# -*- coding: utf-8 -*-
"""
Created on Mon Oct 16 11:13:12 2023
@author: atakan
"""
import numpy as np
import carbatpy as cb
import pandas as pd
import seaborn as sbn
import matplotlib.pyplot as plt
import datetime
[docs]dir_name = cb._RESULTS_DIR + "\\optimal_hp_fluid"
[docs]fname = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M")+"threeAlkanes"
plt.style.use('seaborn-v0_8-poster') # 'seaborn-v0_8-poster')
[docs]FLUID_COMP = "Propane * Butane * Pentane" # " * Hexane"
[docs]comp = [.5, 0., 0.5] # , 0.0]
# comp =[0.000,1.0,0.00,0.0]
[docs]FLCOLD = "Methanol" # "Water" #
[docs]flm = cb.fprop.fluid_model(FLUID_COMP)
[docs]my_fluid = cb.fprop.Fluid(flm, comp)
[docs]secFlm = cb.fprop.fluid_model(FLS)
[docs]secondary_fluid = cb.fprop.Fluid(secFlm, [1.])
[docs]coldFlm = cb.fprop.fluid_model(FLCOLD)
[docs]cold_fluid_act = cb.fprop.Fluid(coldFlm, [1.])
# Condenser(c) and storage (s), secondary fluids fix all, temperatures(T in K),
# pressures (p in Pa)
[docs]SECONDARY_TEMP_IN = 290.0
[docs]COLD_TEMP_IN = SECONDARY_TEMP_IN
[docs]SECONDARY_TEMP_OUT = 363. # 395.0
[docs]DH_MIN = 1E3 # AND HEAT_FLOW RATE (W)
[docs]D_TEMPMIN = 1.530 # MINIMUM APPROACH TEMPERATURE (PINCH POINT)
[docs]state_sec_in = secondary_fluid.set_state([SECONDARY_TEMP_IN, SP_IN], "TP")
[docs]state_cold_in = cold_fluid_act.set_state([COLD_TEMP_IN, CP_IN], "TP")
# working fluid
[docs]D_TEMPSUPER = 5. # super heating of working fluid
[docs]TEMP_DEW = SECONDARY_TEMP_OUT
state_in_act = my_fluid.set_state([TEMP_DEW, 1.], "TQ") # find minimum pressure
[docs]TEMP_IN = TEMP_DEW + D_TEMPSUPER
state_in_act = my_fluid.set_state([my_fluid.properties.pressure,
my_fluid.properties.temperature + D_TEMPSUPER], "PT")
[docs]p_high_act = state_in_act[1]
state_in_act = my_fluid.set_state(
[SECONDARY_TEMP_IN - D_TEMPSUPER, 1.], "TQ") # find minimum pressure
[docs]p_low_act = state_in_act[1]
state_in_act = my_fluid.set_state([p_low_act,
SECONDARY_TEMP_IN - D_TEMPMIN], "PT")
print(f"p-ratio: {p_high_act/p_low_act: .2f}, p_low: {p_low_act/1e5: .2} bar")
[docs]state_in_act = my_fluid.set_state([p_low_act, TEMP_IN], "PT")
[docs]fixed_points_act = {"eta_s": ETA_S,
"p_low": p_low_act,
"temp_hh": SECONDARY_TEMP_OUT,
"temp_hl": SECONDARY_TEMP_IN,
"temp_lh": SECONDARY_TEMP_IN,
"temp_ll": COLD_TEMP_OUT,
"q_dot_h": Q_DOT_H,
"d_tempmin": D_TEMPMIN}
[docs]hp0_act = cb.hp_simple.heat_pump([my_fluid, secondary_fluid, cold_fluid_act],
fixed_points_act)
[docs]cop_act = hp0_act.calc_p_high(p_high_act)
hp0_act.hp_plot()
[docs]out = hp0_act.evaluation
print(
f"COP: {out[0]/out[1]:.2f},p-ratio: { out[2]/out[3]:.2f}, p_low {out[3]/1e5:.2f} bar")
[docs]def hp_comp_cop(composition, work_fluid, sec_fluid, cold_fluid,
fixed_points, d_tempsuper=5.0, opt=+1):
# working fluid
sum3 = np.sum(composition)
if sum3 > 1:
return 0
last = 1-sum3
new_composition = np.array([*composition, last])
work_fluid.set_composition(new_composition)
temp_dew = fixed_points["temp_hh"]
state_in = work_fluid.set_state(
[temp_dew, 1.], "TQ") # find minimum pressure
# TEMP_IN = temp_dew + D_TEMPSUPER
state_in = work_fluid.set_state([work_fluid.properties.pressure,
work_fluid.properties.temperature + D_TEMPSUPER], "PT")
p_high = state_in[1]
state_in = work_fluid.set_state(
[fixed_points["temp_lh"] - d_tempsuper, 1.], "TQ") # find minimum pressure
p_low = state_in[1]
state_in = my_fluid.set_state([p_low,
SECONDARY_TEMP_IN - D_TEMPMIN], "PT")
fixed_points["p_low"] = p_low
hp0 = cb.hp_simple.heat_pump(
[work_fluid, sec_fluid, cold_fluid], fixed_points)
cop = hp0.calc_p_high(p_high)
print("Result-hp-opt:", new_composition, np.sum(new_composition),
cop, p_low, p_high, p_high/p_low)
if opt == -1:
return cop * opt
return cop, p_low/1e5, p_high/1e5
all_res = []
[docs]x0_range = np.linspace(0.0, 0.6, 12)
[docs]x1_range = np.linspace(0, 0.6, 10)
for x0 in x0_range:
for x1 in x1_range:
if x0+x1 <= 1:
comp = np.array([x0, x1])
results = hp_comp_cop(comp, my_fluid, secondary_fluid,
cold_fluid_act,
fixed_points_act,
d_tempsuper=D_TEMPSUPER,
opt=+1)
if results[0] > 1:
new = np.array([*results, x0, x1, x2,
*fixed_points_act.values()])
all_res.append(new)
[docs]names = ["COP", "$p_{low}$", "$p_{high}$", "$x_{Propane}$",
"$x_{Butane}$", "$x_{Pentane}$", *fixed_points_act.keys()]
[docs]all_res = np.array(all_res)
[docs]dframe = pd.DataFrame(all_res, columns=names)
dframe.to_csv(dir_name+"\\"+fname+".csv")
[docs]dframe2 = dframe.round(3)
f, ax = plt.subplots(figsize=(10, 6), layout="constrained")
[docs]fff = sbn.scatterplot(x=names[4], y=names[5],
hue=names[2], size=names[0], data=dframe2, ax=ax)
sbn.move_legend(fff, "upper left", bbox_to_anchor=(1, 1))
f.savefig(dir_name+"\\"+fname+".png")
# bounds = ((0.05, 0.95), (0.00, 0.65))
# def constr(comp):
# print(comp, np.sum(comp))
# return 1-np.sum(comp)
# res = opt.differential_evolution(hp_comp_cop, bounds,
# args=(my_fluid, secFluid, cold_fluid_act, fixed_points)
# )
# print(res)