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Fixed issue with coefficient computation

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This commit is contained in:
Peter Yefi 2021-11-10 10:17:01 +00:00
parent f6de5b6f96
commit ebe5439f02
2 changed files with 10 additions and 5 deletions
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13
imports/energy_systems/xlsx_heat_pump_parameters.py
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@ -86,7 +86,7 @@ class XlsxHeatPumpParameters:
self._city.add_city_object(energy_system) self._city.add_city_object(energy_system)
return self._city return self._city
def _extract_heat_pump_data(self, heat_pump_capacity_data) -> [List, List]: def _extract_heat_pump_data(self, heat_pump_capacity_data: Dict) -> [List, List]:
""" """
Fetches a list of metric based data for heat pump for various temperature, Fetches a list of metric based data for heat pump for various temperature,
eg. cooling capacity data for 12 capacity heat pump eg. cooling capacity data for 12 capacity heat pump
@ -102,7 +102,7 @@ class XlsxHeatPumpParameters:
compressor_power_data.append(metric_data[1]) compressor_power_data.append(metric_data[1])
return [cooling_heating_capacity_data, compressor_power_data] return [cooling_heating_capacity_data, compressor_power_data]
def _compute_coefficients(self, heat_pump_data, data_type="heat") -> List[float]: def _compute_coefficients(self, heat_pump_data: List, data_type="heat") -> List[float]:
""" """
Compute heat output and electrical demand coefficients Compute heat output and electrical demand coefficients
from heating and cooling performance data from heating and cooling performance data
@ -111,10 +111,15 @@ class XlsxHeatPumpParameters:
or heating performance data or heating performance data
:return: Tuple[Dict, Dict] :return: Tuple[Dict, Dict]
""" """
out_temp = [25, 30, 32, 35, 40, 45] * 6 # Determine the recurrence of temperature values. 6 repetitions for
# cooling performance and 5 repetition for heating performance
temp_multiplier = 5 if data_type == "heat" else 6
out_temp = [25, 30, 32, 35, 40, 45] * temp_multiplier
heat_x_values = np.repeat([-5, 0, 7, 10, 15], 6) heat_x_values = np.repeat([-5, 0, 7, 10, 15], 6)
cool_x_values = np.repeat([6, 7, 8, 9, 10, 11], 6) cool_x_values = np.repeat([6, 7, 8, 9, 10, 11], 6)
x_values = heat_x_values if data_type == "heat" else cool_x_values x_values = heat_x_values if data_type == "heat" else cool_x_values
x_values = x_values.tolist()
# convert list of lists to one list # convert list of lists to one list
heat_pump_data = list(itertools.chain.from_iterable(heat_pump_data)) heat_pump_data = list(itertools.chain.from_iterable(heat_pump_data))
@ -122,7 +127,7 @@ class XlsxHeatPumpParameters:
popt, _ = curve_fit(self._objective_function, [x_values, out_temp], heat_pump_data) popt, _ = curve_fit(self._objective_function, [x_values, out_temp], heat_pump_data)
return popt.tolist() return popt.tolist()
def _objective_function(self, xdata, a1, a2, a3, a4, a5, a6) -> float: def _objective_function(self, xdata: List, a1: float, a2: float, a3: float, a4: float, a5: float, a6: float) -> float:
""" """
Objective function for computing coefficients Objective function for computing coefficients
:param xdata: :param xdata:

2
imports/energy_systems_factory.py
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@ -19,7 +19,7 @@ class EnergySystemsFactory:
self._city = city self._city = city
self._base_path = base_path self._base_path = base_path
def _xlsx_heat_pump(self): def _xlsx_heat_pump_parameters(self):
""" """
Enrich the city by using xlsx heat pump information Enrich the city by using xlsx heat pump information
""" """