def calc_PVT_module(config, radiation_Wperm2, panel_properties_SC,
panel_properties_PV, Tamb_vector_C, IAM_b, tilt_angle_deg,
pipe_lengths, absorbed_radiation_PV_Wperm2, Tcell_PV_C,
module_area_per_group_m2):
"""
This function calculates the heat & electricity production from PVT collectors.
The heat production calculation is adapted from calc_SC_module and then the updated cell temperature is used to
calculate PV electricity production.
:param tilt_angle_deg: solar panel tilt angle [rad]
:param IAM_b_vector: incident angle modifier for beam radiation [-]
:param I_direct_vector: direct radiation [W/m2]
:param I_diffuse_vector: diffuse radiation [W/m2]
:param Tamb_vector_C: dry bulb temperature [C]
:param IAM_d_vector: incident angle modifier for diffuse radiation [-]
:param Leq: equivalent length of pipes per aperture area [m/m2 aperture)
:param Le: equivalent length of collector pipes per aperture area [m/m2 aperture]
:param absorbed_radiation_PV_Wperm2: absorbed solar radiation of PV module [Wh/m2]
:param Tcell_PV_C: PV cell temperature [C]
:param module_area_per_group_m2: PV module area [m2]
:return:
..[J. Allan et al., 2015] J. Allan, Z. Dehouche, S. Stankovic, L. Mauricette. "Performance testing of thermal and
photovoltaic thermal solar collectors." Energy Science & Engineering 2015; 3(4): 310-326
"""
# read variables
Tin_C = get_t_in_pvt(config)
n0 = panel_properties_SC[
'n0'] # zero loss efficiency at normal incidence [-]
c1 = panel_properties_SC[
'c1'] # collector heat loss coefficient at zero temperature difference and wind speed [W/m2K]
c2 = panel_properties_SC[
'c2'] # temperature difference dependency of the heat loss coefficient [W/m2K2]
mB0_r = panel_properties_SC[
'mB0_r'] # nominal flow rate per aperture area [kg/h/m2 aperture]
mB_max_r = panel_properties_SC[
'mB_max_r'] # maximum flow rate per aperture area
mB_min_r = panel_properties_SC[
'mB_min_r'] # minimum flow rate per aperture area
C_eff_Jperm2K = panel_properties_SC[
'C_eff'] # thermal capacitance of module [J/m2K]
IAM_d = panel_properties_SC[
'IAM_d'] # incident angle modifier for diffuse radiation [-]
dP1 = panel_properties_SC['dP1'] # pressure drop [Pa/m2] at zero flow rate
dP2 = panel_properties_SC[
'dP2'] # pressure drop [Pa/m2] at nominal flow rate (mB0)
dP3 = panel_properties_SC[
'dP3'] # pressure drop [Pa/m2] at maximum flow rate (mB_max)
dP4 = panel_properties_SC[
'dP4'] # pressure drop [Pa/m2] at minimum flow rate (mB_min)
Cp_fluid_JperkgK = panel_properties_SC['Cp_fluid'] # J/kgK
aperature_area_ratio = panel_properties_SC[
'aperture_area_ratio'] # aperature area ratio [-]
area_pv_module = panel_properties_PV['module_length_m']**2
Nseg = panel_properties_SC['Nseg']
T_max_C = panel_properties_SC['t_max']
eff_nom = panel_properties_PV['PV_n']
Bref = panel_properties_PV['PV_Bref']
misc_losses = panel_properties_PV['misc_losses']
aperture_area_m2 = aperature_area_ratio * area_pv_module # aperture area of each module [m2]
msc_max_kgpers = mB_max_r * aperture_area_m2 / 3600 # maximum mass flow [kg/s]
# Do the calculation of every time step for every possible flow condition
# get states where highly performing values are obtained.
specific_flows_kgpers = [
np.zeros(HOURS_IN_YEAR),
(np.zeros(HOURS_IN_YEAR) + mB0_r) * aperture_area_m2 / 3600,
(np.zeros(HOURS_IN_YEAR) + mB_max_r) * aperture_area_m2 / 3600,
(np.zeros(HOURS_IN_YEAR) + mB_min_r) * aperture_area_m2 / 3600,
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
] # in kg/s
specific_pressure_losses_Pa = [
np.zeros(HOURS_IN_YEAR),
(np.zeros(HOURS_IN_YEAR) + dP2) * aperture_area_m2,
(np.zeros(HOURS_IN_YEAR) + dP3) * aperture_area_m2,
(np.zeros(HOURS_IN_YEAR) + dP4) * aperture_area_m2,
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
] # in Pa
# generate empty lists to store results
temperature_out = [
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
]
temperature_in = [
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
]
supply_out_kW = [
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
]
supply_losses_kW = [
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
]
auxiliary_electricity_kW = [
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
]
temperature_mean = [
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR),
np.zeros(HOURS_IN_YEAR)
]
mcp_kWperK = np.zeros(HOURS_IN_YEAR)
T_module_C = np.zeros(HOURS_IN_YEAR)
# calculate absorbed radiation
tilt_rad = radians(tilt_angle_deg)
q_rad_vector = np.vectorize(calc_q_rad)(
n0, IAM_b, IAM_d, radiation_Wperm2.I_direct,
radiation_Wperm2.I_diffuse,
tilt_rad) # absorbed solar radiation in W/m2 is a mean of the group
counter = 0
Flag = False
Flag2 = False
for flow in range(6):
Mo_seg = 1 # mode of segmented heat loss calculation. only one mode is implemented.
TIME0 = 0
DELT = 1 # timestep 1 hour
delts = DELT * 3600 # convert time step in seconds
Tfl = np.zeros(
3
) # create vector to store value at previous [1] and present [2] time-steps
DT = np.zeros(3)
Tabs = np.zeros(3)
STORED = np.zeros(600)
TflA = np.zeros(600)
TflB = np.zeros(600)
TabsB = np.zeros(600)
TabsA = np.zeros(600)
q_gain_Seg = np.zeros(101) # maximum Iseg = maximum Nseg + 1 = 101
for time in range(HOURS_IN_YEAR):
# c1_pvt = c1 - eff_nom * Bref * absorbed_radiation_PV_Wperm2[time] #todo: to delete
c1_pvt = calc_cl_pvt(Bref, absorbed_radiation_PV_Wperm2, c1,
eff_nom, time)
Mfl_kgpers = calc_Mfl_kgpers(DELT, Nseg, STORED, TIME0, Tin_C,
specific_flows_kgpers[flow], time,
Cp_fluid_JperkgK, C_eff_Jperm2K,
aperture_area_m2)
# calculate average fluid temperature and average absorber temperature at the beginning of the time-step
Tamb_C = Tamb_vector_C[time]
q_rad_Wperm2 = q_rad_vector[time]
Tout_C = calc_Tout_C(Cp_fluid_JperkgK, DT, Mfl_kgpers, Nseg,
STORED, Tabs, Tamb_C, Tfl, Tin_C,
aperture_area_m2, c1_pvt, q_rad_Wperm2)
# calculate q_gain with the guess for DT[1]
q_gain_Wperm2 = calc_q_gain(Tfl, q_rad_Wperm2, DT, Tin_C,
aperture_area_m2, c1_pvt, c2,
Mfl_kgpers, delts, Cp_fluid_JperkgK,
C_eff_Jperm2K, Tamb_C)
Aseg_m2 = aperture_area_m2 / Nseg # aperture area per segment
# multi-segment calculation to avoid temperature jump at times of flow rate changes
Tout_Seg_C = do_multi_segment_calculation(
Aseg_m2, C_eff_Jperm2K, Cp_fluid_JperkgK, DT, Mfl_kgpers,
Mo_seg, Nseg, STORED, Tabs, TabsA, Tamb_C, Tfl, TflA, TflB,
Tin_C, Tout_C, c1_pvt, c2, delts, q_gain_Seg, q_gain_Wperm2,
q_rad_Wperm2)
# resulting energy output
q_out_kW = Mfl_kgpers * Cp_fluid_JperkgK * (Tout_Seg_C -
Tin_C) / 1000 # [kW]
Tabs[2] = 0
# storage of the mean temperature
for Iseg in range(1, Nseg + 1):
STORED[200 + Iseg] = TflB[Iseg]
STORED[400 + Iseg] = TabsB[Iseg]
Tabs[2] = Tabs[2] + TabsB[Iseg] / Nseg
# outputs
temperature_out[flow][time] = Tout_Seg_C
temperature_in[flow][time] = Tin_C
supply_out_kW[flow][time] = q_out_kW
temperature_mean[flow][time] = (
Tin_C + Tout_Seg_C) / 2 # Mean absorber temperature at present
q_gain_Wperm2 = 0
TavgB = 0
TavgA = 0
for Iseg in range(1, Nseg + 1):
q_gain_Wperm2 = q_gain_Wperm2 + q_gain_Seg * Aseg_m2 # W
TavgA = TavgA + TflA[Iseg] / Nseg
TavgB = TavgB + TflB[Iseg] / Nseg
# # OUT[9] = qgain/Area_a # in W/m2
# q_mtherm_Wperm2 = (TavgB - TavgA) * C_eff_Jperm2K * aperture_area_m2 / delts
# q_balance_error = q_gain_Wperm2 - q_mtherm_Wperm2 - q_out_kW
# OUT[11] = q_mtherm
# OUT[12] = q_balance_error
if flow < 4:
auxiliary_electricity_kW[flow] = vectorize_calc_Eaux_SC(
specific_flows_kgpers[flow], specific_pressure_losses_Pa[flow],
pipe_lengths, aperture_area_m2) # in kW
if flow == 3:
q1 = supply_out_kW[0]
q2 = supply_out_kW[1]
q3 = supply_out_kW[2]
q4 = supply_out_kW[3]
E1 = auxiliary_electricity_kW[0]
E2 = auxiliary_electricity_kW[1]
E3 = auxiliary_electricity_kW[2]
E4 = auxiliary_electricity_kW[3]
specific_flows_kgpers[4], specific_pressure_losses_Pa[
4] = calc_optimal_mass_flow(q1, q2, q3, q4, E1, E2, E3, E4, 0,
mB0_r, mB_max_r, mB_min_r, 0, dP2,
dP3, dP4, aperture_area_m2)
if flow == 4:
auxiliary_electricity_kW[flow] = vectorize_calc_Eaux_SC(
specific_flows_kgpers[flow], specific_pressure_losses_Pa[flow],
pipe_lengths, aperture_area_m2) # in kW
dp5 = specific_pressure_losses_Pa[flow]
q5 = supply_out_kW[flow]
m5 = specific_flows_kgpers[flow]
# set points to zero when load is negative
specific_flows_kgpers[5], specific_pressure_losses_Pa[
5] = calc_optimal_mass_flow_2(m5, q5, dp5)
if flow == 5: # optimal mass flow
supply_losses_kW[flow] = np.vectorize(calc_qloss_network)(
specific_flows_kgpers[flow], pipe_lengths['l_ext_mperm2'],
aperture_area_m2, temperature_mean[flow], Tamb_vector_C,
msc_max_kgpers)
supply_out_pre = supply_out_kW[flow].copy(
) + supply_losses_kW[flow].copy()
auxiliary_electricity_kW[flow] = vectorize_calc_Eaux_SC(
specific_flows_kgpers[flow], specific_pressure_losses_Pa[flow],
pipe_lengths, aperture_area_m2) # in kW
supply_out_total_kW = supply_out_kW + 0.5 * auxiliary_electricity_kW[
flow] - supply_losses_kW[flow]
mcp_kWperK = specific_flows_kgpers[flow] * (Cp_fluid_JperkgK / 1000
) # mcp in kW/c
turn_off_the_water_circuit_if_total_energy_supply_is_zero(
T_module_C, Tcell_PV_C, auxiliary_electricity_kW[flow], mcp_kWperK,
supply_out_total_kW[5], temperature_in[5], temperature_out[5])
el_output_PV_kW = np.vectorize(calc_PV_power)(absorbed_radiation_PV_Wperm2,
T_module_C, eff_nom,
module_area_per_group_m2,
Bref, misc_losses)
# write results into a list
result = [
supply_losses_kW[5], supply_out_total_kW[5],
auxiliary_electricity_kW[5], temperature_out[5], temperature_in[5],
mcp_kWperK, el_output_PV_kW
]
return result
def calc_PVT_module(config, radiation_Wperm2, panel_properties_SC,
panel_properties_PV, Tamb_vector_C, IAM_b, tilt_angle_deg,
pipe_lengths, absorbed_radiation_PV_Wperm2, Tcell_PV_C,
module_area_per_group_m2):
"""
This function calculates the heat & electricity production from PVT collectors.
The heat production calculation is adapted from calc_SC_module and then the updated cell temperature is used to
calculate PV electricity production.
:param tilt_angle_deg: solar panel tilt angle [rad]
:param IAM_b_vector: incident angle modifier for beam radiation [-]
:param I_direct_vector: direct radiation [W/m2]
:param I_diffuse_vector: diffuse radiation [W/m2]
:param Tamb_vector_C: dry bulb temperature [C]
:param IAM_d_vector: incident angle modifier for diffuse radiation [-]
:param Leq: equivalent length of pipes per aperture area [m/m2 aperture)
:param Le: equivalent length of collector pipes per aperture area [m/m2 aperture]
:param absorbed_radiation_PV_Wperm2: absorbed solar radiation of PV module [Wh/m2]
:param Tcell_PV_C: PV cell temperature [C]
:param module_area_per_group_m2: PV module area [m2]
:return:
..[J. Allan et al., 2015] J. Allan, Z. Dehouche, S. Stankovic, L. Mauricette. "Performance testing of thermal and
photovoltaic thermal solar collectors." Energy Science & Engineering 2015; 3(4): 310-326
"""
# read variables
Tin_C = get_t_in_pvt(config)
n0 = panel_properties_SC[
'n0'] # zero loss efficiency at normal incidence [-]
c1 = panel_properties_SC[
'c1'] # collector heat loss coefficient at zero temperature difference and wind speed [W/m2K]
c2 = panel_properties_SC[
'c2'] # temperature difference dependency of the heat loss coefficient [W/m2K2]
mB0_r = panel_properties_SC[
'mB0_r'] # nominal flow rate per aperture area [kg/h/m2 aperture]
mB_max_r = panel_properties_SC[
'mB_max_r'] # maximum flow rate per aperture area
mB_min_r = panel_properties_SC[
'mB_min_r'] # minimum flow rate per aperture area
C_eff_Jperm2K = panel_properties_SC[
'C_eff'] # thermal capacitance of module [J/m2K]
IAM_d = panel_properties_SC[
'IAM_d'] # incident angle modifier for diffuse radiation [-]
dP1 = panel_properties_SC['dP1'] # pressure drop [Pa/m2] at zero flow rate
dP2 = panel_properties_SC[
'dP2'] # pressure drop [Pa/m2] at nominal flow rate (mB0)
dP3 = panel_properties_SC[
'dP3'] # pressure drop [Pa/m2] at maximum flow rate (mB_max)
dP4 = panel_properties_SC[
'dP4'] # pressure drop [Pa/m2] at minimum flow rate (mB_min)
Cp_fluid_JperkgK = panel_properties_SC['Cp_fluid'] # J/kgK
aperature_area_ratio = panel_properties_SC[
'aperture_area_ratio'] # aperature area ratio [-]
area_pv_module = panel_properties_PV['module_length_m']**2
Nseg = panel_properties_SC['Nseg']
T_max_C = panel_properties_SC['t_max']
eff_nom = panel_properties_PV['PV_n']
Bref = panel_properties_PV['PV_Bref']
misc_losses = panel_properties_PV['misc_losses']
aperture_area_m2 = aperature_area_ratio * area_pv_module # aperture area of each module [m2]
msc_max_kgpers = mB_max_r * aperture_area_m2 / 3600 # maximum mass flow [kg/s]
# Do the calculation of every time step for every possible flow condition
# get states where highly performing values are obtained.
specific_flows_kgpers = [
np.zeros(8760), (np.zeros(8760) + mB0_r) * aperture_area_m2 / 3600,
(np.zeros(8760) + mB_max_r) * aperture_area_m2 / 3600,
(np.zeros(8760) + mB_min_r) * aperture_area_m2 / 3600,
np.zeros(8760),
np.zeros(8760)
] # in kg/s
specific_pressure_losses_Pa = [
np.zeros(8760), (np.zeros(8760) + dP2) * aperture_area_m2,
(np.zeros(8760) + dP3) * aperture_area_m2,
(np.zeros(8760) + dP4) * aperture_area_m2,
np.zeros(8760),
np.zeros(8760)
] # in Pa
# generate empty lists to store results
temperature_out = [
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760)
]
temperature_in = [
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760)
]
supply_out_kW = [
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760)
]
supply_losses_kW = [
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760)
]
auxiliary_electricity_kW = [
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760)
]
temperature_mean = [
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760),
np.zeros(8760)
]
mcp_kWperK = np.zeros(8760)
T_module_C = np.zeros(8760)
# calculate absorbed radiation
tilt_rad = radians(tilt_angle_deg)
q_rad_vector = np.vectorize(calc_q_rad)(
n0, IAM_b, IAM_d, radiation_Wperm2.I_direct,
radiation_Wperm2.I_diffuse,
tilt_rad) # absorbed solar radiation in W/m2 is a mean of the group
counter = 0
Flag = False
Flag2 = False
for flow in range(6):
Mo_seg = 1 # mode of segmented heat loss calculation. only one mode is implemented.
TIME0 = 0
DELT = 1 # timestep 1 hour
delts = DELT * 3600 # convert time step in seconds
Tfl = np.zeros(
[3, 1]
) # create vector to store value at previous [1] and present [2] time-steps
DT = np.zeros([3, 1])
Tabs = np.zeros([3, 1])
STORED = np.zeros([600, 1])
TflA = np.zeros([600, 1])
TflB = np.zeros([600, 1])
TabsB = np.zeros([600, 1])
TabsA = np.zeros([600, 1])
q_gain_Seg = np.zeros([101,
1]) # maximum Iseg = maximum Nseg + 1 = 101
for time in range(8760):
#c1_pvt = c1 - eff_nom * Bref * absorbed_radiation_PV_Wperm2[time] #todo: to delete
c1_pvt = max(0, c1 -
eff_nom * Bref * absorbed_radiation_PV_Wperm2[time]
) # _[J. Allan et al., 2015] eq.(18)
Mfl_kgpers = specific_flows_kgpers[flow][time]
if time < TIME0 + DELT / 2:
for Iseg in range(101, 501): # 400 points with the data
STORED[Iseg] = Tin_C
else:
for Iseg in range(1, Nseg): # 400 points with the data
STORED[100 + Iseg] = STORED[200 + Iseg]
STORED[300 + Iseg] = STORED[400 + Iseg]
# calculate stability criteria
if Mfl_kgpers > 0:
stability_criteria = Mfl_kgpers * Cp_fluid_JperkgK * Nseg * (
DELT * 3600) / (C_eff_Jperm2K * aperture_area_m2)
if stability_criteria <= 0.5:
print('ERROR: stability criteria' +
str(stability_criteria) +
'is not reached. aperture_area: ' +
str(aperture_area_m2) + 'mass flow: ' +
str(Mfl_kgpers))
# calculate average fluid temperature and average absorber temperature at the beginning of the time-step
Tamb_C = Tamb_vector_C[time]
q_rad_Wperm2 = q_rad_vector[time]
Tfl[1] = 0 # mean fluid temperature
Tabs[1] = 0 # mean absorber temperature
for Iseg in range(1, Nseg + 1):
Tfl[1] = Tfl[1] + STORED[100 +
Iseg] / Nseg # mean fluid temperature
Tabs[1] = Tabs[1] + STORED[
300 + Iseg] / Nseg # mean absorber temperature
# first guess for Delta T
if Mfl_kgpers > 0:
Tout = Tin_C + (q_rad_Wperm2 - (
(c1_pvt) + 0.5) * (Tin_C - Tamb_C)) / (
Mfl_kgpers * Cp_fluid_JperkgK / aperture_area_m2)
Tfl[2] = (Tin_C + Tout
) / 2 # mean fluid temperature at present time-step
else:
# if c1_pvt < 0:
# print('c1_pvt: ', c1_pvt)
Tout = Tamb_C + q_rad_Wperm2 / (c1_pvt + 0.5)
Tfl[2] = Tout # fluid temperature same as output
# if Tout > T_max_C:
# print('Tout: ',Tout, 'c1_pvt: ', c1_pvt, 'q_rad', q_rad_Wperm2)
DT[1] = Tfl[
2] - Tamb_C # difference between mean absorber temperature and the ambient temperature
# calculate q_gain with the guess for DT[1]
q_gain_Wperm2 = calc_q_gain(Tfl, Tabs, q_rad_Wperm2, DT, Tin_C,
Tout, aperture_area_m2, c1_pvt, c2,
Mfl_kgpers, delts, Cp_fluid_JperkgK,
C_eff_Jperm2K, Tamb_C)
Aseg_m2 = aperture_area_m2 / Nseg # aperture area per segment
for Iseg in range(1, Nseg + 1):
# get temperatures of the previous time-step
TflA[Iseg] = STORED[100 + Iseg]
TabsA[Iseg] = STORED[300 + Iseg]
if Iseg > 1:
TinSeg = ToutSeg
else:
TinSeg = Tin_C
if Mfl_kgpers > 0 and Mo_seg == 1: # same heat gain/ losses for all segments
ToutSeg = ((Mfl_kgpers * Cp_fluid_JperkgK *
(TinSeg + 273.15)) / Aseg_m2 -
(C_eff_Jperm2K * (TinSeg + 273.15)) /
(2 * delts) + q_gain_Wperm2 +
(C_eff_Jperm2K *
(TflA[Iseg] + 273.15) / delts)) / (
Mfl_kgpers * Cp_fluid_JperkgK / Aseg_m2 +
C_eff_Jperm2K / (2 * delts))
ToutSeg = ToutSeg - 273.15 # in [C]
TflB[Iseg] = (TinSeg + ToutSeg) / 2
else: # heat losses based on each segment's inlet and outlet temperatures.
Tfl[1] = TflA[Iseg]
Tabs[1] = TabsA[Iseg]
q_gain_Wperm2 = calc_q_gain(Tfl, Tabs, q_rad_Wperm2, DT,
TinSeg, Tout, Aseg_m2, c1_pvt,
c2, Mfl_kgpers, delts,
Cp_fluid_JperkgK,
C_eff_Jperm2K, Tamb_C)
ToutSeg = Tout
if Mfl_kgpers > 0:
TflB[Iseg] = (TinSeg + ToutSeg) / 2
ToutSeg = TflA[Iseg] + (q_gain_Wperm2 *
delts) / C_eff_Jperm2K
else:
TflB[Iseg] = ToutSeg
# TflB[Iseg] = ToutSeg
q_fluid_Wperm2 = (
ToutSeg -
TinSeg) * Mfl_kgpers * Cp_fluid_JperkgK / Aseg_m2
q_mtherm_Wperm2 = (TflB[Iseg] -
TflA[Iseg]) * C_eff_Jperm2K / delts
q_balance_error = q_gain_Wperm2 - q_fluid_Wperm2 - q_mtherm_Wperm2
if abs(q_balance_error) > 1:
time = time # re-enter the iteration when energy balance not satisfied
q_gain_Seg[Iseg] = q_gain_Wperm2 # in W/m2
# resulting energy output
q_out_kW = Mfl_kgpers * Cp_fluid_JperkgK * (ToutSeg -
Tin_C) / 1000 # [kW]
Tabs[2] = 0
# storage of the mean temperature
for Iseg in range(1, Nseg + 1):
STORED[200 + Iseg] = TflB[Iseg]
STORED[400 + Iseg] = TabsB[Iseg]
Tabs[2] = Tabs[2] + TabsB[Iseg] / Nseg
# outputs
temperature_out[flow][time] = ToutSeg
temperature_in[flow][time] = Tin_C
supply_out_kW[flow][time] = q_out_kW
temperature_mean[flow][time] = (
Tin_C + ToutSeg) / 2 # Mean absorber temperature at present
q_gain_Wperm2 = 0
TavgB = 0
TavgA = 0
for Iseg in range(1, Nseg + 1):
q_gain_Wperm2 = q_gain_Wperm2 + q_gain_Seg * Aseg_m2 # W
TavgA = TavgA + TflA[Iseg] / Nseg
TavgB = TavgB + TflB[Iseg] / Nseg
# # OUT[9] = qgain/Area_a # in W/m2
# q_mtherm_Wperm2 = (TavgB - TavgA) * C_eff_Jperm2K * aperture_area_m2 / delts
# q_balance_error = q_gain_Wperm2 - q_mtherm_Wperm2 - q_out_kW
# OUT[11] = q_mtherm
# OUT[12] = q_balance_error
if flow < 4:
auxiliary_electricity_kW[flow] = np.vectorize(calc_Eaux_SC)(
specific_flows_kgpers[flow], specific_pressure_losses_Pa[flow],
pipe_lengths, aperture_area_m2) # in kW
if flow == 3:
q1 = supply_out_kW[0]
q2 = supply_out_kW[1]
q3 = supply_out_kW[2]
q4 = supply_out_kW[3]
E1 = auxiliary_electricity_kW[0]
E2 = auxiliary_electricity_kW[1]
E3 = auxiliary_electricity_kW[2]
E4 = auxiliary_electricity_kW[3]
specific_flows_kgpers[4], specific_pressure_losses_Pa[
4] = calc_optimal_mass_flow(q1, q2, q3, q4, E1, E2, E3, E4, 0,
mB0_r, mB_max_r, mB_min_r, 0, dP2,
dP3, dP4, aperture_area_m2)
if flow == 4:
auxiliary_electricity_kW[flow] = np.vectorize(calc_Eaux_SC)(
specific_flows_kgpers[flow], specific_pressure_losses_Pa[flow],
pipe_lengths, aperture_area_m2) # in kW
dp5 = specific_pressure_losses_Pa[flow]
q5 = supply_out_kW[flow]
m5 = specific_flows_kgpers[flow]
# set points to zero when load is negative
specific_flows_kgpers[5], specific_pressure_losses_Pa[
5] = calc_optimal_mass_flow_2(m5, q5, dp5)
if flow == 5: # optimal mass flow
supply_losses_kW[flow] = np.vectorize(calc_qloss_network)(
specific_flows_kgpers[flow], pipe_lengths['l_ext_mperm2'],
aperture_area_m2, temperature_mean[flow], Tamb_vector_C,
msc_max_kgpers)
supply_out_pre = supply_out_kW[flow].copy(
) + supply_losses_kW[flow].copy()
auxiliary_electricity_kW[flow] = np.vectorize(calc_Eaux_SC)(
specific_flows_kgpers[flow], specific_pressure_losses_Pa[flow],
pipe_lengths, aperture_area_m2) # in kW
supply_out_total_kW = supply_out_kW + 0.5 * auxiliary_electricity_kW[
flow] - supply_losses_kW[flow]
mcp_kWperK = specific_flows_kgpers[flow] * (Cp_fluid_JperkgK / 1000
) # mcp in kW/c
for x in range(8760):
# turn off the water circuit if total energy supply is zero
if supply_out_total_kW[5][x] <= 0:
supply_out_total_kW[5][x] = 0
mcp_kWperK[x] = 0
auxiliary_electricity_kW[5][x] = 0
temperature_out[5][x] = 0
temperature_in[5][x] = 0
# update pv cell temperature with temperatures of the water circuit
T_module_mean_C = (temperature_out[5][x] + temperature_in[5][x]) / 2
T_module_C[
x] = T_module_mean_C if T_module_mean_C > 0 else Tcell_PV_C[x]
el_output_PV_kW = np.vectorize(calc_PV_power)(absorbed_radiation_PV_Wperm2,
T_module_C, eff_nom,
module_area_per_group_m2,
Bref, misc_losses)
# write results into a list
result = [
supply_losses_kW[5], supply_out_total_kW[5],
auxiliary_electricity_kW[5], temperature_out[5], temperature_in[5],
mcp_kWperK, el_output_PV_kW
]
return result