test_calculate_reserve_margin()')
pf = 'pass'
# Establish test market
test_mkt = Market()
# Establish test market with an active time interval
# Note: modified 1/29/18 due to new TimeInterval constructor
dt = datetime.now()
at = dt
# NOTE: def Hours() corrects behavior of Matlab hours().
dur = timedelta(hours=1)
mkt = test_mkt
mct = dt
# st = datetime(date)
st = datetime.combine(date.today(), time())
ti = TimeInterval(at, dur, mkt, mct, st)
# Store time interval
test_mkt.timeIntervals = [ti]
# Establish a test object that is a LocalAsset with assigned maximum power
test_object = LocalAsset()
test_object.maximumPower = 100
# Establish test object that is a LocalAssetModel
test_model = LocalAssetModel()
test_model.scheduledPowers = [
IntervalValue(test_model, ti, test_mkt, MeasurementType.ScheduledPower, 0.0)]
# Allow object and model to cross-reference one another.
test_object.model = test_model
test_model.object = test_object
# Run the first test case.
test_model.calculate_reserve_margin(test_mkt)
print('- method ran without errors')
if len(test_model.reserveMargins) != 1:
raise Exception('- an unexpected number of results were stored')
else:
print('- one reserve margin was stored, as expected')
if test_model.reserveMargins[0].value != test_object.maximumPower:
pf = 'fail'
raise Exception('- the method did not use the available maximum power')
else:
print('- the method used maximum power value, as expected')
# create some vertices and store them
iv = [
IntervalValue(test_model, ti, test_mkt, MeasurementType.Vertex, Vertex(0, 0, -10)),
IntervalValue(test_model, ti, test_mkt, MeasurementType.Vertex, Vertex(0, 0, 10))
]
test_model.activeVertices = iv
# run test with maximum power greater than maximum vertex
test_object.maximumPower = 100
test_model.calculate_reserve_margin(test_mkt)
if test_model.reserveMargins[0].value != 10:
pf = 'fail'
raise Exception('- the method should have used vertex for comparison')
else:
print('- the method correctly chose to use the vertex power')
# run test with maximum power less than maximum vertex
test_object.maximumPower = 5
test_model.calculate_reserve_margin(test_mkt)
if test_model.reserveMargins[0].value != 5:
pf = 'fail'
raise Exception('- method should have used maximum power for comparison')
else:
print('- the method properly chose to use the maximum power')
# run test with scheduled power greater than maximum vertex
test_model.scheduledPowers[0].value = 20
test_object.maximumPower = 500
test_model.calculate_reserve_margin(test_mkt)
if test_model.reserveMargins[0].value != 0:
pf = 'fail'
raise Exception('- method should have assigned zero for a neg. result')
else:
print('- the method properly assigned 0 for a negative result')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_update_dual_costs():
# TEST_UPDATE_DUAL_COSTS() - test method update_dual_costs() that creates
# or revises the dual costs in active time intervals using active vertices,
# scheduled powers, and marginal prices.
# NOTE: This test is virtually identical to the NeighborModel test of the
# same name.
print('Running LocalAssetModel.test_update_dual_costs()')
pf = 'pass'
# Create a test Market object.
test_market = Market()
# Create and store a TimeInterval object.
dt = datetime.now() # datetime that may be used for most datetime arguments
time_interval = TimeInterval(dt, timedelta(hours=1), test_market, dt, dt)
test_market.timeIntervals = [time_interval]
# Create and store a marginal price IntervalValue object.
test_market.marginalPrices = [
IntervalValue(test_market, time_interval, test_market, MeasurementType.MarginalPrice, 0.1)]
# Create a test LocalAssetModel object.
test_model = LocalAssetModel()
# Create and store a scheduled power IntervalValue in the active time
# interval.
test_model.scheduledPowers = [
IntervalValue(test_model, time_interval, test_market, MeasurementType.ScheduledPower, 100)]
# Create and store a production cost IntervalValue object in the active
# time interval.
test_model.productionCosts = [
IntervalValue(test_model, time_interval, test_market, MeasurementType.ProductionCost, 1000)]
# TEST 1
print('- Test 1: First calculation of a dual cost')
test_model.update_dual_costs(test_market)
print(' - the method ran without errors')
if len(test_model.dualCosts) != 1:
pf = 'fail'
print(' - the wrong number of dual cost values was created')
else:
print(' - the right number of dual cost values was created')
dual_cost = test_model.dualCosts[0].value
if dual_cost != (1000 - 100 * 0.1):
pf = 'fail'
print(' - an unexpected dual cost value was found')
else:
print(' - the expected dual cost value was found')
# TEST 2
print('- Test 2: Reassignment of an existing dual cost')
# Configure the test by modifying the marginal price value.
test_market.marginalPrices[0].value = 0.2
test_model.update_dual_costs(test_market)
print(' - the method ran without errors')
if len(test_model.dualCosts) != 1:
pf = 'fail'
print(' - the wrong number of dual cost values was created')
else:
print(' - the right number of dual cost values was created')
dual_cost = test_model.dualCosts[0].value
if dual_cost != (1000 - 100 * 0.2):
pf = 'fail'
print(' - an unexpected dual cost value was found')
else:
print(' - the expected dual cost value was found')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_update_production_costs():
# TEST_UPDATE_PRODUCTION_COSTS() - test method update_production_costs()
# that calculates production costs from active vertices and scheduled
# powers.
# NOTE: This test is virtually identical to the NeighborModel test of the
# same name.
print('Running LocalAssetModel.test_update_production_costs()')
pf = 'pass'
# Create a test Market object.
test_market = Market
# Create and store a TimeInterval object.
dt = datetime.now() # datetime that may be used for most datetime arguments
time_interval = TimeInterval(dt, timedelta(hours=1), test_market, dt, dt)
test_market.timeIntervals = [time_interval]
# Create a test LocalAssetModel object.
test_model = LocalAssetModel()
# Create and store a scheduled power IntervalValue in the active time
# interval.
test_model.scheduledPowers = [
IntervalValue(test_model, time_interval, test_market, MeasurementType.ScheduledPower, 50)]
# Create and store some active vertices IntervalValue objects in the
# active time interval.
vertices = [
Vertex(0.1, 1000, 0),
Vertex(0.2, 1015, 100)
]
interval_values = [
IntervalValue(test_model, time_interval, test_market, MeasurementType.ActiveVertex, vertices[0]),
IntervalValue(test_model, time_interval, test_market, MeasurementType.ActiveVertex, vertices[1])
]
test_model.activeVertices = interval_values
# TEST 1
print('- Test 1: First calculation of a production cost')
test_model.update_production_costs(test_market)
print(' - the method ran without errors')
if len(test_model.productionCosts) != 1:
pf = 'fail'
print(' - the wrong number of production costs was created')
else:
print(' - the right number of production cost values was created')
production_cost = test_model.productionCosts[0].value
if float(production_cost) != float(1007.5):
pf = 'fail'
print(' - an unexpected production cost value was found')
else:
print(' - the expected production cost value was found')
# TEST 2
print('- Test 2: Reassignment of an existing production cost')
# Configure the test by modifying the scheduled power value.
test_model.scheduledPowers[0].value = 150
test_model.update_production_costs(test_market)
print(' - the method ran without errors')
if len(test_model.productionCosts) != 1:
pf = 'fail'
print(' - the wrong number of productions was created')
else:
print(' - the right number of production cost values was created')
production_cost = test_model.productionCosts[0].value
if float(production_cost) != float(1015):
pf = 'fail'
print(' - an unexpected dual cost value was found')
else:
print(' - the expected dual cost value was found')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_schedule_engagement():
# TEST_SCHEDULE_ENGAGEMENT() - tests a LocalAssetModel method called
# schedule_engagment()
print('Running LocalAssetModel.test_schedule_engagement()')
pf = 'pass'
# Establish test market
test_mkt = Market()
# Establish test market with two distinct active time intervals
# Note: This changed 1/29/18 due to new TimeInterval constructor
dt = datetime.now()
at = dt
# NOTE: def Hours() corrects behavior of Matlab hours().
dur = timedelta(hours=1)
mkt = test_mkt
mct = dt
st = datetime.combine(date.today(), time()) # datetime(date)
ti = [TimeInterval(at, dur, mkt, mct, st)]
st = ti[0].startTime + dur
ti.append(TimeInterval(at, dur, mkt, mct, st))
# store time intervals
test_mkt.timeIntervals = ti
# Establish test object that is a LocalAssetModel
test_object = LocalAssetModel()
# Run the first test case.
test_object.schedule_engagement(test_mkt)
# Were the right number of engagement schedule values created?
if len(test_object.engagementSchedule) != 2:
pf = 'fail'
raise Exception('- the method did not store the engagement schedule')
else:
print('- the method stored the right number of results')
# Where the correct scheduled engagement values stored?
if len([x.value for x in test_object.engagementSchedule if x.value != 1]) > 0:
pf = 'fail'
raise Exception('- the stored engagement schedule was not as expected')
else:
print('- the result values were as expected')
# Create and store another active time interval.
st = ti[1].startTime + dur
ti.append(TimeInterval(at, dur, mkt, mct, st))
# Re-store time intervals
test_mkt.timeIntervals = ti
# Run next test case.
test_object.schedule_engagement(test_mkt)
# Was the new time interval used?
if len(test_object.engagementSchedule) != 3:
pf = 'fail'
raise Exception('- the method apparently failed to create a new engagement')
else:
print('- the method created and stored new values')
# Were the existing time interval values reassigned properly?
# if any([test_object.engagementSchedule.value] != true * ones(1, 3)):
if any([x.value != 1 for x in test_object.engagementSchedule]):
pf = 'fail'
raise Exception('- the existing list was not augmented as expected')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_schedule_power():
# TEST_SCHEDULE_POWER() - tests a LocalAssetModel method called
# schedule_power().
print('Running LocalAssetModel.test_schedule_power()')
pf = 'pass'
# Establish test market
test_mkt = Market
# Establish test market with two distinct active time intervals
# Note: This changed 1/29/19 due to new TimeInterval constructor
dt = datetime.now()
at = dt
# NOTE: def Hours() corrects behavior of Matlab hours().
dur = timedelta(hours=1)
mkt = test_mkt
mct = dt
st = datetime.combine(date.today(), time()) # datetime(date)
ti = [TimeInterval(at, dur, mkt, mct, st)]
st = ti[0].startTime + dur
ti.append(TimeInterval(at, dur, mkt, mct, st))
# Store time intervals
test_mkt.timeIntervals = ti
# Establish test object that is a LocalAssetModel with a default power
# property.
test_object = LocalAssetModel()
test_object.defaultPower = 3.14159
# Run the first test case.
test_object.schedule_power(test_mkt)
# Were the right number of schduled power values created?
if len(test_object.scheduledPowers) != 2:
pf = 'fail'
raise Exception('- the method did not store the right number of results')
else:
print('- the method stored the right number of results')
# Where the correct scheduled power valules stored?
# if any([test_object.scheduledPowers.value] != test_object.defaultPower * ones(1, 2))
if any([x.value != test_object.defaultPower for x in test_object.scheduledPowers]):
pf = 'fail'
raise Exception('- the stored scheduled powers were not as expected')
else:
print('- the result value was as expected')
# Change the default power.
test_object.defaultPower = 6
# Create and store another active time interval.
st = ti[1].startTime + dur
ti.append(TimeInterval(at, dur, mkt, mct, st))
# Re-store time intervals
test_mkt.timeIntervals = ti
# Run next test case.
test_object.schedule_power(test_mkt)
# Was the new time interval used?
if len(test_object.scheduledPowers) != 3:
pf = 'fail'
raise Exception('- the method failed to create a new scheduled power')
# Were the existing time intervals reassigned properly?
# if any([test_object.scheduledPowers.value] != test_object.defaultPower * ones(1, 3))
if any([x.value != test_object.defaultPower for x in test_object.scheduledPowers]):
pf = 'fail'
raise Exception('- existing scheduled powers were not reassigned properly')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_schedule():
print('Running AbstractModel.test_schedule()')
pf = 'pass'
# Create a test market test_mkt
test_mkt = Market()
# Create a sample time interval ti
dt = datetime.now()
at = dt
# NOTE: Function Hours() corrects behavior of Matlab hours().
dur = timedelta(hours=1)
mkt = test_mkt
mct = dt
# NOTE: Function Hours() corrects behavior of Matlab hours().
st = datetime.combine(date.today(), time()) + timedelta(hours=20)
ti = TimeInterval(at, dur, mkt, mct, st)
# Save the time interval
test_mkt.timeIntervals = [ti]
# Assign a marginal price in the time interval
test_mkt.check_marginal_prices()
# Create a Neighbor test object and give it a default maximum power value
test_obj = Neighbor()
test_obj.maximumPower = 100
# Create a corresponding NeighborModel
test_mdl = NeighborModel()
# Make sure that the model and object cross-reference one another
test_obj.model = test_mdl
test_mdl.object = test_obj
# Run a test with a NeighborModel object
print('- running test with a NeighborModel:')
test_mdl.schedule(test_mkt)
print(' - the method encountered no errors')
if len(test_mdl.scheduledPowers) != 1:
pf = 'fail'
raise ' - the method did not store a scheduled power'
else:
print(' - the method calculated and stored a scheduled power')
if len(test_mdl.reserveMargins) != 1:
pf = 'fail'
raise ' - the method did not store a reserve margin'
else:
print(' - the method stored a reserve margin')
if len(test_mdl.activeVertices) != 1:
pf = 'fail'
raise ' - the method did not store an active vertex'
else:
print(' - the method stored an active vertex')
# Run a test again with a LocalAssetModel object
test_obj = LocalAsset()
test_obj.maximumPower = 100
test_mdl = LocalAssetModel()
test_obj.model = test_mdl
test_mdl.object = test_obj
print('- running test with a LocalAssetModel:')
test_mdl.schedule(test_mkt)
print(' - the method encountered no errors')
if len(test_mdl.scheduledPowers) != 1:
pf = 'fail'
raise ' - the method did not store a scheduled power'
else:
print(' - the method calculated and stored a scheduled power')
if len(test_mdl.reserveMargins) != 1:
pf = 'fail'
raise ' - the method did not store a reserve margin'
else:
print(' - the method stored a reserve margin')
if len(test_mdl.activeVertices) != 1:
pf = 'fail'
raise ' - the method did not store an active vertex'
else:
print(' - the method stored an active vertex')
# Success
print('- the test ran to completion')
print('Result: %s', pf)
def test_engagement_cost():
print('Running LocalAssetModel.test_engagement_cost()')
pf = 'pass'
# Create a test LocalAssetModel object.
test_model = LocalAssetModel()
# Assign engagement costs for [dissengagement, hold, engagement]
test_model.engagementCost = [1, 2, 3]
## TEST 1
print('- Test 1: Normal transition input arguments [-1,0,1]')
transition = 0 # false - false # a hold transition, unchanged
cost = test_model.engagement_cost(transition)
print(' - the method ran without errors')
if cost != 2:
pf = 'fail'
print(' - the method miscalculated the cost of a hold')
else:
print(' - the method correctly calculated the cost of a hold')
transition = -1 # false - true # an disengagement transition
cost = test_model.engagement_cost(transition)
if cost != 1:
pf = 'fail'
print(' - the method miscalculated the cost of a disengagement')
else:
print(' - the method correctly calculated the cost of a disengagement')
transition = 1 # true - false # an disengagement transition
cost = test_model.engagement_cost(transition)
if cost != 3:
pf = 'fail'
print(' - the method miscalculated the cost of an engagement')
else:
print(' - the method correctly calculated the cost of an engagement')
## TEST 2
print('- Test 2: Unexpected, dissallowed input argument')
transition = 7 # a disallowed transition
cost = test_model.engagement_cost(transition)
print(' - method warned and returned gracefully')
if cost != 0:
pf = 'fail'
print(' - the method assigned a cost value other than zero')
else:
print(' - the method correctly assigned zero to the cost')
# Success.
print('- the test ran to completion')
print('\nResult: #s\n\n', pf)
def test_update_costs():
print('Running AbstractModel.test_update_costs()')
pf = 'pass'
# Create a test market test_mkt
test_mkt = Market()
# Create a sample time interval ti
dt = datetime.now()
at = dt
# NOTE: Function Hours() corrects behavior of Matlab hours().
dur = timedelta(hours=1)
mkt = test_mkt
mct = dt
st = datetime.combine(date.today(), time()) + timedelta(hours=20)
ti = TimeInterval(at, dur, mkt, mct, st)
# Save the time interval
test_mkt.timeIntervals = [ti]
# Assign a marginal price in the time interval
test_mkt.check_marginal_prices()
# Create a Neighbor test object and give it a default maximum power value
test_obj = Neighbor()
# test_obj.maximumPower = 100
# Create a corresponding NeighborModel
test_mdl = NeighborModel()
# Make sure that the model and object cross-reference one another
test_obj.model = test_mdl
test_mdl.object = test_obj
test_mdl.scheduledPowers = [
IntervalValue(test_mdl, ti, test_mkt, MeasurementType.ScheduledPower,
100)
]
test_mdl.activeVertices = [
IntervalValue(test_mdl, ti, test_mkt, MeasurementType.ActiveVertex,
Vertex(0.05, 0, 100))
]
# Run a test with a NeighborModel object
print('- running test with a NeighborModel:')
try:
test_mdl.update_costs(test_mkt)
print(' - the method encountered no errors')
except:
pf = 'fail'
raise ' - the method did not run without errors'
if len(test_mdl.productionCosts) != 1:
pf = 'fail'
raise ' - the method did not store a production cost'
else:
print(' - the method calculated and stored a production cost')
if len(test_mdl.dualCosts) != 1:
pf = 'fail'
raise ' - the method did not store a dual cost'
else:
print(' - the method stored a dual cost')
if test_mdl.totalProductionCost != sum(
[x.value for x in test_mdl.productionCosts]):
pf = 'fail'
raise ' - the method did not store a total production cost'
else:
print(' - the method stored an total production cost')
if test_mdl.totalDualCost != sum([x.value for x in test_mdl.dualCosts]):
pf = 'fail'
raise ' - the method did not store a total dual cost'
else:
print(' - the method stored an total dual cost')
# Run a test again with a LocalAssetModel object
test_obj = LocalAsset()
# test_obj.maximumPower = 100
test_mdl = LocalAssetModel()
test_obj.model = test_mdl
test_mdl.object = test_obj
test_mdl.scheduledPowers = [
IntervalValue(test_mdl, ti, test_mkt, MeasurementType.ScheduledPower,
100)
]
test_mdl.activeVertices = [
IntervalValue(test_mdl, ti, test_mkt, MeasurementType.ActiveVertex,
Vertex(0.05, 0, 100))
]
print('- running test with a LocalAssetModel:')
try:
test_mdl.update_costs(test_mkt)
print(' - the method encountered no errors')
except:
pf = 'fail'
raise ' - the method did not run without errors'
if len(test_mdl.productionCosts) != 1:
pf = 'fail'
raise ' - the method did not store a production cost'
else:
print(' - the method calculated and stored a production cost')
if len(test_mdl.dualCosts) != 1:
pf = 'fail'
raise ' - the method did not store a dual cost'
else:
print(' - the method stored a dual cost')
if test_mdl.totalProductionCost != sum(
[x.value for x in test_mdl.productionCosts]):
pf = 'fail'
raise ' - the method did not store a total production cost'
else:
print(' - the method stored an total production cost')
if test_mdl.totalDualCost != sum([x.value for x in test_mdl.dualCosts]):
pf = 'fail'
raise ' - the method did not store a total dual cost'
else:
print(' - the method stored an total dual cost')
# Success
print('- the test ran to completion')
print('Result: %s', pf)
def test_prod_cost_from_formula():
from local_asset_model import LocalAssetModel
from market import Market
print('Running test_prod_cost_from_formula()')
pf = 'pass'
# Create a test object
test_object = LocalAssetModel()
# Create a test market
test_market = Market()
# Create and store the object's cost parameters
test_object.costParameters = [4, 3, 2]
# Create and store three hourly TimeIntervals
# Modified to use the TimeInterval constructor.
dt = datetime.now()
at = dt
dur = timedelta(hours=1)
mkt = test_market
mct = dt
st = dt
ti = [TimeInterval(at, dur, mkt, mct, st)]
st = st + dur
ti.append(TimeInterval(at, dur, mkt, mct, st))
st = st + dur
ti.append(TimeInterval(at, dur, mkt, mct, st))
test_market.timeIntervals = ti
# Create and store three corresponding scheduled powers
iv = [
IntervalValue(test_object, ti[0], test_market,
MeasurementType.ScheduledPower, 100),
IntervalValue(test_object, ti[1], test_market,
MeasurementType.ScheduledPower, 200),
IntervalValue(test_object, ti[2], test_market,
MeasurementType.ScheduledPower, 300)
]
test_object.scheduledPowers = iv
# Run the test
pc = [0] * 3
for i in range(3):
pc[i] = prod_cost_from_formula(test_object, ti[i])
# pc(1) = 4 + 3 * 100 + 0.5 * 2 * 100^2 = 10304
# pc(2) = 4 + 3 * 200 + 0.5 * 2 * 200^2 = 40604
# pc(3) = 4 + 3 * 300 + 0.5 * 2 * 300^2 = 90904
#if all(pc ~=[10304, 40604, 90904])
expected = [10304, 40604, 90904]
if all([pc[i] != expected[i] for i in range(len(pc))]):
pf = 'fail'
raise Exception('- production cost was incorrectly calculated')
else:
print('- production cost was correctly calculated')
# Success
print('- the test ran to completion')
print('Result: #s\n\n', pf)
def test_production():
from local_asset_model import LocalAssetModel
from market import Market
print('Running test_production()')
pf = 'pass'
# Create a test object
test_object = LocalAssetModel()
# Create a test market
test_market = Market()
# Create several active vertices av
av = [
Vertex(0.0200, 5.00, 0.0),
Vertex(0.0200, 7.00, 100.0),
Vertex(0.0250, 9.25, 200.0)
]
# Create a time interval ti
dt = datetime.now()
at = dt
# NOTE: Function Hours() corrects the behavior of Matlab hours().
dur = timedelta(hours=1)
mkt = test_market
mct = dt
st = dt
ti = TimeInterval(at, dur, mkt, mct, st)
# Assign activeVertices, which are IntervalValues
test_object.activeVertices = [
IntervalValue(test_object, ti, test_market,
MeasurementType.ActiveVertex, av[0]),
IntervalValue(test_object, ti, test_market,
MeasurementType.ActiveVertex, av[1]),
IntervalValue(test_object, ti, test_market,
MeasurementType.ActiveVertex, av[2])
]
## CASE: Various marginal prices when there is more than one vertex
test_prices = [-0.010, 0.000, 0.020, 0.0225, 0.030]
p = [0] * len(test_prices) #zeros(1, length(test_prices))
for i in range(len(test_prices)): #for i = 1:length(test_prices)
p[i] = production(test_object, test_prices[i], ti)
print('- the function ran without errors')
# p(1) = 0: below first vertex
# p(2) = 0: below first vertex
# p(3) = 100: at first vertex, which has identical marginal price as second
# p(4) = 150: interpolate between vertices
# p(5) = 200: exceeds last vertex
#if ~all(abs(p - [0, 0, 100, 150, 200]) < 0.001):
expected = [0, 0, 100, 150, 200]
if not all([p[i] - expected[i] < 0.001 for i in range(len(p))]):
pf = 'fail'
raise Exception('- the production cost was incorrectly calculated')
else:
print('- the production cost was correctly calculated')
## CASE: One vertex (inelastic case, a constant)
test_object.activeVertices = [
IntervalValue(test_object, ti, test_market,
MeasurementType.ActiveVertex, av[2])
]
for i in range(5):
p[i] = production(test_object, test_prices[i], ti)
#if ~all(p == 200 * ones(1, length(p))):
if not all(x == 200 for x in p):
pf = 'fail'
raise Exception(
'the vertex power should be assigned when there is one vertex')
else:
print('- the correct power was assigned when there is one vertex')
## CASE: No active vertices (error case):
test_object.activeVertices = []
try:
p = production(test_object, test_prices[4], ti)
pf = 'fail'
raise Exception(
'- an error should have occurred with no active vertices')
except:
print('- with no vertices, system returned with warnings, as expected')
# Success
print('- the test function ran to completion')
print('Result: #s\n\n', pf)
def test_sum_vertices():
print('Running Market.test_sum_vertices()')
pf = 'pass'
# Create a test myTransactiveNode object.
test_node = myTransactiveNode()
# Create a test Market object.
test_market = Market()
# List the test market with the test_node.
test_node.markets = test_market
# Create and store a time interval to work with.
dt = datetime.now()
at = dt
dur = timedelta(hours=1)
mkt = test_market
mct = dt
st = dt
time_interval = TimeInterval(at, dur, mkt, mct, st)
test_market.timeIntervals = [time_interval]
# Create test LocalAsset and LocalAssetModel objects
test_asset = LocalAsset()
test_asset_model = LocalAssetModel()
# Add the test_asset to the test node list.
test_node.localAssets = [test_asset]
# Have the test asset and its model cross reference one another.
test_asset.model = test_asset_model
test_asset_model.object = test_asset
# Create and store an active Vertex or two for the test asset
test_vertex = [Vertex(0.2, 0, -110), Vertex(0.2, 0, -90)]
interval_values = [
IntervalValue(test_node, time_interval, test_market,
MeasurementType.ActiveVertex, test_vertex[0]),
IntervalValue(test_node, time_interval, test_market,
MeasurementType.ActiveVertex, test_vertex[1])
]
test_asset_model.activeVertices = [interval_values[0], interval_values[1]
] # interval_value(1:2)
# Create test Neighbor and NeighborModel objects.
test_neighbor = Neighbor()
test_neighbor_model = NeighborModel()
# Add the test neighbor to the test node list.
test_node.neighbors = [test_neighbor]
# Have the test neighbor and its model cross reference one another.
test_neighbor.model = test_neighbor_model
test_neighbor.model.object = test_neighbor
# Create and store an active Vertex or two for the test neighbor
test_vertex.append(Vertex(0.1, 0, 0))
test_vertex.append(Vertex(0.3, 0, 200))
interval_values.append(
IntervalValue(test_node, time_interval, test_market,
MeasurementType.ActiveVertex, test_vertex[2]))
interval_values.append(
IntervalValue(test_node, time_interval, test_market,
MeasurementType.ActiveVertex, test_vertex[3]))
test_neighbor_model.activeVertices = [
interval_values[2], interval_values[3]
]
## Case 1
print('- Case 1: Basic case with interleaved vertices')
# Run the test.
try:
vertices = test_market.sum_vertices(test_node, time_interval)
print(' - the method ran without errors')
except:
pf = 'fail'
print(' - the method had errors when called and stopped')
if len(vertices) != 4:
pf = 'fail'
print(' - an unexpected number of vertices was returned')
else:
print(' - the expected number of vertices was returned')
powers = [x.power for x in vertices]
# if any(~ismember(single(powers), single([-110.0000, -10.0000, 10.0000, 110.0000])))
if len([
x for x in powers
if round(x, 4) not in [-110.0000, -10.0000, 10.0000, 110.0000]
]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex powers were as expected')
marginal_prices = [round(x.marginalPrice, 4) for x in vertices]
# if any(~ismember(single(marginal_prices), single([0.1000, 0.2000, 0.3000])))
if len([
x for x in marginal_prices
if round(x, 4) not in [0.1000, 0.2000, 0.3000]
]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex marginal prices were as expected')
## CASE 2: NEIGHBOR MODEL TO BE EXCLUDED
# This case is needed when a demand or supply curve must be created for a
# transactive Neighbor object. The active vertices of the target Neighbor
# must be excluded, leaving a residual supply or demand curve against which
# the Neighbor may plan.
print('- Case 2: Exclude test Neighbor model')
# Run the test.
try:
# [vertices] = test_market.sum_vertices(test_node, time_interval, test_neighbor_model)
vertices = test_market.sum_vertices(test_node, time_interval,
test_neighbor_model)
print(' - the method ran without errors')
except:
pf = 'fail'
print(' - the method encountered errors and stopped')
if len(vertices) != 2:
pf = 'fail'
print(' - an unexpected number of vertices was returned')
else:
print(' - the expected number of vertices was returned')
powers = [round(x.power, 4) for x in vertices]
# if any(~ismember(single(powers), single([-110.0000, -90.0000])))
if len([x for x in powers if x not in [-110.0000, -90.0000]]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex powers were as expected')
marginal_prices = [x.marginalPrice for x in vertices]
# if any(~ismember(single(marginal_prices), single([0.2000])))
if len([x for x in marginal_prices if round(x, 4) not in [0.2000]]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex marginal prices were as expected')
## CASE 3: CONSTANT SHOULD NOT CREATE NEW NET VERTEX
print('- Case 3: Include a constant vertex. No net vertex should be added')
# Change the test asset to NOT have any flexibility. A constant should
# not introduce a net vertex at a constant's marginal price. Marginal
# price is NOT meaningful for an inelastic device.
test_asset_model.activeVertices = [interval_values[0]]
# Run the test.
try:
# [vertices] = test_market.sum_vertices(test_node, time_interval)
vertices = test_market.sum_vertices(test_node, time_interval)
print(' - the method ran without errors')
except:
pf = 'fail'
print(' - the method encountered errors and stopped')
#%[180907DJH: THIS TEST IS CORRECTED. THE NEIGHBOR HAS TWO VERTICES. ADDING
#AN ASSET WITH ONE VERTEX (NO FLEXIBILITY) SHOULD NOT CHANGE THE NUMBER OF
#ACTIVE VERTICES, SO THE CORRECTED TEST CONFIRMS TWO VERTICES. THE CODE HAS
#BEEN CORRECTED ACCORDINGLY.]
if len(vertices) != 2:
pf = 'fail'
print(' - an unexpected number of vertices was returned')
else:
print(' - the expected number of vertices was returned')
powers = [x.power for x in vertices]
# if any(~ismember(single(powers), single([-110.0000, 90])))
if len([x for x in powers if round(x, 4) not in [-110.0000, 90]]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex powers were as expected')
marginal_prices = [x.marginalPrice for x in vertices]
# if any(~ismember(single(marginal_prices), single([0.1000, 0.3000, Inf])))
if len([
x for x in marginal_prices if round(x, 4) not in
[0.1000, 0.3000, float("inf")]
]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex marginal prices were as expected')
# CASE 4: More than two vertices at any marginal price
print('- Case 4: More than two vertices at same marginal price')
# Move the two active vertices of the test asset to be at the same
# marginal price as one of the neighbor active vertices.
test_vertex = [Vertex(0.1, 0, -110), Vertex(0.1, 0, -90)]
interval_values = [
IntervalValue(test_node, time_interval, test_market,
MeasurementType.ActiveVertex, test_vertex[0]),
IntervalValue(test_node, time_interval, test_market,
MeasurementType.ActiveVertex, test_vertex[1])
]
test_asset_model.activeVertices = [interval_values[0], interval_values[1]
] # interval_value(1:2)
# Run the test.
try:
vertices = test_market.sum_vertices(test_node, time_interval)
print(' - the method ran without errors')
except:
pf = 'fail'
print(' - the method encountered errors and stopped')
if len(vertices) != 3:
pf = 'fail'
print(' - an unexpected number of vertices was returned')
else:
print(' - the expected number of vertices was returned')
powers = [x.power for x in vertices]
# if any(~ismember(single(powers), single([-110.0000, -90.0000, 110.0000])))
if len([
x for x in powers
if round(x, 4) not in [-110.0000, -90.0000, 110.0000]
]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex powers were as expected')
marginal_prices = [x.marginalPrice for x in vertices]
# if any(~ismember(single(marginal_prices), single([0.1000, 0.3000])))
if len([x for x in marginal_prices if round(x, 4) not in [0.1000, 0.3000]
]) > 0:
pf = 'fail'
print(' - the vertex powers were not as expected')
else:
print(' - the vertex marginal prices were as expected')
# Success
print('- the test ran to completion')
print('Result: #s\n\n', pf)
def test_schedule():
print('Running Market.test_schedule()')
print('WARNING: This test may be affected by NeighborModel.schedule()')
print('WARNING: This test may be affected by NeighborModel.schedule()')
pf = 'pass'
# Establish a myTransactiveNode object
mtn = myTransactiveNode()
# Establish a test market
test_mkt = Market()
# Create and store one TimeInterval
dt = datetime(2018, 1, 1, 12, 0, 0) # Noon Jan 1, 2018
at = dt
dur = timedelta(hours=1)
mkt = test_mkt
mct = dt
st = dt
ti = TimeInterval(at, dur, mkt, mct, st)
test_mkt.timeIntervals = [ti]
# Create and store a marginal price in the active interval.
test_mkt.marginalPrices = [
IntervalValue(test_mkt, ti, test_mkt, MeasurementType.MarginalPrice,
0.01)
]
print('- configuring a test Neighbor and its NeighborModel')
# Create a test object that is a Neighbor
test_obj1 = Neighbor()
test_obj1.maximumPower = 100
# Create the corresponding model that is a NeighborModel
test_mdl1 = NeighborModel()
test_mdl1.defaultPower = 10
test_obj1.model = test_mdl1
test_mdl1.object = test_obj1
mtn.neighbors = [test_obj1]
print('- configuring a test LocalAsset and its LocalAssetModel')
# Create a test object that is a Local Asset
test_obj2 = LocalAsset
test_obj2.maximumPower = 100
# Create the corresponding model that is a LocalAssetModel
test_mdl2 = LocalAssetModel()
test_mdl2.defaultPower = 10
test_obj2.model = test_mdl2
test_mdl2.object = test_obj2
mtn.localAssets = [test_obj2]
try:
test_mkt.schedule(mtn)
print('- method ran without errors')
except:
raise ('- method did not run due to errors')
if len(test_mdl1.scheduledPowers) != 1:
raise (
'- the wrong numbers of scheduled powers were stored for the Neighbor'
)
else:
print(
'- the right number of scheduled powers were stored for the Neighbor'
)
if len(test_mdl2.scheduledPowers) != 1:
raise (
'- the wrong numbers of scheduled powers were stored for the LocalAsset'
)
else:
print(
'- the right number of scheduled powers were stored for the LocalAsset'
)
# Success
print('- the test ran to completion')
print('Result: #s\n\n', pf)