Implement an example for pinch analysis through coupling tespy with pina

pyproject.toml

@@ -53,6 +53,7 @@ dependencies = [
     "matplotlib>=3.2.1",
     "numpy>=1.13.3",
     "pandas>=1.3.0",
+    "pina>=0.1.1",
     "pint",
     "scipy",
     "tabulate>=0.8.2",

src/tespy/tools/pinch_analysis.py

@@ -0,0 +1,297 @@
+# using pina 0.1.1 for pinch related tasks
+from pina import PinchAnalyzer, make_stream
+import matplotlib.pyplot as plt
+
+# Useful literature: 
+# Arpagaus 2019 Hochtemperatur-Wärmepumpen (ISBN 978-3-8007-4550-0)
+# Kemp 2006 (p.20) (https://doi.org/10.1016/B978-0-7506-8260-2.X5001-9)
+# Walden et al. 2023 (https://doi.org/10.1016/j.apenergy.2023.121933)
+
+
+class TesypPinchAnalysis():
+
+    def __init__(self, label:str):
+        self.min_dT = None
+        self.temp_shift = None
+        self.streams = []
+        self.analyzer = None
+        self.label = label
+        self.gcc_fig = None
+        self.gcc_data_enthalpy = None
+
+
+    # including the general functions of pina to expand them later
+
+
+    # setting the value for shifting the composit curces (CCs)
+    def set_minimum_temperature_difference(self, minimum_temperature_difference:float):
+        # minimum temperature difference of streams 
+        self.min_dT = minimum_temperature_difference
+        # the hot and cold composit curve (CC) are shifted by half the minimum temperature difference to meet at the pinch point
+        self.temp_shift = self.min_dT / 2
+
+
+    # adding cold streams to the used streams, colsd streams have to be heated and form the cold composite curvve (cold CC)
+    def add_cold_stream_manually(self, enthalpy_difference:float, T_inlet:float, T_outlet:float):
+        # check if the stream has a positive enthalpy flow difference, pina needs negative sign for hot streams, way to check user
+        if enthalpy_difference > 0:
+            print("Got positive enthaply difference, expected negative enthalpy for cold streams. stream not added")
+        else:
+            self.streams.append(make_stream(enthalpy_difference,T_inlet,T_outlet))
+
+
+    # adding cold streams to the used streams, colsd streams have to be heated and form the cold composite curvve (hot CC)
+    def add_hot_stream_manually(self,  enthalpy_difference:float, T_inlet:float, T_outlet:float):
+        # check if the stream has a negative enthalpy flow difference, pina needs positive sign for cold streams, way to check user
+        if enthalpy_difference < 0:
+            print("Got positive enthaply difference, expected negative enthalpy for cold streams. stream not added")
+        else:
+            self.streams.append(make_stream(enthalpy_difference,T_inlet,T_outlet))
+
+
+    # add: functions to read lists for hot and cold later
+
+
+    # add: functions to remove streams later
+
+
+    # create the pinch analyzer from pina
+    def _create_analyzer(self):
+        # check if necessary input is set
+        if self.temp_shift is not None:
+            self.analyzer = PinchAnalyzer(self.temp_shift)
+        else:
+            print("set minimum temperature difference first")
+            return
+        self.analyzer.add_streams(*self.streams) # add a way to add streams later
+        self._get_analyzer_data()
+
+
+    # get datapoints of hot composite curve
+    def get_hot_cc(self):
+        if self.analyzer is None:
+            self._create_analyzer()
+        [self.hot_cc_data_enthalpy, self.hot_cc_data_temperature] = self.analyzer.hot_composite_curve
+
+
+    # get datapoints of cold composite curve
+    def get_cold_cc(self):
+        if self.analyzer is None:
+            self._create_analyzer()
+        [self.cold_cc_data_enthalpy, self.cold_cc_data_temperature] = self.analyzer.cold_composite_curve
+
+
+    # get datapoints of shifted hot composite curve
+    def get_shifted_hot_cc(self):
+        if self.analyzer is None:
+            self._create_analyzer()
+        [self.shifted_hot_cc_data_enthalpy, self.shifted_hot_cc_data_temperature] = self.analyzer.shifted_hot_composite_curve
+
+
+    # get datapoints of shifted cold composite curve
+    def get_shifted_cold_cc(self):
+        if self.analyzer is None:
+            self._create_analyzer()
+        [self.shifted_cold_cc_data_enthalpy, self.shifted_cold_cc_data_temperature] = self.analyzer.shifted_cold_composite_curve
+
+
+    # get datapoints of grand composite curve
+    def get_gcc(self):
+        if self.analyzer is None:
+            self._create_analyzer()
+        [self.gcc_data_enthalpy, self.gcc_data_shifted_temperature] = self.analyzer.grand_composite_curve
+
+
+    def _get_analyzer_data(self):  
+        # get additional analysis data from pina
+        self.T_pinch = self.analyzer.pinch_temps[0]
+        self.cold_utility = self.analyzer.cold_utility_target
+        self.hot_utility = self.analyzer.hot_utility_target
+        self.heat_recovery = self.analyzer.heat_recovery_target
+
+        # needed to check e.g. pinch rules for heat pump integration automatically
+
+
+    def plot_cc_diagram(self, save_fig:bool = True, show_fig:bool = False, return_fig:bool = False):
+        fig, ax = plt.subplots()
+        # activate minor ticks
+        ax.minorticks_on()
+        # plot subplots with same axes limits
+        ax.plot(self.hot_cc_data_enthalpy, self.hot_cc_data_temperature, color = "red")
+        ax.plot(self.cold_cc_data_enthalpy, self.cold_cc_data_temperature, color = "blue")
+        # add visualization of sections
+        # get minimum temperature
+        T_min_CC = min(min(self.hot_cc_data_temperature), min(self.cold_cc_data_temperature))
+        ax.plot([0,self.cold_utility,self.heat_recovery+self.cold_utility,
+                 self.heat_recovery+self.cold_utility+self.hot_utility],[T_min_CC-5]*4, "o-", color="black")
+        # adding annotations to the different sections
+        ax.annotate(f'{self.cold_utility:.0f}', xy=(self.cold_utility/2, T_min_CC-4), horizontalalignment='center', fontsize=10)
+        ax.annotate(f'{self.heat_recovery:.0f}', xy=(self.cold_utility + self.heat_recovery/2, T_min_CC-4), horizontalalignment='center', fontsize=10)
+        ax.annotate(f'{self.hot_utility:.0f}', xy=(self.cold_utility + self.heat_recovery + self.hot_utility/2, T_min_CC-4), horizontalalignment='center', fontsize=10)
+
+        # set x scale on lowest subplot
+        ax.tick_params(axis='x', which='major', labelsize=10, rotation = 0)
+        # set x label
+        ax.set_xlabel("$\dot{H}$ [kW]", loc='center', fontsize="10")
+        ax.xaxis.label.set_color("black")
+        # set y label
+        ax.set_ylabel("T [°C]", color = "black")
+        # set grid
+        ax.grid(visible=True, which='major', color='lightgrey', linewidth = 0.5)
+        ax.grid(visible=True, which='minor', color='lightgrey', linestyle='dotted', linewidth = 0.5)
+        # set aspect ratio of subplot
+        ax.set_box_aspect(1)
+        ax.set_title(f"Composite Curves of \"{self.label}\"",color = "black", fontsize = 10)
+
+        if save_fig:
+            fig.savefig(f"Composite_Curves_{self.label}.svg")
+        if show_fig:
+            fig.show()
+        if return_fig:
+            return fig
+
+
+    def plot_shifted_cc_diagram(self, save_fig:bool = True, show_fig:bool = False, return_fig:bool = False):
+        fig, ax = plt.subplots()
+        # activate minor ticks
+        ax.minorticks_on()
+        # plot subplots with same axes limits
+        ax.plot(self.shifted_hot_cc_data_enthalpy, self.shifted_hot_cc_data_temperature, color = "red")
+        ax.plot(self.shifted_cold_cc_data_enthalpy, self.shifted_cold_cc_data_temperature, color = "blue")
+        # add visualization of sections
+        # get minimum temperature
+        T_min_shifted_CC = min(min(self.shifted_hot_cc_data_temperature), min(self.shifted_cold_cc_data_temperature))
+        ax.plot([0,self.cold_utility,self.heat_recovery+self.cold_utility,
+                 self.heat_recovery+self.cold_utility+self.hot_utility],[T_min_shifted_CC-5]*4, "o-", color="black")
+        # adding annotations to the different sections
+        ax.annotate(f'{self.cold_utility:.0f}', xy=(self.cold_utility/2, T_min_shifted_CC-4), horizontalalignment='center', fontsize=10)
+        ax.annotate(f'{self.heat_recovery:.0f}', xy=(self.cold_utility + self.heat_recovery/2, T_min_shifted_CC-4), horizontalalignment='center', fontsize=10)
+        ax.annotate(f'{self.hot_utility:.0f}', xy=(self.cold_utility + self.heat_recovery + self.hot_utility/2, T_min_shifted_CC-4), horizontalalignment='center', fontsize=10)
+        # set x scale on lowest subplot
+        ax.tick_params(axis='x', which='major', labelsize=10, rotation = 0)
+        # set x label
+        ax.set_xlabel("$\dot{H}$ [kW]", loc='center', fontsize="10")
+        ax.xaxis.label.set_color("black")
+        # set y label
+        ax.set_ylabel("shifted T* [°C]", color = "black")
+        # set grid
+        ax.grid(visible=True, which='major', color='lightgrey', linewidth = 0.5)
+        ax.grid(visible=True, which='minor', color='lightgrey', linestyle='dotted', linewidth = 0.5)
+        # set aspect ratio of subplot
+        ax.set_box_aspect(1)
+        ax.set_title(f"Shifted Composite Curves of \"{self.label}\"",color = "black", fontsize = 10)
+
+        if save_fig:
+            fig.savefig(f"Shifted_Composite_Curves_{self.label}.svg")
+        if show_fig:
+            fig.show()
+        if return_fig:
+            return fig
+
+
+    def plot_gcc_diagram(self, save_fig:bool = True, show_fig:bool = False, return_fig:bool = False):
+        # plot
+        fig, ax = plt.subplots()
+        # activate minor ticks
+        ax.minorticks_on()
+        # get GCC data from pina, if not done manually before
+        if self.gcc_data_enthalpy is None:
+            self.get_gcc()
+        # plot subplots with same axes limits
+        ax.plot(self.gcc_data_enthalpy, self.gcc_data_shifted_temperature, color = "black")
+        # add pinch point
+        ax.plot(0, self.T_pinch, "o", color = "black")
+        # set x scale on lowest subplot
+        ax.tick_params(axis='x', which='major', labelsize=10, rotation = 0)
+        # set x label
+        ax.set_xlabel("$\Delta\dot{H}$ [kW]", loc='center', fontsize="10")
+        ax.xaxis.label.set_color("black")
+        # set x limit to 0
+        ax.set_xlim(xmin=0)
+        # set y label
+        ax.set_ylabel("shifted T* [°C]", color = "black")
+        # set grid
+        ax.grid(visible=True, which='major', color='lightgrey', linewidth = 0.5)
+        ax.grid(visible=True, which='minor', color='lightgrey', linestyle='dotted', linewidth = 0.5)
+        # set aspect ratio of subplot
+        ax.set_box_aspect(1)
+        ax.set_title(f"Grand Composite Curve of \"{self.label}\"",color = "black", fontsize = 10)
+
+        self.gcc_fig, self.gcc_ax = fig, ax
+
+        if save_fig:
+            fig.savefig(f"Grand_Composite_Curve_{self.label}.svg")
+        if show_fig:
+            fig.show()
+        if return_fig:
+            return fig
+
+
+    # add: include heat cascades later (for more than one point in time / investigated interval)
+
+
+    # adding components from tespy models
+
+    # adding a heat pump in the GCC (by referencing evaporator and condenser)  
+    def show_heat_pump_in_gcc(self, evaporator, condenser):
+        from tespy.components import SimpleHeatExchanger, MovingBoundaryHeatExchanger, SectionedHeatExchanger
+
+        # create GCC diagram, if not done before
+        try:
+            # get the GCC
+            fig = self.gcc_fig
+            ax = self.gcc_ax
+        except:
+            # create GCC without saving fig
+            self.plot_gcc_diagram(save_fig=False)
+            # get the GCC
+            fig = self.gcc_fig
+            ax = self.gcc_ax
+
+        # get the plotting data of the heat exchangers
+        # condensers
+        if isinstance(condenser,SimpleHeatExchanger):
+            # get plot data of heat exchangers at heat sink (taken from user meeting example of heat exchangers)
+            condenser_Q_vals = [0, abs(condenser.Q.val)]
+            condenser_T_vals = [condenser.outl[0].T.val,condenser.inl[0].T.val]
+            # to do: include a warning, if there is at least one change between to or from a latent stream
+        elif isinstance(condenser, SectionedHeatExchanger) or isinstance(condenser, MovingBoundaryHeatExchanger):
+            # get the data from calc_sections
+            condenser_Q_sections, condenser_T_steps_hot, condenser_T_steps_cold, condenser_Q_per_section, condenser_td_log_per_section = condenser.calc_sections()
+            condenser_Q_vals = [Q / 1000 for Q in condenser_Q_sections] # convert to kW
+            condenser_T_vals = [T - 273.17 for T in condenser_T_steps_hot] # convert to degC
+        else:
+            raise ValueError("The component type is not implemented as a condenser.")
+
+        # evaporators
+        if isinstance(evaporator,SimpleHeatExchanger):
+            # get plot data of heat exchangers at heat source (taken from user meeting example of heat exchangers)
+            evaporator_Q_vals = [0, abs(evaporator.Q.val)]         
+            evaporator_T_vals = [evaporator.inl[0].T.val,evaporator.outl[0].T.val]
+            # to do: include a warning, if there is at least one change between to or from a latent stream
+        elif isinstance(evaporator, SectionedHeatExchanger) or isinstance(evaporator, MovingBoundaryHeatExchanger):
+            # get the data from calc_sections
+            evaporator_Q_sections, evaporator_T_steps_hot, evaporator_T_steps_cold, evaporator_Q_per_section, evaporator_td_log_per_section = evaporator.calc_sections()
+            evaporator_Q_vals = [Q / 1000 for Q in evaporator_Q_sections] # convert to kW
+            evaporator_T_vals = [T - 273.17 for T in evaporator_T_steps_cold] # convert to degC
+        else:
+            raise ValueError("The component type is not implemented as an evaporator.")
+
+        # add: expand these conditions in future for other types
+        # missing: HeatExchanger, ParallelFlowHeatExchanger, Desuperheater, Condenser
+
+
+        # show (only display) by adding the plot data of the heat exchangers to the GCC
+        ax.plot(condenser_Q_vals, condenser_T_vals, "-",color="red") # as in heat exchanger example
+        ax.plot(evaporator_Q_vals, evaporator_T_vals, "-",color="blue")
+
+        # save figure
+        fig.savefig(f"GCC_with_heat_pump_{self.label}.svg")
+
+
+    # add: check heat pump integration by using the integration rules
+    # see e.g. Arpagaus 2019, Walden et al. 2023
+    # Temperature and heat flux
+
+    # add: def add_heat_exchanger_to_streams(self):
+        # function to read streams from given heat exchangers, later use to iterate all heat exchangers of network with possibility to exclude streams / heat exchangers