def METHOD_NAME():
    # build generic models
    m = pyo.ConcreteModel()
    m.fs = idc.FlowsheetBlock(dynamic=False)
    m.fs.costing = WaterTAPCosting()
    # change base units for value assertions
    m.fs.costing.base_currency = pyo.units.USD_2021
    m.fs.unit = idc.UnitModelBlock()
    # build power variable required for cost_rectifier
    m.fs.unit.power = pyo.Var(
        initialize=100,
        domain=pyo.NonNegativeReals,
        units=pyo.units.kW,
    )
    m.fs.unit.power.fix()
    # cost rectifier
    m.fs.unit.costing = idc.UnitModelCostingBlock(
        flowsheet_costing_block=m.fs.costing,
        costing_method=dummy_cost_rectifier,
    )
    # cost process for cost_flow to be applied
    m.fs.costing.cost_process()
    # check model and solve
    assert_units_consistent(m)
    assert istat.degrees_of_freedom(m) == 0
    results = solver.solve(m)
    assert pyo.check_optimal_termination(results)
    # check values
    assert pytest.approx(59320, rel=1e-3) == pyo.value(m.fs.unit.costing.capital_cost)
    assert pytest.approx(111.1, rel=1e-3) == pyo.value(m.fs.unit.costing.ac_power)
    assert pytest.approx(111.1, rel=1e-3) == pyo.value(
        m.fs.costing.aggregate_flow_electricity
    )
    assert pytest.approx(80040, rel=1e-3) == pyo.value(
        m.fs.costing.aggregate_flow_costs["electricity"]
    )