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Added Minimum Thermal Power for arrays
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and fixed a bug: where the arrays would not be simulated
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@xihaui
xihaui committed Mar 31, 2022
1 parent a97e644 commit 6e5d3ef
Showing 1 changed file with 163 additions and 151 deletions.
314 changes: 163 additions & 151 deletions hplib/hplib.py
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Original file line number Diff line number Diff line change
Expand Up @@ -255,8 +255,7 @@ def fit_func_p_th_ref(p_th: int, t_in: int, t_out: int, group_id: int, p_th_set
return p_th_diff


def simulate(t_in_primary: any, t_in_secondary: any, parameters: pd.DataFrame,
t_amb: any, mode: int = 1) -> pd.DataFrame:
def simulate(t_in_primary: Union[float,np.ndarray], t_in_secondary: Union[float,np.ndarray], parameters, t_amb: Union[float,np.ndarray], mode: int = 1, p_th_min: Union[float,np.ndarray] = 0) -> dict:
"""
Performs the simulation of the heat pump model.
Expand All @@ -272,6 +271,7 @@ def simulate(t_in_primary: any, t_in_secondary: any, parameters: pd.DataFrame,
Ambient temperature :math:'T' of the air. [°C]
mode : int
for heating: 1, for cooling: 2
P_th_min : Minimum thermal power output [W]. Inverter heat pumps increase electrical Power input. At maximum electrical input a electrical heating rod turns on.
Returns
-------
Expand All @@ -284,13 +284,11 @@ def simulate(t_in_primary: any, t_in_secondary: any, parameters: pd.DataFrame,
EER = Energy Efficiency Ratio.
P_el = Electrical input Power. [W]
P_th = Thermal output power. [W]
m_dot = Mass flow at secondary side of the heat pump. [kg/s]
m_dot = Mass flow at secondary side of the heat pump. [kg/s]
"""

DELTA_T = 5 # Inlet temperature is supposed to be heated up by 5 K
CP = 4200 # J/(kg*K), specific heat capacity of water
t_in = t_in_primary#info value for dataframe
T_amb = t_amb #info value for dataframe
delta_t = 5 # Inlet temperature is supposed to be heated up by 5 K
cp = 4200 # J/(kg*K), specific heat capacity of water
group_id = parameters['Group'].array[0]
p1_p_el_h = parameters['p1_P_el_h [1/°C]'].array[0]
p2_p_el_h = parameters['p2_P_el_h [1/°C]'].array[0]
Expand Down Expand Up @@ -322,140 +320,144 @@ def simulate(t_in_primary: any, t_in_secondary: any, parameters: pd.DataFrame,
p3_p_el_c = np.nan
p4_p_el_c = np.nan
p_el_col_ref=np.nan

if mode==2 and group_id > 1:
raise ValueError('Cooling is only possible with heat pumps of group id = 1.')

t_in = t_in_primary # info value for dataframe
if mode==1:
t_out = t_in_secondary + delta_t #Inlet temperature is supposed to be heated up by 5 K
eer=0
if mode==2: # Inlet temperature is supposed to be cooled down by 5 K
t_out = t_in_secondary - delta_t
cop=0
# for subtype = air/water heat pump
if group_id == 1 or group_id == 4:
if group_id in (1, 4):
t_amb = t_in
else:
pass
if(type(t_in)==pd.core.series.Series or type(t_in_secondary)==pd.core.series.Series or type(t_amb)==pd.core.series.Series):# for handling pandas.Series
try:
df=t_in.to_frame()
df.rename(columns = {t_in.name:'T_in'}, inplace = True)
df['mode']=mode
df.loc[df['mode']==1,'T_out']=t_in_secondary + DELTA_T
df.loc[df['mode']==2,'T_out']=t_in_secondary - DELTA_T
df['T_amb']=t_amb

except:
try:
df=t_in_secondary.to_frame()
df.rename(columns = {t_in_secondary.name:'T_out'}, inplace = True)
df['mode']=mode
df.loc[df['mode']==1,'T_out']=df['T_out']+ DELTA_T
df.loc[df['mode']==2,'T_out']=df['T_out'] - DELTA_T
df['T_in']=t_in
df['T_amb']=t_amb
except:
df=t_amb.to_frame()
df.rename(columns = {t_amb.name:'T_amb'}, inplace = True)
df['T_in']=t_in
df['mode']=mode
df.loc[df['mode']==1,'T_out']=t_in_secondary + DELTA_T
df.loc[df['mode']==2,'T_out']=t_in_secondary - DELTA_T
if group_id == 1 or group_id == 2 or group_id == 3:
df.loc[df['mode']==1,'COP'] = p1_cop * t_in + p2_cop * df['T_out'] + p3_cop + p4_cop * t_amb
df.loc[df['mode']==1,'P_el'] = (p1_p_el_h * t_in + p2_p_el_h * df['T_out'] + p3_p_el_h + p4_p_el_h * t_amb) * p_el_ref #this is the first calculated value for P_el
if group_id == 1:#with regulated heatpumps the electrical power can get too low. We defined a minimum value at 25% from the point at -7/output temperature.
df.loc[df['mode']==2,'EER'] = (p1_eer * t_in + p2_eer * df['T_out'] + p3_eer + p4_eer * t_amb)
df.loc[df['mode']==2,'P_el'] = (p1_p_el_c * t_in + p2_p_el_c * df['T_out'] + p3_p_el_c + p4_p_el_c * t_amb) * p_el_col_ref
df.loc[(df['mode']==2) & (df['T_in'] < 25),'P_el'] = p_el_col_ref * (p1_p_el_c * 25 + p2_p_el_c * df['T_out'] + p3_p_el_c + p4_p_el_c * 25)
df.loc[(df['mode']==2) & (df['EER']<1),'P_th'] = np.nan
df.loc[(df['mode']==2) & (df['EER']<1),'EER'] = np.nan
df.loc[df['mode']==2,'P_th'] = -(df['P_el'] * df['EER'])
df.loc[(df['mode']==2) & (df['P_el']<0),'EER'] = np.nan
df.loc[(df['mode']==2) & (df['P_el']<0),'P_th'] = np.nan
df.loc[(df['mode']==2) & (df['P_el']<0),'P_el'] = np.nan
#df.loc[df['mode']==2,'P_el'] = df['P_th'] / df['COP']
df.loc[df['mode']==1,'t_in'] = -7
df.loc[df['mode']==1,'t_amb'] = -7
if group_id == 2:
df['t_in']=df['T_in']
df.loc[:,'t_amb'] = -7
df.loc[(df['mode']==1) & (df['P_el'] < 0.25 * p_el_ref * (p1_p_el_h * df['t_in'] + p2_p_el_h * df['T_out'] + p3_p_el_h + p4_p_el_h * df['t_amb'])),'P_el'] = 0.25 * p_el_ref * (p1_p_el_h * df['t_in'] + p2_p_el_h * df['T_out'] + p3_p_el_h + p4_p_el_h * df['t_amb'])
df.loc[(df['mode']==1) ,'P_th'] = (df['P_el'] * df['COP'])
df.loc[(df['mode']==1) & (df['COP'] < 1),'P_el']=p_th_ref#if COP is too low the electeric heating element is used in simulation
df.loc[(df['mode']==1) & (df['COP'] < 1),'P_th']=p_th_ref
df.loc[(df['mode']==1) & (df['COP'] < 1),'COP']=1
df['m_dot']=df['P_th']/(DELTA_T * CP)
del df['t_in']
del df['t_amb']
elif group_id == 4 or group_id == 5 or group_id == 6:
df['COP'] = p1_cop * t_in + p2_cop * df['T_out'] + p3_cop + p4_cop * t_amb
df['P_el'] = (p1_p_el_h * t_in + p2_p_el_h * df['T_out'] + p3_p_el_h + p4_p_el_h * t_amb) * p_el_ref
df['P_th'] = df['P_el'] * df['COP']
df.loc[df['COP'] < 1,'P_el']=p_th_ref
df.loc[df['COP'] < 1,'P_th']=p_th_ref#if COP is too low the electeric heating element is used in simulation
df.loc[df['COP'] < 1,'COP']=1
df['m_dot']=df['P_th']/(DELTA_T * CP)
df['P_el']=df['P_el'].round(0)
df['COP']=df['COP'].round(2)
df['m_dot']=df['m_dot'].round(3)
df['m_dot']=df['m_dot'].abs()
else:
t_ambient=t_amb
# for regulated heat pumps
if group_id in (1, 2, 3):
if mode==1:
t_out = t_in_secondary + DELTA_T #Inlet temperature is supposed to be heated up by 5 K
EER=0
if mode==2: # Inlet temperature is supposed to be cooled down by 5 K
t_out = t_in_secondary - DELTA_T
COP=0
# for regulated heat pumps
if group_id == 1 or group_id == 2 or group_id == 3:
if mode==1:
COP = p1_cop * t_in + p2_cop * t_out + p3_cop + p4_cop * t_amb
P_el = (p1_p_el_h * t_in + p2_p_el_h * t_out + p3_p_el_h + p4_p_el_h * t_amb) * p_el_ref
if group_id == 1:
cop = p1_cop * t_in + p2_cop * t_out + p3_cop + p4_cop * t_amb
p_el=p_el_ref * (p1_p_el_h * t_in
+ p2_p_el_h * t_out
+ p3_p_el_h
+ p4_p_el_h * t_amb)
if group_id == 1:
if isinstance(t_in, np.ndarray):
t_in = np.full_like(t_in, -7)
else:
t_in = -7
t_amb = t_in
if group_id == 2:
t_amb = t_in

elif group_id == 2:
if isinstance(t_amb, np.ndarray):
t_amb = np.full_like(t_amb, -7)
else:
t_amb = -7
p_el_25 = 0.25 * p_el_ref * (p1_p_el_h * t_in
+ p2_p_el_h * t_out
+ p3_p_el_h
+ p4_p_el_h * t_amb)
if isinstance(p_el, np.ndarray):
p_el = np.where(p_el < p_el_25, p_el_25, p_el)
elif p_el < p_el_25:
p_el = p_el_25

p_th = p_el * cop

if isinstance(cop, np.ndarray):
# turn on heating rod and compressor
p_el=np.where((cop>1) & (p_th < p_th_min) & (p_el_ref < p_th_min/cop), p_el_ref + p_th_ref, p_el)
p_th=np.where((cop>1) & (p_th < p_th_min) & (p_el_ref < p_th_min/cop), p_el_ref * cop + p_th_ref, p_th)
# increase electrical power for compressor
p_el=np.where((cop>1) & (p_th < p_th_min) & (p_el_ref > p_th_min/cop), p_th_min/cop, p_el)
p_th=np.where((cop>1) & (p_th < p_th_min) & (p_el_ref > p_th_min/cop), p_th_min, p_th)
# only turn on heating rod
p_el = np.where(cop <= 1, p_th_ref, p_el)
p_th = np.where(cop <= 1, p_th_ref, p_th)
cop = p_th/p_el
else:
if cop <= 1:
cop = 1
p_el = p_th_ref
p_th = p_th_ref
elif p_th < p_th_min:
if p_el_ref > p_th_min/cop:
p_el = p_th_min/cop
p_th = p_th_min
else:
p_el = p_el_ref + p_th_ref
p_th = p_el_ref*cop + p_th_ref
cop = p_th/p_el

if P_el < 0.25 * p_el_ref * (
p1_p_el_h * t_in + p2_p_el_h * t_out + p3_p_el_h + p4_p_el_h * t_amb): # 25% of Pel @ -7°C T_amb = T_in
P_el = 0.25 * p_el_ref * (p1_p_el_h * t_in + p2_p_el_h * t_out + p3_p_el_h + p4_p_el_h * t_amb)
P_th = P_el * COP
if COP <= 1:
COP = 1
P_el = p_th_ref
P_th = p_th_ref
elif mode==2:
EER = (p1_eer * t_in + p2_eer * t_out + p3_eer + p4_eer * t_amb)

if t_in<25:
t_in=25
t_amb=t_in
P_el = (p1_p_el_c * t_in + p2_p_el_c * t_out + p3_p_el_c + p4_p_el_c * t_amb) * p_el_col_ref
if P_el<0:
EER = 0
P_el = 0
P_th = -(EER*P_el)
if EER < 1:
EER = 0
P_el = 0
P_th = 0
if mode==2:
eer = (p1_eer * t_in + p2_eer * t_out + p3_eer + p4_eer * t_amb)
if isinstance(t_in, np.ndarray):
t_in=np.where(t_in<25,25,t_in)
elif t_in<25:
t_in=25
t_amb=t_in
p_el = (p1_p_el_c * t_in + p2_p_el_c * t_out + p3_p_el_c + p4_p_el_c * t_amb) * p_el_col_ref
if isinstance(p_el,np.ndarray):
eer = np.where(p_el<0,0,eer)
p_el = np.where(p_el<0,0,p_el)
elif p_el<0:
eer = 0
p_el = 0
p_th = -(eer*p_el)
if isinstance(eer,np.ndarray):
p_el = np.where(eer <= 1, 0 , p_el)
p_th = np.where(eer <= 1, 0 , p_th)
eer = np.where(eer <= 1, 0, eer)
elif eer < 1:
eer = 0
p_el = 0
p_th = 0

# for subtype = On-Off
elif group_id in (4, 5, 6):
p_el = (p1_p_el_h * t_in
+ p2_p_el_h * t_out
+ p3_p_el_h
+ p4_p_el_h * t_amb) * p_el_ref

cop = p1_cop * t_in + p2_cop * t_out + p3_cop + p4_cop * t_amb

p_th = p_el * cop

if isinstance(cop, np.ndarray):
p_el=np.where((cop>1) & (p_th < p_th_min) , p_el + p_th_ref, p_el)
p_th=np.where((cop>1) & (p_th < p_th_min) , p_th + p_th_ref, p_th)
p_el = np.where(cop <= 1, p_th_ref, p_el)
p_th = np.where(cop <= 1, p_th_ref, p_th)
cop = p_th / p_el

# for subtype = On-Off
elif group_id == 4 or group_id == 5 or group_id == 6:
P_el = (p1_p_el_h * t_in + p2_p_el_h * t_out + p3_p_el_h + p4_p_el_h * t_amb) * p_el_ref
COP = p1_cop * t_in + p2_cop * t_out + p3_cop + p4_cop * t_amb
P_th = P_el * COP
if COP <= 1:
COP = 1
P_el = p_th_ref
P_th = p_th_ref
# massflow
m_dot = P_th / (DELTA_T * CP)
#round
df=pd.DataFrame()

df['T_in']=[t_in_primary]
df['T_out']=[t_out]
df['T_amb']=[T_amb]
df['COP']=[COP]
df['EER']=[EER]
df['P_el']=[P_el]
df['P_th']=[P_th]
df['m_dot']=[abs(m_dot)]
return df
else:
if cop <= 1:
cop = 1
p_el = p_th_ref
p_th = p_th_ref
elif p_th < p_th_min:
p_th=p_th+p_th_ref
p_el=p_el+p_th_ref
cop=p_th/p_el

# massflow
m_dot = abs(p_th / (delta_t * cp))

# round
result = pd.DataFrame()

result['T_in'] = [t_in_primary]
result['T_out'] = [t_out]
result['T_amb'] = [t_ambient]
result['COP'] = [cop]
result['EER'] = [eer]
result['P_el'] = [p_el]
result['P_th'] = [p_th]
result['m_dot']= [m_dot]
return result

def same_built_type(modelname):
"""
Expand Down Expand Up @@ -514,7 +516,7 @@ def __init__(self, parameters: pd.DataFrame):
self.delta_t = 5 # Inlet temperature is supposed to be heated up by 5 K
self.cp = 4200 # J/(kg*K), specific heat capacity of water

def simulate(self, t_in_primary: float, t_in_secondary: float, t_amb: float, mode: int = 1, p_th_min: float = 0) -> dict:
def simulate(self, t_in_primary: Union[float,np.ndarray], t_in_secondary: Union[float,np.ndarray], t_amb: Union[float,np.ndarray], mode: int = 1, p_th_min: Union[float,np.ndarray] = 0) -> dict:
"""
Performs the simulation of the heat pump model.
Expand Down Expand Up @@ -590,23 +592,32 @@ def simulate(self, t_in_primary: float, t_in_secondary: float, t_amb: float, mod
p_el = p_el_25

p_th = p_el * cop

if isinstance(cop, np.ndarray):
# turn on heating rod and compressor
p_el=np.where((cop>1) & (p_th < p_th_min) & (self.p_el_ref < p_th_min/cop), self.p_el_ref + self.p_th_ref, p_el)
p_th=np.where((cop>1) & (p_th < p_th_min) & (self.p_el_ref < p_th_min/cop), self.p_el_ref * cop + self.p_th_ref, p_th)
# increase electrical power for compressor
p_el=np.where((cop>1) & (p_th < p_th_min) & (self.p_el_ref > p_th_min/cop), p_th_min/cop, p_el)
p_th=np.where((cop>1) & (p_th < p_th_min) & (self.p_el_ref > p_th_min/cop), p_th_min, p_th)
# only turn on heating rod
p_el = np.where(cop <= 1, self.p_th_ref, p_el)
p_th = np.where(cop <= 1, self.p_th_ref, p_th)
cop = np.where(cop <= 1, 1, cop)
elif p_th < p_th_min:
if cop>1:
cop = p_th/p_el
else:
if cop <= 1:
cop = 1
p_el = self.p_th_ref
p_th = self.p_th_ref
elif p_th < p_th_min:
if self.p_el_ref > p_th_min/cop:
p_el = p_th_min/cop
p_th = p_th_min
else:
p_el = self.p_el_ref + self.p_th_ref
p_th = self.p_el_ref*cop + self.p_th_ref
cop = p_th/p_el
if cop <= 1:
cop = 1
p_el = self.p_th_ref
p_th = self.p_th_ref

if mode==2:
eer = (self.p1_eer * t_in + self.p2_eer * t_out + self.p3_eer + self.p4_eer * t_amb)
if isinstance(t_in, np.ndarray):
Expand Down Expand Up @@ -643,20 +654,21 @@ def simulate(self, t_in_primary: float, t_in_secondary: float, t_amb: float, mod
p_th = p_el * cop

if isinstance(cop, np.ndarray):
p_el=np.where((cop>1) & (p_th < p_th_min) , p_el + self.p_th_ref, p_el)
p_th=np.where((cop>1) & (p_th < p_th_min) , p_th + self.p_th_ref, p_th)
p_el = np.where(cop <= 1, self.p_th_ref, p_el)
p_th = np.where(cop <= 1, self.p_th_ref, p_th)
cop = np.where(cop <= 1, 1, cop)
elif p_th < p_th_min:
if cop>1:
cop = p_th / p_el

else:
if cop <= 1:
cop = 1
p_el = self.p_th_ref
p_th = self.p_th_ref
elif p_th < p_th_min:
p_th=p_th+self.p_th_ref
p_el=p_el+self.p_th_ref
cop=p_th/p_el
if cop <= 1:
cop = 1
p_el = self.p_th_ref
p_th = self.p_th_ref



# massflow
m_dot = abs(p_th / (self.delta_t * self.cp))
Expand Down

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