Add maximum power to Building Load classes

Author: WouterPeere

CHANGELOG.md

@@ -11,6 +11,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
 - Add flow_rates as explicit argument in PressureDrop curve function.
 - Add function for cascading heat pumps.
+- Added _get_max_power functions to BuildingLoad classes.
 - Inlet and outlet water temperature (issue #271).
 - Added 'type' attribute to temperature profile plotting so also the inlet and outlet temperatures can be shown (issue
   #271).

GHEtool/VariableClasses/LoadData/Baseclasses/_HourlyDataBuilding.py

@@ -179,7 +179,7 @@ def _get_hourly_cop(self, power: np.ndarray = None) -> Union[float, np.ndarray]:
         if isinstance(self.cop, SCOP) and isinstance(self.eer, SEER) and isinstance(self.cop_dhw, SCOP):
             return self.cop.get_COP(0, power=np.nan_to_num(power))
         if isinstance(self.results, ResultsMonthly):
-            raise TypeError('You cannot get an hourly EER values based on monthly temperature results.')
+            raise TypeError('You cannot get an hourly COP values based on monthly temperature results.')
         if isinstance(self.results, tuple):
             temperature = self.results[1]
         else:
@@ -209,7 +209,7 @@ def _get_hourly_cop_dhw(self, power: np.ndarray = None) -> Union[float, np.ndarr
         if isinstance(self.cop, SCOP) and isinstance(self.eer, SEER) and isinstance(self.cop_dhw, SCOP):
             return self.cop_dhw.get_COP(0, power=np.nan_to_num(power))
         if isinstance(self.results, ResultsMonthly):
-            raise TypeError('You cannot get an hourly EER values based on monthly temperature results.')
+            raise TypeError('You cannot get an hourly COP values based on monthly temperature results.')
         if isinstance(self.results, tuple):
             temperature = self.results[1]
         else:
@@ -247,6 +247,64 @@ def _get_hourly_eer(self, power: np.ndarray = None) -> Union[float, np.ndarray]:
 
         return self.eer.get_EER(temperature, power=np.nan_to_num(power), month_indices=self.month_indices)
 
+    def _get_max_power_heating(self) -> Union[float, np.ndarray]:
+        """
+        This function returns the maximum power available in heating, taking into account the maximum power of the
+        heat pump (when available). When the attribute '_limit_to_max_heat_pump_power' is False, the input array
+        is simply returned.
+
+        Returns
+        -------
+        maximum heating power : float | np.ndarray
+            Array with the maximum heating power
+        """
+        if isinstance(self.cop, SCOP):
+            return self.hourly_heating_load_simulation_period
+        if isinstance(self.results, tuple):
+            temperature = self.results[1]
+        else:
+            temperature = self.results.Tf
+        return np.minimum(self.hourly_heating_load_simulation_period, self.cop._get_max_power(temperature))
+
+    def _get_max_power_dhw(self) -> Union[float, np.ndarray]:
+        """
+        This function returns the maximum power available in dhw, taking into account the maximum power of the
+        heat pump (when available). When the attribute '_limit_to_max_heat_pump_power' is False, the input array
+        is simply returned.
+
+        Returns
+        -------
+        maximum dhw power : float | np.ndarray
+            Array with the maximum dhw power
+        """
+        if isinstance(self.cop_dhw, SCOP):
+            return self.hourly_dhw_load_simulation_period
+        if isinstance(self.results, tuple):
+            temperature = self.results[1]
+        else:
+            temperature = self.results.Tf
+        return np.minimum(self.hourly_dhw_load_simulation_period, self.cop_dhw._get_max_power(temperature))
+
+    def _get_max_power_cooling(self) -> Union[float, np.ndarray]:
+        """
+        This function returns the maximum power available in cooling, taking into account the maximum power of the
+        heat pump (when available). When the attribute '_limit_to_max_heat_pump_power' is False, the input array
+        is simply returned.
+
+        Returns
+        -------
+        maximum cooling power : float | np.ndarray
+            Array with the maximum cooling power
+        """
+        if isinstance(self.eer, SEER):
+            return self.hourly_cooling_load_simulation_period
+        if isinstance(self.results, tuple):
+            temperature = self.results[1]
+        else:
+            temperature = self.results.Tf
+        return np.minimum(self.hourly_cooling_load_simulation_period, self.eer._get_max_power(temperature, month_indices=self.month_indices))
+
+
     @property
     def hourly_injection_load_simulation_period(self) -> np.ndarray:
         """
@@ -258,6 +316,10 @@ def hourly_injection_load_simulation_period(self) -> np.ndarray:
             Hourly injection values [kWh/h] for the whole simulation period
         """
         part_load = self.hourly_cooling_load_simulation_period
+        if self._limit_to_max_heat_pump_power:
+            return np.multiply(
+            self._get_max_power_cooling(),
+            self.conversion_factor_secondary_to_primary_cooling(self._get_hourly_eer(part_load)))
         return np.multiply(
             self.hourly_cooling_load_simulation_period,
             self.conversion_factor_secondary_to_primary_cooling(self._get_hourly_eer(part_load)))
@@ -285,6 +347,10 @@ def _hourly_extraction_load_heating_simulation_period(self) -> np.ndarray:
             Hourly extraction values [kWh/h] for the whole simulation period
         """
         part_load = self.hourly_heating_load_simulation_period
+        if self._limit_to_max_heat_pump_power:
+            return np.multiply(
+            self._get_max_power_heating(),
+            self.conversion_factor_secondary_to_primary_heating(self._get_hourly_cop(part_load)))
         return np.multiply(
             self.hourly_heating_load_simulation_period,
             self.conversion_factor_secondary_to_primary_heating(self._get_hourly_cop(part_load)))
@@ -300,6 +366,9 @@ def _hourly_extraction_load_dhw_simulation_period(self) -> np.ndarray:
             Hourly extraction values [kWh/h] for the whole simulation period
         """
         part_load_dhw = self.hourly_dhw_load_simulation_period
+        if self._limit_to_max_heat_pump_power:
+            return np.multiply(            self._get_max_power_dhw(),
+                self.conversion_factor_secondary_to_primary_heating(self._get_hourly_cop_dhw(part_load_dhw)))
         return np.multiply(
             self.hourly_dhw_load_simulation_period,
             self.conversion_factor_secondary_to_primary_heating(self._get_hourly_cop_dhw(part_load_dhw)))

GHEtool/VariableClasses/LoadData/Baseclasses/_LoadDataBuilding.py

@@ -47,8 +47,12 @@ def __init__(self,
         self._cop_dhw = None
         self._results = None
         self._results_fixed = (0, 17)
-        self.exclude_DHW_from_peak: bool = False  # by default, the DHW increase the peak load. Set to false,
+
+        # False by default, the DHW increase the peak load. Set to false,
         # if you only want the heating load to determine the peak in extraction
+        self.exclude_DHW_from_peak: bool = False
+
+        self._limit_to_max_heat_pump_power: bool = False
 
         # set variables
         self.cop = efficiency_heating
@@ -398,7 +402,7 @@ def _get_monthly_cop(self, peak: bool, power: np.ndarray = None) -> Union[float,
         elif peak:
             temperature = self.results.peak_extraction
         else:
-            temperature = self.results.monthly_extraction
+            temperature = self.results.baseload_temperature
 
         return self.cop.get_COP(temperature, power=np.nan_to_num(power))
 
@@ -424,7 +428,7 @@ def _get_monthly_cop_dhw(self, peak: bool, power: np.ndarray = None) -> Union[fl
         elif peak:
             temperature = self.results.peak_extraction
         else:
-            temperature = self.results.monthly_extraction
+            temperature = self.results.baseload_temperature
 
         return self.cop_dhw.get_COP(temperature, power=np.nan_to_num(power))
 
@@ -454,6 +458,63 @@ def _get_monthly_eer(self, peak: bool, power: np.ndarray = None) -> Union[float,
 
         return self.eer.get_EER(temperature, power=np.nan_to_num(power), month_indices=self.month_indices)
 
+    def _get_max_power_heating_monthly(self) -> Union[float, np.ndarray]:
+        """
+        This function returns the maximum power available in heating, taking into account the maximum power of the
+        heat pump (when available). When the attribute '_limit_to_max_heat_pump_power' is False, the input array
+        is simply returned.
+
+        Returns
+        -------
+        maximum heating power : float | np.ndarray
+            Array with the maximum heating power
+        """
+        if isinstance(self.cop, SCOP):
+            return self.monthly_peak_heating_simulation_period
+        if isinstance(self.results, tuple):
+            temperature = self.results[1]
+        else:
+            temperature = self.results.Tf
+        return np.minimum(self.monthly_peak_heating_simulation_period, self.cop._get_max_power(temperature))
+
+    def _get_max_power_dhw_monthly(self) -> Union[float, np.ndarray]:
+        """
+        This function returns the maximum power available in dhw, taking into account the maximum power of the
+        heat pump (when available). When the attribute '_limit_to_max_heat_pump_power' is False, the input array
+        is simply returned.
+
+        Returns
+        -------
+        maximum dhw power : float | np.ndarray
+            Array with the maximum dhw power
+        """
+        if isinstance(self.cop_dhw, SCOP):
+            return self.monthly_peak_dhw_simulation_period
+        if isinstance(self.results, tuple):
+            temperature = self.results[1]
+        else:
+            temperature = self.results.Tf
+        return np.minimum(self.monthly_peak_dhw_simulation_period, self.cop_dhw._get_max_power(temperature))
+
+    def _get_max_power_cooling_monthly(self) -> Union[float, np.ndarray]:
+        """
+        This function returns the maximum power available in cooling, taking into account the maximum power of the
+        heat pump (when available). When the attribute '_limit_to_max_heat_pump_power' is False, the input array
+        is simply returned.
+
+        Returns
+        -------
+        maximum cooling power : float | np.ndarray
+            Array with the maximum cooling power
+        """
+        if isinstance(self.eer, SEER):
+            return self.monthly_peak_cooling_simulation_period
+        if isinstance(self.results, tuple):
+            temperature = self.results[1]
+        else:
+            temperature = self.results.Tf
+        return np.minimum(self.monthly_peak_cooling_simulation_period, self.eer._get_max_power(temperature, month_indices=self.month_indices))
+
     @staticmethod
     def conversion_factor_secondary_to_primary_heating(cop_value: Union[int, float, np.ndarray]) -> Union[
         float, np.ndarray]:
@@ -560,6 +621,10 @@ def monthly_peak_injection_simulation_period(self) -> np.ndarray:
             Peak injection for the whole simulation period
         """
         part_load = self.monthly_peak_cooling_simulation_period
+        if self._limit_to_max_heat_pump_power:
+            return np.multiply(
+            self._get_max_power_cooling_monthly(),
+            self.conversion_factor_secondary_to_primary_cooling(self._get_monthly_eer(True,part_load)))
         return np.multiply(
             self.monthly_peak_cooling_simulation_period,
             self.conversion_factor_secondary_to_primary_cooling(self._get_monthly_eer(True, part_load)))
@@ -591,6 +656,10 @@ def _monthly_peak_extraction_heating_simulation_period(self) -> np.ndarray:
             Peak extraction for the whole simulation period
         """
         part_load = self.monthly_peak_heating_simulation_period
+        if self._limit_to_max_heat_pump_power:
+            return np.multiply(
+            self._get_max_power_heating_monthly(),
+            self.conversion_factor_secondary_to_primary_heating(self._get_monthly_cop(True,part_load)))
         return np.multiply(
             self.monthly_peak_heating_simulation_period,
             self.conversion_factor_secondary_to_primary_heating(self._get_monthly_cop(True, part_load)))
@@ -606,6 +675,10 @@ def _monthly_peak_extraction_dhw_simulation_period(self) -> np.ndarray:
             Peak extraction for the whole simulation period
         """
         part_load_dhw = self.monthly_peak_dhw_simulation_period
+        if self._limit_to_max_heat_pump_power:
+            return np.multiply(
+            self._get_max_power_dhw_monthly(),
+            self.conversion_factor_secondary_to_primary_heating(self._get_monthly_cop_dhw(True,part_load_dhw)))
         return np.multiply(
             self.monthly_peak_dhw_simulation_period,
             self.conversion_factor_secondary_to_primary_heating(self._get_monthly_cop_dhw(True, part_load_dhw)))