• 1. Thermodynamic Cycles Package

  • 1.1. Fluid Source
    • 1.1.1. Input parameters
  • 1.2. Sink
  • 1.3. Compressor
    • 1.3.1. Compressor model
  • [1.4. Water Heat Storage] (#14-water-heat-storage)
    • 1.4.1. Mixed Tank

• 2. AHU modules

  • 2.1 Fresh AHU Example

• 3. Chiller Example

  • 3.1. Launch Chiller Application (Tkinter GUI)
  • 3.2. Create Oriented-Object Chiller

• 4. Données météo

  • 4.1. OpenWeaterMap
  • 4.2. MeteoCiel

1. Thermodynamic Cycles Package

1.1. Fluid Source

1.1.1. Input parameters

from ThermodynamicCycles.Source import Source

#Create Compressor Object
SOURCE=Source.Object()

#Data Input
SOURCE.Pi_bar=1.01325
SOURCE.fluid="air"
SOURCE.F_kgs=1
#SOURCE.F_Sm3s=2937.482966/3600 #SOURCE.F_m3s=2480.143675/3600
#SOURCE.F_Sm3h=1 #SOURCE.F_m3h=2480.143675 #SOURCE.F_kgh=3600

#Calculate Object
SOURCE.calculate()

#Data output
print(SOURCE.df)

1.2. Sink

1.2.1. Test Sink

from ThermodynamicCycles.Sink import Sink
#from ThermodynamicCycles.Connect import Fluid_connect

#Create Sink object
SINK=Sink.Object()

#Fluid_connect(SINK.Inlet,SOURCE.Outlet) 
SINK.Inlet.fluid="air"
SINK.Inlet.F_kgs=0.334
SINK.Inlet.P=101325
SINK.Inlet.h=420000

#calculate SINK
SINK.calculate()

#Print result

print(SINK.df)
print(SINK.To_degC)

Output data

1.3. Compressor

1.3.1. Compressor model

from ThermodynamicCycles.Source import Source
from ThermodynamicCycles.Compressor import Compressor
from ThermodynamicCycles.Sink import Sink
from ThermodynamicCycles.Connect import Fluid_connect

#Create Compressor Object with Source and fluid Sink
SOURCE=Source.Object()
COMP=Compressor.Object()
SINK=Sink.Object()

#Data Input
SOURCE.Ti_degC=20
SOURCE.fluid="air"
SOURCE.Pi_bar=1
SOURCE.F_Sm3h=500 # is not considered if  COMP.Qcomp is not None

COMP.eta_is=0.80
COMP.Tdischarge_target=80 # (discharge temperature in degC, after cooler)
COMP.HP=7.5*100000 # discharge pressure in Pa
COMP.Qcomp=48745.761 # if Energy Power is given (W) the Mass flow rate is recalculated


#Calculate and Connect Objects
SOURCE.calculate()
Fluid_connect(COMP.Inlet,SOURCE.Outlet)
COMP.calculate()
Fluid_connect(SINK.Inlet,COMP.Outlet)
SINK.calculate()

#Data output (print DataFrame)
print(SOURCE.df)
print(COMP.df)
print(SINK.df)

1.4. Water Heat Storage

1.4.1. Mixed Tank

from ThermodynamicCycles import MixedStorage
from ThermodynamicCycles.Source import Source
from ThermodynamicCycles.Sink import Sink
from ThermodynamicCycles.Connect import Fluid_connect


#lecture d'un fichier excel
#pip install pandas
import pandas as pd
import os
data=pd.read_excel( os.path.join(os.path.dirname(__file__), 'HotWaterStorage.xlsx'))
data['Timestamp'] = pd.to_datetime(data['Timestamp'], unit="%d/%m/%y %H:%M:%S")
rows = data.shape[0]
print(rows)
print(data.columns)

#initialiser les table de sortie
df_result=pd.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False)
df_source=pd.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False)
df_str=pd.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False)
df_sink=pd.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False)

#CreateTank Object with Source and fluid Sink
SOURCE=Source.Object()
SINK=Sink.Object()
STR=MixedStorage.Object()

#paramètres
STR.V=4
STR.Tinit_degC=40
STR.t=1*3600 #in seconde

for r in range(1, rows):
#Data Input
    SOURCE.Ti_degC=data["TdegC"][r] 
    SOURCE.fluid="water"
    SOURCE.Pi_bar=1
    SOURCE.F_m3h=data["F_m3h"][r] 

    SOURCE.Timestamp=data["Timestamp"][r]
    STR.Timestamp=data["Timestamp"][r]
    SINK.Timestamp=data["Timestamp"][r]

    #calcul du pas de temps
    Timestamp=data["Timestamp"][r] 
    dt=(data["Timestamp"][r]-data["Timestamp"][r-1]).total_seconds()
    #print(dt)
    STR.t=dt

    SOURCE.calculate()
    Fluid_connect(STR.Inlet,SOURCE.Outlet)
    STR.calculate()
    Fluid_connect(SINK.Inlet,STR.Outlet)
    SINK.calculate()

    df_str=df_str.append(STR.df.T)
    df_source=df_source.append(SOURCE.df.T)
    df_sink=df_sink.append(SINK.df.T)
  
# Add new column to the DataFrame
df_result=df_str.merge(df_sink, on=['Timestamp']).merge(df_source, on=['Timestamp'])
print(df_result)

with pd.ExcelWriter('output_WaterStorage.xlsx') as writer:                #Création d'un fichier de sortie + Ecriture
    df_result.to_excel(writer, sheet_name='Feuille output',index=False)
    data.to_excel(writer, sheet_name='Feuille input',index=False)

####PLOT#####

# Import Library

import matplotlib.pyplot as plt
df_result.index=df_result['Timestamp']

# to set the plot size
plt.figure(figsize=(16, 8), dpi=100)

# Plot
df_result["str_Ti_degC"].plot(marker="o",label='Tentrèe (°C)', color='orange')
df_result["str_T_degC"].plot(marker="o",label='Tsortie (°C)')
df_result["cumul_Qstr_kWh"].plot(marker="o",label='Energie stockée cumulée (kWh)')
df_result["Qstr_kW"].plot(marker="o",label='Puissance de stockage (kW)')

# Labelling 

plt.xlabel("Date")
plt.ylabel("kWh, kW et °C")
plt.legend()
plt.grid()
plt.title("Stockage d'énergie thermique")

# Display

plt.show()

2. AHU modules

2.1 Fresh AHU Example

# =============================================================================
# AHU Model (Fresh air + Heating Coil + humidifier)
# =============================================================================

#module de calcul des prop d'air humide
from AHU import FreshAir
#Heating Coil Component
from AHU import HeatingCoil
#composant Humidifier (vapeur ou adiabatique)
from AHU.Humidification import Humidifier
# connexion entre les composants
from AHU.Connect import Air_connect

##########Création des Objects
AN=FreshAir.Object()
BC=HeatingCoil.Object()
HMD=Humidifier.Object()

    
#Récupération des données entrées par l'utilisateur
        #AN
AN.m_vol=3000 #m3/h
#print("AN.m_vol = ",AN.m_vol)
AN.T=14 #°C
AN.HR_FreshAir=71 # %
    #BC
BC.T_out_target=15 #°C
    #Humidifier
HMD.HA_out_target=8 #g/Kg dry air

    #calculate les propriétés d'air neuf; !important
AN.calculate()

Air_connect(BC.Inlet,AN.Outlet)
BC.calculate()
    

Air_connect(HMD.Inlet,BC.Outlet)
    
HMD.HumidType="vapeur" #par default : Humdificateur adiabatique
HMD.calculate()


#enregistrer les résultats du module d'air neuf

#Absolute Humidity  g/kg_as

print("Fresh Air Absolute Humidity  g/kg_as",round(AN.HA,1))
# print("HA_FreshAir[r-1] = ",HA_FreshAir[r-1])
#Sat Vapor Pressure  " Pa"

print("Fresh Air Sat Vapor Pressure   Pa",round(AN.Pvsat,0))
#Wet-Bulb Temperature  °C

print("Fresh Air Wet-Bulb Temperature  °C",round(AN.T_hum,1))
#Specific Enthalpy  KJ/Kg_as

print("Fresh Air Specific Enthalpy  KJ/Kg_as",round(AN.h,3))

#enregistrer les résultats de la Coil de préchauffage

# Specific Enthalpy KJ/Kg_as
print("Heating Coil Specific Enthalpy KJ/Kg_as",round(BC.h_out,1))
# Thermal Power  kW"
print("Heating Coil Thermal Power  kW",round(BC.Qth,1))
# Relative Humidity %"
print("Heating Coil Relative Humidity %",round(BC.HR_out,1))
    
print("Humidifier Steam mass flow rate Kg/s",round(HMD.m_water,3))  
print("Humidifier Dry air mass flow rate Kg/s",round(HMD.m_as,3)) 

# =============================================================================
# End AHU Model
# =============================================================================

3. Chiller Example

3.1. Launch Chiller Application (Tkinter GUI)

from TkinterGUI import Chiller

3.2. Create Oriented-Object Chiller

# =============================================================================
# Chiller Model (Evaporator + Compressor + Desuperheater + Condenser + Expansion_Valve)
# =============================================================================

# #ThermodynamicCycles
import CoolProp.CoolProp as CP
from ThermodynamicCycles.Evaporator import Evaporator
from ThermodynamicCycles.Compressor import Compressor
from ThermodynamicCycles.Desuperheater import Desuperheater
from ThermodynamicCycles.Expansion_Valve import Expansion_Valve
from ThermodynamicCycles.Condenser import Condenser
from ThermodynamicCycles.Connect import Fluid_connect

###############Create chiller component object ##################
EVAP=Evaporator.Object()
COMP=Compressor.Object()
DESURCH=Desuperheater.Object()
COND=Condenser.Object()
DET=Expansion_Valve.Object()
###############################################################

########################Cycle Inlet Parameters########################
#***************Evaporator parameters*******
fluid="R134a"
EVAP.fluid=fluid
EVAP.Inlet.F_kgs=1 #Kg/s
# T or P evap :
EVAP.LP_bar=2.930154 #bar
#EVAP.Ti_degC=0 #Tevap 
EVAP.surchauff=2 #superheating
EVAP.Inlet.h= CP.PropsSI('H','P',1*1e5,'T',40+273.15,fluid)   #initialisation pour le calcul en boucle
#******************compresseur parameters***********

# give HP or Tcond
#COMP.HP=1e5*10 #Pa
COMP.Tcond_degC=40
COMP.eta_is=0.8 # isentropic efficiency
COMP.Tdischarge_target=80 #°C compressor outlet temperature, neglected if compressor is not cooled
COMP.Qcomp==100000 #in (W) If this value is given, the mass flow rate is calculated /Write None if not used  #in (W) If this value is given, the mass flow rate is calculated
#*************** Condenser parameters**************
COND.subcooling=2 #°C subcooling


#calculation algorithme
EVAP.calculate() # evaporator initialisation
Fluid_connect(COMP.Inlet,EVAP.Outlet)
COMP.calculate()
Fluid_connect(DESURCH.Inlet,COMP.Outlet)
DESURCH.calculate()
Fluid_connect(COND.Inlet, DESURCH.Outlet)
COND.calculate()
Fluid_connect(DET.Inlet,COND.Outlet)
Fluid_connect(DET.Outlet,EVAP.Inlet)
DET.calculate()
Fluid_connect(EVAP.Inlet,DET.Outlet)
EVAP.calculate() # recalculate evaporator

# Cycle performance
EER=EVAP.Qevap/COMP.Qcomp
print("EER="+str(round(EER,1))+" ")
QcondTot=COND.Qcond+DESURCH.Qdesurch
print("QcondTot="+str(round(QcondTot/1000,1))+" kW")
COP=QcondTot/COMP.Qcomp
print("COP="+str(round(COP,1))+" ")

# ####### Print Results#######################"
print(COMP.df)
print(EVAP.df)
print(DESURCH.df)
print(COND.df)
print(DET.df)

# =============================================================================
# End Chiller Model
# =============================================================================

3. Pinch Analysis

from PinchAnalysis.PinchCalculation import PinchCalculation
import pandas as pd
import matplotlib.pyplot as plt

#DataFrame Input Data
df=pd.DataFrame({'id': [1, 2, 3, 4],
                   'name': ['stream1', 'stream2', 'stream3', 'stream4'],
                   'Ti': [200, 50, 125, 45],
                 'To': [50, 250, 124, 195],
                 'mCp': [3, 2,300,4],
                 'dTmin2': [5, 5, 10, 10],
                 'integration': [True, True, True, True]
                 })


#Pinch Calculation
T, plot_GCC, plot_ccf,plot_ccc,utilite_froide,utilite_chaude=PinchCalculation(df)

#Print the results
print("T",T)
print("GCC",plot_GCC[:,0])
print("ccf",plot_ccf[:,0])
print("ccc",plot_ccc[:,0])
print("utilite_froide",utilite_froide)
print("uilite_chaude",utilite_chaude)


# Plot the results

fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.plot(plot_ccf[:,0],T, color='tab:blue')
ax1.plot(plot_ccc[:,0],T, color='tab:red')
ax2.plot(plot_GCC[:,0],T, color='tab:orange')
ax1.set(xlabel='kW', ylabel='Temperature (°C)')
ax2.set(xlabel='kW')
ax1.grid(True)
ax2.grid(True)
plt.show()

4 Données-météo

4.1 OpenWeaterMap

Pour lire la température et l'humidité en fonction d'une position GPS à partir des données de OpenWeaterMap

from OpenWeatherMap import OpenWeatherMap_call_location

df=OpenWeatherMap_call_location.API_call_location("48.862725","2.287592")

print(df)

<Response [200]> Timestamp T(°C) HR(%) 0 2023-03-09 14:09:01.941527 14.39 72

4.2 MeteoCiel

Scraper les données historique d'une station Meteociel

from datetime import datetime
#pip install energysystemmodels
from MeteoCiel.MeteoCiel_Scraping import MeteoCiel_histoScraping

# 0. Données d'entrée#
code2=7471 #station météo
date_debut=datetime(2023,1,1)
date_fin=datetime.now()

print("date_debut:",date_debut)
print("date_fin:",date_fin)

# 1. Utiliser la fonction de scraping
df_histo=MeteoCiel_histoScraping(code2,date_debut,date_fin)

# 2. Entregistrer sous forme d'un fichier Excel
df_histo.to_excel("Meteociel.fr_station_"+str(date_debut.date())+"_to_"+str(date_fin.date())+".xlsx")