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_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)