Fix: minor fix

Author: sertomas

.gitignore

@@ -93,6 +93,10 @@ target/
 profile_default/
 ipython_config.py
 
+# Claude
+.claude
+CLAUDE.md
+
 # pyenv
 #   For a library or package, you might want to ignore these files since the code is
 #   intended to run in multiple environments; otherwise, check them in:

examples/butane_hp/butane_hp_tespy.py

@@ -0,0 +1,297 @@
+import numpy as np
+from CoolProp.CoolProp import PropsSI as PSI
+from tespy.components import (
+    Compressor,
+    CycleCloser,
+    HeatExchanger,
+    Merge,
+    Motor,
+    MovingBoundaryHeatExchanger,
+    PowerSource,
+    Sink,
+    Source,
+    Splitter,
+    Valve,
+)
+from tespy.connections import Connection, PowerConnection
+from tespy.networks import Network
+
+# "Bus" Parameters
+# Heat source
+T_ev_in = 25
+T_ev_out = 15
+p_ev = 1
+# Water/steam side
+T_co_in = 45
+T_co_out = 105
+p_co = 1
+# T_co_out = 65
+# p_co = 0.2
+
+# Default component parameters
+td_pinch = 5
+td_dew = 5
+eta_s = 0.8
+
+wf = "Butane"
+
+# Preliminary calculations, actually optimization variables...
+p_ev_wf = PSI("P", "Q", 1, "T", T_ev_out - td_pinch + 273.15, wf) * 1e-5
+# p_co_wf = PSI('P', 'Q', 0, 'T', PSI('T', 'Q', 1, 'P', p_co * 1e5, 'water') + td_pinch, wf) * 1e-5
+p_co_wf = (
+    PSI("P", "Q", 0, "T", PSI("T", "Q", 1, "P", p_co * 1e5, "water") + td_pinch + td_dew, wf) * 1e-5
+)  # hier müsste der Druck wirklich sukzessive gesenkt werden...
+pr_tot = p_co_wf / p_ev_wf
+pr_per_stage = np.power(pr_tot, 1 / 2)
+p_mid_wf = p_ev_wf * pr_per_stage
+
+# Create the network
+nw = Network(T_unit="C", p_unit="bar", h_unit="kJ / kg", m_unit="t / h", iterinfo=False)
+
+# Create the components
+# Ammonia cycle
+compressor_1 = Compressor("Compressor 1")
+compressor_2 = Compressor("Compressor 2")
+evaporator = HeatExchanger("Evaporator")
+expansion_valve_1 = Valve("Expansion Valve 1")
+expansion_valve_2 = Valve("Expansion Valve 2")
+cycle_closer = CycleCloser("Cycle Closer")
+condenser = MovingBoundaryHeatExchanger("Condenser")
+splitter = Splitter("Splitter")
+merge = Merge("Merge")
+economizer = MovingBoundaryHeatExchanger("Economizer")
+
+# Water/steam side
+water_in = Source("Water In")
+steam_out = Sink("Steam Out")
+
+# Heat source
+heat_source_in = Source("Heat Source In")
+heat_source_out = Sink("Heat Source Out")
+
+motor_1 = Motor("Motor 1")
+motor_2 = Motor("Motor 2")
+grid_1 = PowerSource("Grid 1")
+grid_2 = PowerSource("Grid 2")
+
+# Create connections
+# Ammonia cycle
+c1 = Connection(cycle_closer, "out1", compressor_1, "in1", label="01")
+c2 = Connection(compressor_1, "out1", merge, "in1", label="02")
+c3 = Connection(merge, "out1", compressor_2, "in1", label="03")
+c4 = Connection(compressor_2, "out1", condenser, "in1", label="04")
+c5 = Connection(condenser, "out1", splitter, "in1", label="05")
+c5a = Connection(splitter, "out1", economizer, "in1", label="05a")
+c6 = Connection(economizer, "out1", expansion_valve_1, "in1", label="06")
+c7 = Connection(expansion_valve_1, "out1", evaporator, "in2", label="07")
+c0cc = Connection(evaporator, "out2", cycle_closer, "in1", label="07cc")
+c5b = Connection(splitter, "out2", expansion_valve_2, "in1", label="05b")
+c8 = Connection(expansion_valve_2, "out1", economizer, "in2", label="08")
+c9 = Connection(economizer, "out2", merge, "in2", label="09")
+
+# Water/steam side
+c10 = Connection(water_in, "out1", condenser, "in2", label="10")
+c11 = Connection(condenser, "out2", steam_out, "in1", label="11")
+
+# Heat source
+c20 = Connection(heat_source_in, "out1", evaporator, "in1", label="20")
+c21 = Connection(evaporator, "out1", heat_source_out, "in1", label="21")
+
+# Power connections
+e01 = PowerConnection(grid_1, "power", motor_1, "power_in", label="E1")
+w01 = PowerConnection(motor_1, "power_out", compressor_1, "power", label="W1")
+e02 = PowerConnection(grid_2, "power", motor_2, "power_in", label="E2")
+w02 = PowerConnection(motor_2, "power_out", compressor_2, "power", label="W2")
+
+# Add connections to network
+nw.add_conns(c1, c2, c3, c4, c5, c5a, c5b, c6, c7, c8, c9, c0cc, c10, c11, c20, c21, e01, e02, w01, w02)
+
+# Set component parameters
+compressor_1.set_attr(eta_s=eta_s)
+compressor_2.set_attr(eta_s=eta_s)
+condenser.set_attr(pr1=1, pr2=1, td_pinch=td_pinch)
+evaporator.set_attr(pr1=1, pr2=1, ttd_min=td_pinch)
+economizer.set_attr(pr1=1, pr2=1, td_pinch=td_pinch)
+motor_1.set_attr(eta=0.985)
+motor_2.set_attr(eta=0.985)
+
+# Set connection parameters
+# Water/steam side
+c10.set_attr(fluid={"water": 1}, p=p_co, T=T_co_in, m=1)  # Water inlet
+c11.set_attr(T=T_co_out)  # Steam outlet
+
+# Heat source
+c20.set_attr(fluid={"air": 1}, p=p_ev, T=T_ev_in)  # Heat source inlet
+c21.set_attr(T=T_ev_out)  # Heat source outlet
+
+# Butane cycle
+c7.set_attr(fluid={wf: 1})  # Pure butane
+c1.set_attr(p=p_ev_wf)
+c2.set_attr(p=p_mid_wf)
+c4.set_attr(p=p_co_wf)
+
+# Generate starting values
+condenser.set_attr(td_pinch=None)
+evaporator.set_attr(ttd_min=None)
+economizer.set_attr(td_pinch=None)
+
+c1.set_attr(T=T_ev_in - td_pinch)
+c4.set_attr(td_dew=td_dew)
+c5.set_attr(T=T_co_in + td_pinch)
+c6.set_attr(T=T_co_in)
+nw.solve("design")
+
+# Solve real design
+condenser.set_attr(td_pinch=td_pinch)  # For condenser
+c5.set_attr(T=None)
+evaporator.set_attr(ttd_min=td_pinch)
+c1.set_attr(T=None)
+economizer.set_attr(td_pinch=td_pinch)
+c6.set_attr(T=None)
+
+nw.solve("design")
+
+# Exergy analysis via ExerPy
+from exerpy import ExergyAnalysis
+
+p0 = 1.000e5
+T0 = 25 + 273.15
+
+ean = ExergyAnalysis.from_tespy(nw, Tamb=T0, pamb=p0, split_physical_exergy=True)
+fuel = {"inputs": ["E1", "E2"], "outputs": []}
+product = {"inputs": ["11"], "outputs": ["10"]}
+loss = {"inputs": ["21"], "outputs": ["20"]}
+ean.analyse(E_F=fuel, E_P=product, E_L=loss)
+df_component_results, df_material_connection_results, df_non_material_connection_results = ean.exergy_results(
+    print_results=False
+)
+
+from exerpy import EconomicAnalysis, ExergoeconomicAnalysis
+
+# Define the CEPCI values for cost correction.
+CEPCI_2013 = 567.3
+CEPCI_2023 = 797.9
+CEPCI_factor = CEPCI_2023 / CEPCI_2013
+
+# Define values for electricity price and full load hours.
+elec_price_cent_kWh = 40.0  # cent/kWh
+tau = 5500  # hours/year
+
+# Define economic parameters.
+r_n = 0.02  # Cost elevation rate
+i_eff = 0.08  # Interest rate
+n = 20  # Number of years
+omc_relative = 0.03  # Relative operation and maintenance costs (compared to PEC)
+
+import pandas as pd
+from tabulate import tabulate
+
+k_lookup = {"Evaporator": 100, "Economizer": 750, "Condenser": 1000}
+
+PEC_computed = {}
+for comp in nw.comps["object"]:
+    name = comp.label
+    PEC = 0.0  # Default PEC
+    # --- Heat Exchangers ---
+    if isinstance(comp, (HeatExchanger, MovingBoundaryHeatExchanger)):
+        kA = getattr(comp.kA, "val", 0.0)
+        if kA:
+            k = k_lookup.get(name)
+            if k is None:
+                raise KeyError(f"No k-value defined for heat exchanger '{name}'")
+            A = kA / k
+            PEC = 15526 * (A / 42) ** 0.8 * CEPCI_factor
+        else:
+            PEC = 0.0
+        PEC_computed[name] = PEC
+
+    # --- Compressors (and Fans) ---
+    elif isinstance(comp, Compressor):
+        VM = getattr(comp.inl[0].v, "val", 0.0)
+        PEC = 19850 * ((VM * 3600) / 279.8) ** 0.73
+        PEC *= CEPCI_factor  # Adjust PEC cost.
+        PEC_computed[name] = PEC
+
+    # --- Other components ---
+    else:
+        PEC_computed[name] = 0.0
+
+
+for comp in ean.components.values():
+    if comp.__class__.__name__ == "Motor":
+        name = comp.name
+        # Retrieve the electrical input power X from the attribute "energy_flow_1"
+        X = getattr(comp, "E_F", None)
+        if X is not None:
+            PEC = 10710 * (X / 250000) ** 0.65
+            PEC *= CEPCI_factor  # Adjust PEC cost.
+        else:
+            PEC = 0.0
+        PEC_computed[name] = PEC
+
+# ------------------------------
+# Economic Analysis
+# ------------------------------
+# Convert electricity price from cent/kWh to €/GJ.
+# 1 kWh = 3.6 MJ and 1 GJ = 277.78 kWh.
+elec_cost_eur_per_kWh = elec_price_cent_kWh / 100.0
+elec_cost_eur_per_GJ = elec_cost_eur_per_kWh * 277.78
+
+econ_pars = {"tau": tau, "i_eff": i_eff, "n": n, "r_n": r_n}
+components_order = list(PEC_computed.keys())
+PEC_list = [PEC_computed[comp] for comp in components_order]
+# Multiply each PEC by 6.32 to obtain TCI.
+TCI_list = [pec * 6.32 for pec in PEC_list]
+OMC_relative = [omc_relative if pec > 0 else 0.0 for pec in TCI_list]
+
+econ_analysis = EconomicAnalysis(econ_pars)
+Z_CC, Z_OMC, Z_total = econ_analysis.compute_component_costs(TCI_list, OMC_relative)
+
+# Create a DataFrame to display PEC, TCI, annual OMC, and Z for each component
+component_costs_df = pd.DataFrame(
+    {
+        "Component": components_order,
+        "PEC [EUR]": [round(pec, 2) for pec in PEC_list],
+        "CC [EUR]": [round(tci, 2) for tci in TCI_list],
+        "Z_CC [EUR/h]": [round(z_cc, 2) for z_cc in Z_CC],
+        "Z_OMC [EUR/h]": [round(omc, 2) for omc in Z_OMC],
+        "Z [EUR/h]": [round(z, 2) for z in Z_total],
+    }
+)
+
+# Calculate totals
+total_pec = sum(PEC_list)
+total_tci = sum(TCI_list)
+total_z_cc = sum(Z_CC)
+total_z_omc = sum(Z_OMC)
+total_z = sum(Z_total)
+
+# Add a total row
+component_costs_df.loc[len(component_costs_df)] = [
+    "TOTAL",
+    round(total_pec, 2),
+    round(total_tci, 2),
+    round(total_z_cc, 2),
+    round(total_z_omc, 2),
+    round(total_z, 2),
+]
+
+# Print the component costs table without separators
+print("\nComponent Investment Costs (Year 2023):")
+print(tabulate(component_costs_df, headers="keys", tablefmt="psql", floatfmt=".2f"))
+
+# Build the exergoeconomic cost dictionary.
+Exe_Eco_Costs = {}
+for comp, z in zip(components_order, Z_total, strict=False):
+    Exe_Eco_Costs[f"{comp}_Z"] = z
+Exe_Eco_Costs["10_c"] = 0.0
+Exe_Eco_Costs["20_c"] = 0.0
+Exe_Eco_Costs["E2_c"] = elec_cost_eur_per_GJ
+
+# ------------------------------
+# Exergoeconomic Analysis
+# ------------------------------
+exergoeco_analysis = ExergoeconomicAnalysis(ean)
+exergoeco_analysis.run(Exe_Eco_Costs=Exe_Eco_Costs, Tamb=ean.Tamb)
+# Unpack four DataFrames; we only use the component results.
+df_comp, df_mat1, df_mat2, df_non_mat = exergoeco_analysis.exergoeconomic_results()

examples/cgam/cgam_tespy.py

@@ -97,20 +97,15 @@
 nwk.assert_convergence()
 
 nwk.print_results()
-# %%[tespy_model_section_end]
 p0 = 101300
 T0 = 298.15
 
 ean = ExergyAnalysis.from_tespy(nwk, T0, p0, chemExLib="Ahrendts", split_physical_exergy=False)
-# %%[exergy_analysis_setup]
 fuel = {"inputs": ["1", "10"], "outputs": []}
-
 product = {"inputs": ["e3", "9"], "outputs": ["8"]}
-
 loss = {"inputs": ["7"], "outputs": []}
-# %%[exergy_analysis_flows]
+
 ean.analyse(E_F=fuel, E_P=product, E_L=loss)
 df_component_results, _, _ = ean.exergy_results()
-ean.export_to_json("examples/cgam/cgam_tespy.json")
-df_component_results.to_csv("examples/cgam/cgam_components_tespy.csv")
-# %%[exergy_analysis_results]
+# ean.export_to_json("examples/cgam/cgam_tespy.json")
+# df_component_results.to_csv("examples/cgam/cgam_components_tespy.csv")

examples/hp_cascade/hp_cascade_json.py

@@ -59,7 +59,7 @@ def run_exergoeco_analysis(elec_price_cent_kWh, tau):
 
     # Run the exergy analysis.
     ean.analyse(E_F=fuel, E_P=product, E_L=loss)
-    ean.exergy_results(print_results=True)
+    ean.exergy_results(print_results=False)
 
     # ------------------------------
     # PEC Calculation Using Class-Based Correlations with cost correction

examples/hp_cascade/hp_cascade_tespy.py

@@ -527,7 +527,7 @@ def run_sensitivity_analysis(var_name, values):
 plt.title("Normalized investmenet costs and exergy destruction")
 plt.grid(True)
 plt.tight_layout()
-plt.savefig(f"examples/hp_cascade_hp/plots/plot_normalized_scatter_{SENS_VAR_savefig}.png", dpi=300)
+plt.savefig(f"examples/hp_cascade/plots/plot_normalized_scatter_{SENS_VAR_savefig}.png", dpi=300)
 
 
 # 3. Stacked Bar Chart: Z per Component + COP Overlay