# -*- coding: utf-8 -*-
"""
Created on Tue May 21 13:56:39 2024
@author: atakan
"""
import copy
import numpy as np
import matplotlib.pyplot as plt
import carbatpy as cb
[docs]_RESULTS_ = cb._RESULTS_DIR
cb._T_SURROUNDING =20+273.15
if __name__ == "__main__":
# -------HEAT PUMP------------------------------
[docs] FLUID = "Propane * Butane * Pentane * Ethane"
# comp = [.15, 0.55, 0.0, 0.30]
# comp = [0.4, 0.3, 0.3, 0.0] # [0.164,.3330,.50300,0.0]
# comp = [.05, 0.65, 0.0, 0.30]
comp = [0.7, 0.1, 0.2, 0.0]
FLS = "Water" #
FLCOLD = "Methanol" # "Water" #
flm = cb.fprop.FluidModel(FLUID)
myFluid = cb.fprop.Fluid(flm, comp)
secFlm = cb.fprop.FluidModel(FLS)
secFluid = cb.fprop.Fluid(secFlm, [1.])
coldFlm = cb.fprop.FluidModel(FLCOLD)
coldFluid = cb.fprop.Fluid(coldFlm, [1.])
# Condenser(c) and storage (s), secondary fluids fix all, temperatures(T in K),
# pressures (p in Pa)
_ETA_S_ = 0.6 # interesting when changed from 0.69 to 0.65, the efficiency
# decreases, the reason is the low quality along throtteling then
T_MAX = 77 + 273.15 # 369.
T_MIN = 253.15
_STORAGE_T_IN_ = cb._T_SURROUNDING
_COLD_STORAGE_T_IN_ = _STORAGE_T_IN_
_STORAGE_T_OUT_ = T_MAX # 395.0
_COLD_STORAGE_T_OUT_ = T_MIN
_STORAGE_P_IN_ = 5e5 # pressure
_COLD_STORAGE_P_IN_ = 5e5
_Q_DOT_MIN_ = 1e3 # heat_flow rate to storage (W)
_D_T_SUPER_ = 3.8 # super heating of working fluid
_D_T_MIN_ = 2. # minimum approach temperature (pinch point)
_D_T_EVAP = 5.0
_D_T_COND = -7
# high T-storages
state_sec_out = secFluid.set_state([_STORAGE_T_OUT_, _STORAGE_P_IN_], "TP")
state_sec_in = secFluid.set_state([_STORAGE_T_IN_, _STORAGE_P_IN_], "TP")
# low T storages:
state_cold_out = coldFluid.set_state(
[_COLD_STORAGE_T_OUT_, _COLD_STORAGE_P_IN_], "TP")
state_cold_in = coldFluid.set_state(
[_COLD_STORAGE_T_IN_, _COLD_STORAGE_P_IN_], "TP")
# working fluid
T_DEW = _STORAGE_T_OUT_ +_D_T_COND# + _D_T_MIN_
state_in_cond = myFluid.set_state([T_DEW, 1.], "TQ") # find high pressure
state_out_cond = myFluid.set_state([_STORAGE_T_IN_ + _D_T_MIN_,
state_in_cond[1]], "TP")
state_satv_evap = myFluid.set_state(
[_STORAGE_T_IN_-_D_T_MIN_-_D_T_SUPER_-_D_T_EVAP, 1.], "TQ") # find minimum pressure
p_low = state_satv_evap[1]
T_IN = _STORAGE_T_IN_ - _D_T_MIN_
state_out_evap = myFluid.set_state([p_low,
T_IN], "PT")
FIXED_POINTS = {"eta_s": _ETA_S_,
"p_low": state_out_evap[1],
"p_high": state_in_cond[1],
"T_hh": _STORAGE_T_OUT_,
"h_h_out_sec": state_sec_out[2],
"h_h_out_w": state_out_cond[2],
"h_l_out_cold": state_cold_out[2],
"h_l_out_w": state_out_evap[2],
"T_hl": _STORAGE_T_IN_,
"T_lh": _STORAGE_T_IN_,
"T_ll": _COLD_STORAGE_T_OUT_, # 256.0,
"Q_dot_h": _Q_DOT_MIN_,
"d_temp_min": _D_T_MIN_}
print(
f"p-ratio: {state_in_cond[1]/state_out_evap[1]: .2f}, p_low: {state_out_evap[1]/1e5: .2} bar")
hp0 = cb.hp_simple.HeatPump([myFluid, secFluid, coldFluid], FIXED_POINTS)
print(hp0.evaluation)
cop = hp0.calc_heat_pump(verbose=True)
print(hp0.evaluation)
fig_ax_act = hp0.hp_plot()
print(hp0.evaluation, "\n----------------\n")
out = hp0.evaluation
print(f"Min and mean dT evaporator: {out['evaporator']['dT-min']}, {out['evaporator']['dT-mean']}")
print(f"Min and mean dT condenser: {out['condenser']['dT-min']}, {out['condenser']['dT-mean']}")
print(
f"COP: {cop},p-ratio: {out['p_high']/out['p_low']:.2f}, p_low {out['p_low']/1e5:.2f} bar")
print(
f'exergy loss rate: {out["exergy_loss_rate"]}, eff: {1-out["exergy_loss_rate"]/out["Power"]:.4f}')
#
my_dict = cb.hp_simple.read_hp_results(_RESULTS_ +
"\\last_T_H_dot_plot_hp_evaluation_dict.npy")
T_MAX = hp0.all_states[1][-1][0] # actual highest storage temperature
T_MIN = hp0.all_states[3][-1][0] # actual minimum storage temperature
# ----------------------ORC ----------------
# FLUID = "Propane * Butane * Pentane * Hexane"
# comp = [.75, 0.05, 0.15, 0.05]
# comp = [0.4, 0.3, 0.3, 0.0] # [0.164,.3330,.50300,0.0]
# FLS = "Water" # Storage fluid
# FLCOLD = "Methanol" # Storage fluid for low T
FLENV = "Water" #
flm = cb.fprop.FluidModel(FLUID)
myFluid = cb.fprop.Fluid(flm, comp)
secFlm = cb.fprop.FluidModel(FLS)
secFluid = cb.fprop.Fluid(secFlm, [1.])
coldFlm = cb.fprop.FluidModel(FLCOLD)
coldFluid = cb.fprop.Fluid(coldFlm, [1.])
envFlm = cb.fprop.FluidModel(FLENV)
envFluid = cb.fprop.Fluid(secFlm, [1.])
# Condenser(c) and storage (s), secondary fluids fix all, temperatures(T in K),
# pressures (p in Pa)
_ETA_S_ = 0.7 # interesting when changed from 0.69 to 0.65, the efficiency
# decreases, the reason is the low quality along throtteling then
_ETA_S_P_ = 0.6 # pump
_STORAGE_T_OUT_ = cb._T_SURROUNDING
_COLD_STORAGE_T_OUT_ = cb._T_SURROUNDING
_ENV_T_IN_ = cb._T_SURROUNDING
_ENV_T_OUT_ = cb._T_SURROUNDING + 5.
_STORAGE_T_IN_ = T_MAX # 395.0
_COLD_STORAGE_T_IN_ = T_MIN
_STORAGE_P_IN_ = 5e5
_COLD_STORAGE_P_IN_ = 5e5
_ENV_P_IN_ = 5e5
_Q_DOT_MIN_FACTOR = 1. # and heat_flow rate (W)
_D_T_SUPER_ = 5 # super heating of working fluid
_D_T_MIN_ = 2. # minimum approach temperature (pinch point)
_COP_CHARGING = 2.925 # needed to calculate Q_env_discharging
_T_REDUCTION_EVAP = -15 # if the curves cross in the evaporator this parameter may help
_T_INCREASE_COND = 17.5
# environment for heat transfer
state_env_out = envFluid.set_state([_ENV_T_OUT_, _ENV_P_IN_], "TP")
state_env_in = envFluid.set_state([_ENV_T_IN_, _ENV_P_IN_], "TP")
# high T-storages
state_sec_out = secFluid.set_state([_STORAGE_T_OUT_, _STORAGE_P_IN_], "TP")
state_sec_in = secFluid.set_state([_STORAGE_T_IN_, _STORAGE_P_IN_], "TP")
# low T sorages:
state_cold_out = coldFluid.set_state(
[_COLD_STORAGE_T_OUT_, _COLD_STORAGE_P_IN_], "TP")
state_cold_in = coldFluid.set_state(
[_COLD_STORAGE_T_IN_, _COLD_STORAGE_P_IN_], "TP")
# working fluid
state_satv_evap = myFluid.set_state(
[_STORAGE_T_IN_-_D_T_MIN_-_D_T_SUPER_+_T_REDUCTION_EVAP, 1.], "TQ") # find high pressure
p_high = state_satv_evap[1]
T_OUT = _STORAGE_T_IN_ - _D_T_MIN_
# Evaporator input comes from the pump-output
state_out_evap = myFluid.set_state([p_high,
T_OUT], "PT")
# low pressure, condenser # BA 2023-11-14 three points needed: low, environment and slightly higher
T_SATL = _COLD_STORAGE_T_IN_ + _D_T_MIN_ + \
_T_INCREASE_COND # BA 2024-05-21 be careful
state_out_cond = myFluid.set_state([T_SATL, 0.], "TQ") # find low pressure
p_low = state_out_cond[1]
# BA changed 2023-12-13 the fixed starting point for the cycle is the fluid
# state before the pump now.
# the other states in the condenser are fixed by the expander outlet and
# the Q_total : Q_low_stored ratio eventually p_low must be varied until
# the balance is fulfilled, since m_dot_w is fixed by the evaporator!
FIXED_POINTS_ORC = {"eta_s": _ETA_S_, # expander
"eta_s_p": _ETA_S_P_, # pump
"p_low": p_low,
"p_high": p_high,
"T_hh": _STORAGE_T_IN_,
"h_h_out_sec": state_sec_out[2],
"h_h_out_w": state_out_evap[2],
"h_l_out_cold": state_cold_out[2],
"h_l_out_w": state_out_cond[2],
"h_env_in": state_env_in[2],
"h_env_out": state_env_out[2],
"T_hl": _STORAGE_T_OUT_,
"T_lh": _COLD_STORAGE_T_OUT_,
"T_ll": _COLD_STORAGE_T_IN_, # 256.0,
"Q_dot_h": _Q_DOT_MIN_ * _Q_DOT_MIN_FACTOR,
"d_temp_min": _D_T_MIN_,
"cop_charging": cop # needed to calculate Q_env_discharging
}
orc0 = cb.orc_simple.OrganicRankineCycle(
[myFluid, secFluid, envFluid, coldFluid], FIXED_POINTS_ORC)
eta_dis = orc0.calc_orc()
print(f"eta(ORC): {eta_dis:.3f}, COP(HP): {cop:.3f}")
orc0.hp_plot(fig_ax=fig_ax_act)
print(f"RTE: {cop*eta_dis:.3f}")
print(f"warnings: HP {hp0.warning}; ORC {orc0.warning}")