def test_aggregate_demand():
grid = Grid("Texas")
ct = ChangeTable(grid)
kind = "building"
zone_info = {"East": {"res_cooking": {"advanced_heat_pump_v2": 0.7}}}
grid_info = {"res_cooking": {"advanced_heat_pump_v2": 0.3}}
ct.add_electrification(kind, {"zone": zone_info, "grid": grid_info})
mock_input = MockProfileInput(grid)
demand = mock_input.get_data(None, "demand")
mock_input.get_profile = lambda *args: demand
td = TransformDemand(grid, ct, kind)
td._profile_data = mock_input
result = td.value()
pd.testing.assert_series_equal(0.7 * demand.loc[:, 308], result.loc[:,
308])
pd.testing.assert_frame_equal(0.3 * demand.loc[:, :307],
result.loc[:, :307])
def test_profile_mappings():
grid = Grid("Texas")
ct = ChangeTable(grid)
grid_info = {"res_heating": {"standard_heat_pump_v2": 0.3}}
zone_info = {
"East": {
"res_cooking": {
"advanced_heat_pump_v2": 0.7
}
},
"Coast": {
"com_hot_water": {
"standard_heat_pump_v1": 0.6,
"advanced_heat_pump_v2": 0.4,
}
},
"Far West": {
"res_cooking": {
"standard_heat_pump_v1": 0.2,
"advanced_heat_pump_v2": 0.3
}
},
}
kind = "building"
ct.add_electrification(kind, {"zone": zone_info, "grid": grid_info})
td = TransformDemand(grid, ct, kind)
actual = td.p2g
expected = {"res_heating_standard_heat_pump_v2.csv": 0.3}
assert expected == actual
actual = td.p2z
expected = {
"res_cooking_advanced_heat_pump_v2.csv": [(308, 0.7), (301, 0.3)],
"com_hot_water_standard_heat_pump_v1.csv": [(307, 0.6)],
"com_hot_water_advanced_heat_pump_v2.csv": [(307, 0.4)],
"res_cooking_standard_heat_pump_v1.csv": [(301, 0.2)],
}
assert expected == actual
