def main():
house_param = load_config("config2R2C.yml")
days_sim = house_param['timing']['days_sim']
CF = house_param['ventilation']['CF']
Rair_wall, Cwall, Rair_outdoor, Cair = calculateRCOne(house_param)
print(days_sim)
df_nen = nen5060_to_dataframe()
df_irr = run_qsun(df_nen)
print(df_irr.head())
time_sim = df_irr.iloc[0:days_sim * 24, 0].values
Qsolar = (df_irr.total_E * house_param['glass']['E'] +
df_irr.total_SE * house_param['glass']['SE'] +
df_irr.total_S * house_param['glass']['S'] +
df_irr.total_SW * house_param['glass']['SW'] +
df_irr.total_W * house_param['glass']['W'] +
df_irr.total_NW * house_param['glass']['NW'] +
df_irr.total_N * house_param['glass']['N'] +
df_irr.total_NE * house_param['glass']['NE']).values
Qsolar *= house_param['glass']['g_value']
Qsolar_sim = Qsolar[0:days_sim * 24]
Qint = internal_heat_gain(house_param['internal']['Q_day'],
house_param['internal']['delta_Q'],
house_param['internal']['t1'],
house_param['internal']['t2'])
Qinternal_sim = Qint[0:days_sim * 24]
Toutdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
T_outdoor_sim = Toutdoor[0:days_sim * 24]
week_day_setpoint = thermostat_sp(house_param['setpoint']['t1'],
house_param['setpoint']['t2'],
house_param['setpoint']['Night_T_SP'],
house_param['setpoint']['Day_T_SP'],
house_param['setpoint']['Flex_T_SP_workday'],
house_param['setpoint']['Wu_time'],
house_param['setpoint']['Work_time'],
house_param['setpoint']['back_home_from_work'])
day_off_setpoint = thermostat_sp(house_param['setpoint']['t1'],
house_param['setpoint']['t2'],
house_param['setpoint']['Night_T_SP'],
house_param['setpoint']['Day_T_SP'],
house_param['setpoint']['Flex_T_SP_dayoff'],
house_param['setpoint']['Wu_time'],
house_param['setpoint']['shopping_time'],
house_param['setpoint']['back_home'])
SP = SP_profile(week_day_setpoint, day_off_setpoint)
SP_sim = SP[0:days_sim * 24]
g = GasBoiler(kp=5000, ki=0, kd=0, T_setpoint=19.9, T_node=15, T_amb=10, dead_band=1, P_max=10000, P_min=2000)
# solve ODE
data = house_buffervessel(T_outdoor_sim, Qinternal_sim, Qsolar_sim, SP_sim, time_sim,
CF, Rair_outdoor, Rair_wall, Cair, Cwall, g)
# plot the results
plt.figure(figsize=(15, 5)) # key-value pair: no spaces
plt.plot(data[3], data[0], label='Tair')
plt.plot(data[3], data[1], label='Twall')
# plt.plot(time_sim, SP_sim, label='SP_Temperature')
# plt.plot(time_sim,T_outdoor_sim,label='Toutdoor')
plt.legend(loc='best')
plt.show()
def main():
house_param = load_config("config2R2C.yml")
days_sim = house_param['timing']['days_sim']
CF = house_param['ventilation']['CF']
Rair_wall, Cwall, Rair_outdoor, Cair = calculateRCOne(house_param)
print(days_sim)
#Loading the radiator and buffervessel parameters
#Heat transfer coefficient of the radiator and het capacity
cpwater = house_param['radiator']['cpwater']
rhowater = house_param['radiator']['rhowater']
Urad = house_param['radiator']['Urad']
Arad = house_param['radiator']['Arad']
volumeRadiator = house_param['radiator']['volume_rad']
UAradiator = Urad * Arad
Crad = cpwater * volumeRadiator * rhowater
#Heat capacity of the buffervessel
volumeBuffervessel = house_param['radiator']['volume_buffervessel']
Cbuffervessel = cpwater * volumeBuffervessel * rhowater
df_nen = nen5060_to_dataframe()
df_irr = run_qsun(df_nen)
print(df_irr.head())
time_sim = df_irr.iloc[0:days_sim * 24, 0].values
Qsolar = (df_irr.total_E * house_param['glass']['E'] +
df_irr.total_SE * house_param['glass']['SE'] +
df_irr.total_S * house_param['glass']['S'] +
df_irr.total_SW * house_param['glass']['SW'] +
df_irr.total_W * house_param['glass']['W'] +
df_irr.total_NW * house_param['glass']['NW'] +
df_irr.total_N * house_param['glass']['N'] +
df_irr.total_NE * house_param['glass']['NE']).values
Qsolar *= house_param['glass']['g_value']
Qsolar_sim = Qsolar[0:days_sim * 24]
Qint = internal_heat_gain(house_param['internal']['Q_day'],
house_param['internal']['delta_Q'],
house_param['internal']['t1'],
house_param['internal']['t2'])
Qinternal_sim = Qint[0:days_sim * 24]
Toutdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
T_outdoor_sim = Toutdoor[0:days_sim * 24]
week_day_setpoint = thermostat_sp(
house_param['setpoint']['t1'], house_param['setpoint']['t2'],
house_param['setpoint']['Night_T_SP'],
house_param['setpoint']['Day_T_SP'],
house_param['setpoint']['Flex_T_SP_workday'],
house_param['setpoint']['Wu_time'],
house_param['setpoint']['Work_time'],
house_param['setpoint']['back_home_from_work'])
day_off_setpoint = thermostat_sp(
house_param['setpoint']['t1'], house_param['setpoint']['t2'],
house_param['setpoint']['Night_T_SP'],
house_param['setpoint']['Day_T_SP'],
house_param['setpoint']['Flex_T_SP_dayoff'],
house_param['setpoint']['Wu_time'],
house_param['setpoint']['shopping_time'],
house_param['setpoint']['back_home'])
SP = SP_profile(week_day_setpoint, day_off_setpoint)
SP_sim = SP[0:days_sim * 24]
# solve ODE
data = house_buffervessel(T_outdoor_sim, Qinternal_sim, Qsolar_sim, SP_sim,
time_sim, CF, Rair_outdoor, Rair_wall, Cair,
Cwall, UAradiator, Crad, Cbuffervessel, cpwater)
# plot the results
plt.figure(figsize=(15, 5)) # key-value pair: no spaces
plt.plot(data[4], data[0], label='Tair')
plt.plot(data[4], data[1], label='Twall')
plt.plot(data[4], data[2], label='Treturn')
plt.plot(data[4], data[3], label='Tbuffervessel')
plt.plot(time_sim, SP_sim, label='SP_Temperature')
plt.plot(time_sim, T_outdoor_sim, label='Toutdoor')
plt.legend(loc='best')
plt.show()
def main():
house_param = load_config("Tussenwoning_alt.yaml")
days_sim = house_param['timing']['days_sim']
print('Simulation days:', days_sim)
Rair_wall, Cwall, Rair_outdoor, Cair = calculateRC(house_param)
# Loading the radiator and buffervessel parameters
# Heat transfer coefficient of the radiator and het capacity
cpwater = house_param['radiator']['cpwater']
rhowater = house_param['radiator']['rhowater']
Urad = house_param['radiator']['Urad']
Arad = house_param['radiator']['Arad']
volumeRadiator = house_param['radiator']['volume_rad']
UAradiator = Urad * Arad
Crad = cpwater * volumeRadiator * rhowater
# Heat capacity of the buffervessel
volumeBuffervessel = house_param['radiator']['volume_buffervessel']
Cbuffervessel = cpwater * volumeBuffervessel * rhowater
df_nen = nen5060_to_dataframe()
Qsolar = np.zeros(365 * 24)
for s in house_param['chains'][0]['Solar_irradiation']:
descr = s['Designation']
az = s['azimuth']
tlt = s['tilt']
print("Azimuth {0} and Tilt {1} for {2}".format(az, tlt, descr))
df_irr = run_qsun_new(df_nen, az, tlt)
Qsolar += (df_irr.total_irr).values
time_sim = df_irr.iloc[0:days_sim * 24, 0].values
CF = house_param['ventilation']['CF']
Qsolar_sim = Qsolar[0:days_sim * 24]
Q_internal = internal_heat_gain(house_param['internal']['Q_day'],
house_param['internal']['delta_Q'],
house_param['internal']['t1'],
house_param['internal']['t2'])
Qinternal_sim = Q_internal[0:days_sim * 24]
Toutdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
T_outdoor_sim = Toutdoor[0:days_sim * 24]
t_on = house_param['chains'][0]['Controller'][0]['Set_time'][0]
t_off = house_param['chains'][0]['Controller'][0]['Set_time'][1]
T_day = house_param['chains'][0]['Controller'][0]['Set_temp'][0]
T_night = house_param['chains'][0]['Controller'][0]['Set_temp'][1]
SP = simple_thermostat(t_on, t_off, T_day, T_night)
SP_sim = SP[0:days_sim * 24]
# solve ODE
data = house_buffervessel(T_outdoor_sim, Qinternal_sim, Qsolar_sim, SP_sim,
time_sim, CF, Rair_outdoor, Rair_wall, Cair,
Cwall, UAradiator, Crad, Cbuffervessel, cpwater)
# plot the results
plt.figure(figsize=(15, 5)) # key-value pair: no spaces
plt.plot(data[4], data[0], label='Tair')
plt.plot(data[4], data[1], label='Twall')
plt.plot(data[4], data[2], label='Treturn')
plt.plot(data[4], data[3], label='Tbuffervessel')
plt.plot(time_sim, SP_sim, label='SP_Temperature')
plt.plot(time_sim, T_outdoor_sim, label='Toutdoor')
plt.legend(loc='best')
plt.show()
def main(show=False):
house_param = load_config(str(CONFIGDIR / "Tussenwoning2R2C_simple.yml"))
days_sim = 365 # house_param['timing']['days_sim']
num_nodes = 2
CF = house_param['ventilation']['CF']
Cair = house_param['thermal']['capacity'][0]
Cwall = house_param['thermal']['capacity'][1]
Rair_outdoor = 1.0 / house_param['thermal']['conductance'][0]
Rair_wall = 1.0 / house_param['thermal']['conductance'][1]
print(1.0 / Rair_outdoor, Cair, 1.0 / Rair_wall, Cwall)
print(days_sim)
c_matrix = make_c_inv_matrix(house_param['thermal']['capacity'])
logger.info(f"C matrix: \n {c_matrix}")
k_matrix = make_k_minus_matrix(house_param['thermal']['conductance'])
logger.info(f"K matrix: \n {k_matrix}")
#Loading the radiator and buffervessel parameters
#Heat transfer coefficient of the radiator and het capacity
cpwater = house_param['radiator']['cpwater']
rhowater = house_param['radiator']['rhowater']
Urad = house_param['radiator']['Urad']
Arad = house_param['radiator']['Arad']
volumeRadiator = house_param['radiator']['volume_rad']
UAradiator = Urad * Arad
Crad = cpwater * volumeRadiator * rhowater
#Heat capacity of the buffervessel
volumeBuffervessel = house_param['radiator']['volume_buffervessel']
Cbuffervessel = cpwater * volumeBuffervessel * rhowater
df_nen = nen5060_to_dataframe()
"""
# old way: Qsolar as sum of transparent windows in 8 directions and horizontal
df_irr = run_qsun(df_nen)
print(df_irr.head())
time_sim = df_irr.iloc[0:days_sim*24, 0].values
Qsolar = (df_irr.total_E * house_param['glass']['E'] +
df_irr.total_SE * house_param['glass']['SE'] +
df_irr.total_S * house_param['glass']['S'] +
df_irr.total_SW * house_param['glass']['SW'] +
df_irr.total_W * house_param['glass']['W'] +
df_irr.total_NW * house_param['glass']['NW'] +
df_irr.total_N * house_param['glass']['N'] +
df_irr.total_NE * house_param['glass']['NE']).values
Qsolar *= house_param['glass']['g_value']
Qsolar_sim = Qsolar[0:days_sim*24]
"""
# new way: Qsolar2 as loop over transparent surfaces with:
# effective area = area * ZTA
# orientation in azimuth and tilt (inclination)
# partition factor over nodes
# inner loop over node divides energy of each window over nodes
# result: array with num_nodes rows
# containing 8760 values for heat delivered to each node
time_secs = np.zeros(8760)
Qsolar2 = np.zeros((num_nodes, 8760)) # num_nodes rows x 8760 cols
for s in house_param['Solar_irradiation']:
descr = s['Designation']
az = s['Azimuth']
tlt = s['Tilt']
area = s['Effective Area']
df_irr2 = run_qsun_new(df_nen, az, tlt, north_is_zero=True)
area = s['Effective Area']
partfactor = s['Node_partition'] # list of num_nodes elements 0<x<1
logger.info(
f"Window area {area} @ Azimuth {az} and Tilt {tlt} for {descr}, divided {partfactor[0]} {partfactor[1]}"
)
for n in range(num_nodes):
Qsolar2[n, :] += (df_irr2.total_irr * area * partfactor[n]).values
time_secs = df_irr2.iloc[:, 0].values # 8760 rows 1D
time_sim = time_secs[0:days_sim * 24]
Qsolar2 *= house_param['glass']['g_value']
Qsolar2_sum = np.sum(Qsolar2, axis=0)
# logger.info(f"Testing if Qsolar == Qsolar2_sum")
# np.testing.assert_allclose(Qsolar, Qsolar2_sum)
# tested to be true!
# Qsolar_sim = Qsolar[0:days_sim * 24]
Qsolar_sim = Qsolar2_sum[0:days_sim * 24]
Qint = internal_heat_gain(house_param['internal']['Q_day'],
house_param['internal']['delta_Q'],
house_param['internal']['t1'],
house_param['internal']['t2'])
Qinternal_sim = Qint[0:days_sim * 24]
Toutdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
T_outdoor_sim = Toutdoor[0:days_sim * 24]
t_on = house_param['control']['set_time'][0]
t_off = house_param['control']['set_time'][1]
T_day = house_param['control']['set_temp'][0]
T_night = house_param['control']['set_temp'][1]
SP = simple_thermostat(t_on, t_off, T_day, T_night)
SP_sim = SP[0:days_sim * 24]
# solve ODE
data = house_buffervessel(T_outdoor_sim, Qinternal_sim, Qsolar_sim, SP_sim,
time_sim, CF, Rair_outdoor, Rair_wall, Cair,
Cwall, UAradiator, Crad, Cbuffervessel, cpwater)
# if show=True, plot the results
if show:
plt.figure(figsize=(15, 5)) # key-value pair: no spaces
plt.plot(data[4], data[0], label='Tair')
plt.plot(data[4], data[1], label='Twall')
plt.plot(data[4], data[2], label='Treturn')
plt.plot(data[4], data[3], label='Tbuffervessel')
plt.plot(time_sim, SP_sim, label='SP_Temperature')
plt.plot(time_sim, T_outdoor_sim, label='Toutdoor')
plt.legend(loc='best')
plt.show()
return time_sim, SP_sim, T_outdoor_sim, data
def main():
# house_param = load_config("Tussenwoning_alt.yaml")
house_param = load_config("Tussenwoning16april.yaml")
chain = house_param['chains'][0]
num_nodes = len(chain['links'])
logger.info(f'Simulation nodes: {num_nodes}')
num_sim = house_param['Duration']
logger.info(f'Simulation points: {num_sim}')
Rair_wall, Cwall, Rair_outdoor, Cair = calculateRC(house_param)
#Loading the radiator and buffervessel parameters
#Heat transfer coefficient of the radiator and het capacity
cpwater = house_param['radiator']['cpwater']
rhowater = house_param['radiator']['rhowater']
Urad = house_param['radiator']['Urad']
Arad = house_param['radiator']['Arad']
volumeRadiator = house_param['radiator']['volume_rad']
UAradiator = Urad * Arad
Crad = cpwater * volumeRadiator * rhowater
#Heat capacity of the buffervessel
volumeBuffervessel = house_param['radiator']['volume_buffervessel']
Cbuffervessel = cpwater * volumeBuffervessel * rhowater
df_nen = nen5060_to_dataframe()
Qsolar = np.zeros((8760, num_nodes)) # 8760 rows x 2 cols
for s in house_param['chains'][0]['Solar_irradiation']:
descr = s['Designation']
az = s['Azimuth']
tlt = s['Tilt']
print("Azimuth {0} and Tilt {1} for {2}".format(az, tlt, descr))
df_irr = run_qsun_new(df_nen, az, tlt, north_is_zero=True)
area = s['Effective Area']
partfactor = s['Node_partition']
for n in range(num_nodes):
Qsolar[:, n] += (df_irr.total_irr).values * area * partfactor[n]
time_year = df_irr.iloc[:, 0].values # 8760 rows 1D
sources = house_param['chains'][0]['Sources']
for src in sources:
if src['name'] == 'Internal_load':
# Q_internal = np.zeros(8760) # 8760 rows x 1 cols
Q_internal = internal_heat_gain(src['Set_load'][0],
src['Set_load'][1],
src['Set_time'][0],
src['Set_time'][1])
T_outdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
t_on = house_param['chains'][0]['Control']['Set_time'][0]
t_off = house_param['chains'][0]['Control']['Set_time'][1]
T_day = house_param['chains'][0]['Control']['Set_temp'][0]
T_night = house_param['chains'][0]['Control']['Set_temp'][1]
SP = simple_thermostat(t_on, t_off, T_day, T_night)
num_sim = 8760
time_sim = time_year[0:num_sim] # 480 cols 1D
Qsolar_sim = Qsolar[0:num_sim, :].T # 2 rows x 480 cols
Qinternal_sim = Q_internal[0:num_sim].flatten() # 480 cols 1D
T_outdoor_sim = T_outdoor[0:num_sim].flatten() # 480 cols 1D
SP_sim = SP[0:num_sim] # 480 cols 1D
# solve ODE
data = house_buffervessel(T_outdoor_sim, Qinternal_sim, Qsolar_sim, SP_sim,
time_sim, Rair_outdoor, Rair_wall, Cair, Cwall,
UAradiator, Crad, Cbuffervessel, cpwater)
# df_out = pd.DataFrame(data[4], columns=['Timestep'])
df_out = pd.DataFrame({'Timestep': data[4]})
df_out['Outdoor temperature'] = T_outdoor_sim
for n in range(num_nodes):
nodename = house_param['chains'][0]['links'][n]['Name']
df_out["T_{}".format(n)] = data[0].tolist()
df_out["Solar_{}".format(n)] = Qsolar_sim[n, :]
if nodename == 'Internals':
df_out["Internal_{}".format(n)] = Qinternal_sim
df_out["Heating_{}".format(n)] = 0
df_out['Treturn'] = data[2].tolist()
df_out['Tbuffervessel'] = data[3]
wb = Workbook()
ws = wb.active
ws.append(
['DESCRIPTION', 'Resultaten HAN Dynamic Model Heat Built Environment'])
ws.append(['Chain number', 0])
ws.append([
'Designation', None, '2R-2C-1-zone', None, None, None, '2R-2C-1-zone'
])
ws.append(['Node number', None, 0, None, None, None, 1])
ws.append([
'Designation', None, house_param['chains'][0]['links'][0]['Name'],
None, None, None, house_param['chains'][0]['links'][1]['Name']
])
for r in dataframe_to_rows(df_out, index=False):
ws.append(r)
# df_out.to_excel('tst.xlsx', index=False, startrow=10)
wb.save('tst.xlsx')
timeaxis = data[4] / 3600
# plot the results
# plt.figure(figsize=(15, 5)) # key-value pair: no spaces
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True, figsize=(
15,
8)) # 3 rijen en 1 kolom. x-axis will be shared among all subplots.
ax1.plot(timeaxis, data[0], label='Tair')
ax1.plot(timeaxis, data[1], label='Twall')
ax1.plot(time_sim / 3600, SP_sim, label='SP_Temperature')
ax1.set_ylabel('T ($\degree C$)')
ax1.set_ylim(15, 40)
ax2.plot(timeaxis, data[2], label='Treturn')
ax2.plot(timeaxis, data[3], label='Tbuffervessel')
ax2.set_ylabel('T ($\degree C$)')
ax2.set_ylim(10, 90)
ax3.plot(time_sim / 3600, T_outdoor_sim, label='Toutdoor')
ax3.set_ylabel('T ($\degree C$)')
ax3.set_ylim(-10, 30)
ax1.set_title('Simulation2R2C_buffervessel_newyaml_with_xl')
ax3.set_xlabel('time (h)')
ax1.legend()
ax2.legend()
ax3.legend()
plt.show()
def main():
house_param = load_config("config2R2C.yml")
days_sim = house_param['timing']['days_sim']
CF = house_param['ventilation']['CF']
Rair_wall, Cwall, Rair_outdoor, Cair = calculateRCOne(house_param)
print('Simulation days:', days_sim)
df_nen = nen5060_to_dataframe()
df_irr = run_qsun(df_nen)
#df_weeks = read_week('NEN_data')
print(df_irr.head())
time_sim = df_irr.iloc[0:days_sim * 24, 0].values
Qsolar = (df_irr.total_E * house_param['glass']['E'] +
df_irr.total_SE * house_param['glass']['SE'] +
df_irr.total_S * house_param['glass']['S'] +
df_irr.total_SW * house_param['glass']['SW'] +
df_irr.total_W * house_param['glass']['W'] +
df_irr.total_NW * house_param['glass']['NW'] +
df_irr.total_N * house_param['glass']['N'] +
df_irr.total_NE * house_param['glass']['NE']).values
Qsolar *= house_param['glass']['g_value']
Qsolar_sim = Qsolar[0:days_sim * 24]
#print(len(Qsolar_sim))
Qint = internal_heat_gain(house_param['internal']['Q_day'],
house_param['internal']['delta_Q'],
house_param['internal']['t1'],
house_param['internal']['t2'])
Qinternal_sim = Qint[0:days_sim * 24]
Toutdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
T_outdoor_sim = Toutdoor[0:days_sim * 24]
#plt.plot(T_outdoor_sim)
week_day_setpoint = thermostat_sp(
house_param['setpoint']['t1'], house_param['setpoint']['t2'],
house_param['setpoint']['Night_T_SP'],
house_param['setpoint']['Day_T_SP'],
house_param['setpoint']['Flex_T_SP_workday'],
house_param['setpoint']['Wu_time'],
house_param['setpoint']['Work_time'],
house_param['setpoint']['back_home_from_work'])
day_off_setpoint = thermostat_sp(
house_param['setpoint']['t1'], house_param['setpoint']['t2'],
house_param['setpoint']['Night_T_SP'],
house_param['setpoint']['Day_T_SP'],
house_param['setpoint']['Flex_T_SP_dayoff'],
house_param['setpoint']['Wu_time'],
house_param['setpoint']['shopping_time'],
house_param['setpoint']['back_home'])
SP = SP_profile(week_day_setpoint, day_off_setpoint)
#SP = temp_sp(house_param['setpoint']['t1'],
# house_param['setpoint']['t2'],
# house_param['setpoint']['Night_T_SP'],
# house_param['setpoint']['Day_T_SP'],
# house_param['setpoint']['Wu_time'],
# house_param['setpoint']['Work_time'],
# house_param['setpoint']['back_home'])
SP_sim = SP[0:days_sim * 24]
# addition NTA8800 house model
# Controller value
kp = house_param['controller']['kp']
# solve ODE
data = house(T_outdoor_sim, Qinternal_sim, Qsolar_sim, SP_sim, time_sim,
CF, Rair_outdoor, Rair_wall, Cair, Cwall, kp)
# plot the results
plt.figure(figsize=(15, 5)) # key-value pair: no spaces
plt.plot(data[0], label='Tair')
plt.plot(data[1], label='Twall')
plt.plot(SP_sim, label='SP_Temperature')
# plt.plot(T_outdoor_sim,label='Toutdoor')
plt.legend(loc='best')
plt.title("Simulation2R2C")
plt.show()
'''
def main():
house_param = load_config("Tussenwoning_alt.yaml")
days_sim = house_param['timing']['days_sim']
print('Simulation days:', days_sim)
Rair_wall, Cwall, Rair_outdoor, Cair = calculateRC(house_param)
df_nen = nen5060_to_dataframe()
Qsolar = np.zeros(365 * 24)
for s in house_param['chains'][0]['Solar_irradiation']:
descr = s['Designation']
az = s['azimuth']
tlt = s['tilt']
print("Azimuth {0} and Tilt {1} for {2}".format(az, tlt, descr))
df_irr = run_qsun_new(df_nen, az, tlt)
Qsolar += (df_irr.total_irr).values
time_sim = df_irr.iloc[0:days_sim * 24, 0].values
CF = house_param['ventilation']['CF']
Qsolar_sim = Qsolar[0:days_sim * 24]
# Q_internal = np.zeros(days_sim*24)
Q_internal = internal_heat_gain(house_param['internal']['Q_day'],
house_param['internal']['delta_Q'],
house_param['internal']['t1'],
house_param['internal']['t2'])
Q_internal_sim = Q_internal[0:days_sim * 24]
#Q_internal = Q_internal.flatten()
T_outdoor = df_nen.loc[:, 'temperatuur'].values / 10.0 # temperature
T_outdoor_sim = T_outdoor[0:days_sim * 24]
# plt.plot(T_outdoor_sim)
t_on = house_param['chains'][0]['Controller'][0]['Set_time'][0]
t_off = house_param['chains'][0]['Controller'][0]['Set_time'][1]
T_day = house_param['chains'][0]['Controller'][0]['Set_temp'][0]
T_night = house_param['chains'][0]['Controller'][0]['Set_temp'][1]
SP = simple_thermostat(t_on, t_off, T_day, T_night)
SP_sim = SP[0:days_sim * 24]
# addition NTA8800 house model
# Controller value
kp = house_param['chains'][0]['Controller'][0]['kp']
# solve ODE
data = house(T_outdoor_sim, Q_internal_sim, Qsolar_sim, SP, time_sim, CF,
Rair_outdoor, Rair_wall, Cair, Cwall, kp)
# plot the results
plt.figure(figsize=(15, 5)) # key-value pair: no spaces
plt.plot(data[0], label='Tair')
plt.plot(data[1], label='Twall')
plt.plot(SP_sim, label='SP_Temperature')
plt.plot(T_outdoor_sim, label='Toutdoor')
plt.legend(loc='best')
plt.title("Simulation2R2C_newyaml")
plt.show()
'''