def test_creation_of_parameter_names_2022(self):
PredictPlant = PredictModernPlantParameters("CCGT", 1200, 2022)
cost_parameter_variables = PredictPlant._create_parameter_names(self.initial_stub_cost_parameters)
assert cost_parameter_variables == ['Connect_system_cost-Medium _2020', 'Constr_cost-Medium _2020',
'Fixed_cost-Medium _2020',
'Infra_cost-Medium _2020', 'Insurance_cost-Medium _2020',
'Pre_dev_cost-Medium _2020',
'Var_cost-Medium _2020']
def _select_cost_estimator(start_year, plant_type, capacity):
earliest_modern_plant_year = min([
int(column.split(" _")[1])
for column in elecsim.scenario.scenario_data.modern_plant_costs.filter(
regex='Connect_system_cost-Medium _').columns
])
_check_digit(capacity, "capacity")
_check_digit(start_year, "start_year")
_check_positive(start_year, "start_year")
_check_positive(capacity, "capacity")
hist_costs = elecsim.scenario.scenario_data.power_plant_historical_costs_long
hist_costs = hist_costs[hist_costs.Technology.map(
lambda x: x in plant_type)].dropna()
if start_year < earliest_modern_plant_year and not hist_costs.empty:
require_fuel = PlantRegistry(plant_type).check_if_fuel_required()
cost_parameters = _estimate_old_plant_cost_parameters(
capacity, plant_type, require_fuel, start_year)
_check_parameters(capacity, cost_parameters, plant_type, start_year)
return cost_parameters
else:
cost_parameters = PredictModernPlantParameters(
plant_type, capacity, start_year).parameter_estimation()
_check_parameters(capacity, cost_parameters, plant_type, start_year)
return cost_parameters
def test_check_plant_exists_fails_with_no_data(self):
with pytest.raises(ValueError) as excinfo:
PredictModernPlantParameters("Fake_Plant", 1200, 2018).check_plant_exists(
{'connection_cost_per_mw': 0, 'construction_cost_per_mw': 0, 'fixed_o_and_m_per_mw': 0,
'infrastructure': 0, 'insurance_cost_per_mw': 0, 'pre_dev_cost_per_mw': 0,
'variable_o_and_m_per_mwh': 0, 'pre_dev_period': 0, 'operating_period': 0, 'construction_period': 0,
'efficiency': 0, 'average_load_factor': 0, 'construction_spend_years': 0, 'pre_dev_spend_years': 0})
assert "No cost data for power plant of type: Fake_Plant" in str(excinfo.value)
def test_estimate_non_interpolatable_parameters_for_ccgt_1450(self):
predict_modern_parameters = PredictModernPlantParameters("CCGT", 1450, 2018)
assert predict_modern_parameters._estimate_non_interpolatable_parameters("Pre_Dur") == 3
assert predict_modern_parameters._estimate_non_interpolatable_parameters("Operating_Period") ==25
assert predict_modern_parameters._estimate_non_interpolatable_parameters("Constr_Dur") == 3
assert predict_modern_parameters._estimate_non_interpolatable_parameters("Efficiency") == 0.53
assert predict_modern_parameters._estimate_non_interpolatable_parameters("Average_Load_Factor") == 0.93
def calculate_latest_lcoe(self):
logging.info('Selecting latest power plant data')
estimated_cost_parameters = PredictModernPlantParameters(
"PV", 50, 2020).parameter_estimation()
power_plant_obj = PlantRegistry("PV").plant_type_to_plant_object()
power_plant = power_plant_obj(name="Test",
plant_type="PV",
capacity_mw=50,
construction_year=2020,
**estimated_cost_parameters)
lcoe = power_plant.calculate_lcoe(0.05)
return lcoe
def test_parameter_estimation_for_ccgt_1335_5(self):
estimated_plant_parameters = PredictModernPlantParameters("CCGT", 1335.5, 2018).parameter_estimation()
assert estimated_plant_parameters['connection_cost_per_mw'] == 3300
assert estimated_plant_parameters['construction_cost_per_mw'] == 500000
assert estimated_plant_parameters['fixed_o_and_m_per_mw'] == 11800
assert estimated_plant_parameters['infrastructure'] == 15100
assert estimated_plant_parameters['insurance_cost_per_mw'] == 2000
assert estimated_plant_parameters['pre_dev_cost_per_mw'] == 10000
assert estimated_plant_parameters['variable_o_and_m_per_mwh'] == 3.00
assert estimated_plant_parameters['pre_dev_period'] == 3
assert estimated_plant_parameters['operating_period'] == 25
assert estimated_plant_parameters['construction_period'] == 3
assert estimated_plant_parameters['efficiency'] == 0.54
assert estimated_plant_parameters['average_load_factor'] == 0.93
assert estimated_plant_parameters['construction_spend_years'] == [0.4, 0.4, 0.2]
assert estimated_plant_parameters['pre_dev_spend_years'] == [0.44, 0.44, 0.12]
def __init__(self, year, plant_type, capacity):
# Import historical LCOE data for power plants, and use to predict LCOE for current year based on linear
# interpolation
self.year = year
self.plant_type = plant_type
self.capacity = capacity
self.hist_costs = self.hist_costs[self.hist_costs['Technology'].map(
lambda x: x in plant_type)].dropna()
if not all(self.hist_costs.capacity_range.str.contains(">0")):
self.hist_costs = self.hist_costs[[
pd.eval(f"{self.capacity}{j}")
for j in self.hist_costs['capacity_range']
]]
self.estimated_historical_lcoe = ExtrapolateInterpolate(
self.hist_costs.Year, self.hist_costs.lcoe)(year)
self.discount_rate = self.hist_costs.Discount_rate.iloc[0]
self.modern_costs = elecsim.scenario.scenario_data.modern_plant_costs[
elecsim.scenario.scenario_data.modern_plant_costs['Type'].map(
lambda x: x in plant_type)]
minimum_year = self.find_smallest_year_available()
self.estimated_modern_plant_parameters = PredictModernPlantParameters(
self.plant_type, self.capacity,
minimum_year).parameter_estimation()
plant_object = PlantRegistry(
self.plant_type).plant_type_to_plant_object()
self.plant = plant_object(name="Modern Plant",
plant_type=self.plant_type,
capacity_mw=self.capacity,
construction_year=self.year,
**self.estimated_modern_plant_parameters)
self.modern_lcoe = self.plant.calculate_lcoe(self.discount_rate)
self.lcoe_scaler = self.estimated_historical_lcoe / self.modern_lcoe
def test_payment_spread_estimator_for_ccgt_160(self):
predict_modern_parameters = PredictModernPlantParameters("CCGT", 160, 2018)
assert predict_modern_parameters._payment_spread_estimator("Constr") == [0.4, 0.4, 0.2]
assert predict_modern_parameters._payment_spread_estimator("Pre") == [0.435, 0.435, 0.13]
def test_check_plant_exists_with_data(self):
PredictModernPlantParameters("Fake_Plant", 1200, 2018).check_plant_exists(
{'connection_cost_per_mw': 100, 'construction_cost_per_mw': 100, 'fixed_o_and_m_per_mw': 100,
'infrastructure': 100, 'insurance_cost_per_mw': 100, 'pre_dev_cost_per_mw': 100,
'variable_o_and_m_per_mwh': 100, 'pre_dev_period': 100, 'operating_period': 100, 'construction_period': 100,
'efficiency': 100, 'average_load_factor': 100, 'construction_spend_years': 100, 'pre_dev_spend_years': 100})