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)
Exemplo n.º 3
0
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)
Exemplo n.º 4
0
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)