def calc_PVT_generation(sensor_groups, weather_data, date_local,
solar_properties, latitude, tot_bui_height_m,
panel_properties_SC, panel_properties_PV, config):
"""
To calculate the heat and electricity generated from PVT panels.
:param sensor_groups: properties of sensors in each group
:type sensor_groups: dict
:param weather_data: weather data read from .epw
:type weather_data: dataframe
:param solar_properties:
:param latitude: latitude of the case study location
:param tot_bui_height_m: total height of all buildings [m]
:param panel_properties_SC: properties of solar thermal collectors
:param panel_properties_PV: properties of photovoltaic panels
:param config: user settings from cea.config
:return:
"""
# read variables
number_groups = sensor_groups[
'number_groups'] # number of groups of sensor points
prop_observers = sensor_groups[
'prop_observers'] # mean values of sensor properties of each group of sensors
hourly_radiation_Wperm2 = sensor_groups[
'hourlydata_groups'] # mean hourly radiation of sensors in each group [Wh/m2]
T_in_C = get_t_in_pvt(config)
# convert degree to radians
lat_rad = radians(latitude)
g_rad = np.radians(solar_properties.g)
ha_rad = np.radians(solar_properties.ha)
Sz_rad = np.radians(solar_properties.Sz)
# calculate equivalent length of pipes
total_area_module_m2 = prop_observers['area_installed_module_m2'].sum(
) # total area for panel installation
total_pipe_lengths = calc_pipe_equivalent_length(panel_properties_PV,
panel_properties_SC,
tot_bui_height_m,
total_area_module_m2)
# empty lists to store results
list_groups_area = [0 for i in range(number_groups)]
total_el_output_PV_kWh = [0 for i in range(number_groups)]
total_radiation_kWh = [0 for i in range(number_groups)]
total_mcp_kWperC = [0 for i in range(number_groups)]
total_qloss_kWh = [0 for i in range(number_groups)]
total_aux_el_kWh = [0 for i in range(number_groups)]
total_Qh_output_kWh = [0 for i in range(number_groups)]
list_results_from_PVT = list(range(number_groups))
potential = pd.DataFrame(index=[range(HOURS_IN_YEAR)])
panel_orientations = [
'walls_south', 'walls_north', 'roofs_top', 'walls_east', 'walls_west'
]
for panel_orientation in panel_orientations:
potential['PVT_' + panel_orientation + '_Q_kWh'] = 0.0
potential['PVT_' + panel_orientation + '_E_kWh'] = 0.0
potential['PVT_' + panel_orientation + '_m2'] = 0.0
# assign default number of subsdivisions for the calculation
if panel_properties_SC['type'] == 'ET': # ET: evacuated tubes
panel_properties_SC[
'Nseg'] = 100 # default number of subsdivisions for the calculation
else:
panel_properties_SC['Nseg'] = 10
for group in range(number_groups):
# read panel properties of each group
teta_z_deg = prop_observers.loc[group, 'surface_azimuth_deg']
module_area_per_group_m2 = prop_observers.loc[
group, 'area_installed_module_m2']
tilt_angle_deg = prop_observers.loc[group,
'B_deg'] # tilt angle of panels
# degree to radians
tilt_rad = radians(tilt_angle_deg) # tilt angle
teta_z_rad = radians(teta_z_deg) # surface azimuth
# calculate radiation types (direct/diffuse) in group
radiation_Wperm2 = solar_equations.cal_radiation_type(
group, hourly_radiation_Wperm2, weather_data)
## calculate absorbed solar irradiation on tilt surfaces
# calculate effective indicent angles necessary
teta_rad = np.vectorize(solar_equations.calc_angle_of_incidence)(
g_rad, lat_rad, ha_rad, tilt_rad, teta_z_rad)
teta_ed_rad, teta_eg_rad = calc_diffuseground_comp(tilt_rad)
# absorbed radiation and Tcell
absorbed_radiation_PV_Wperm2 = np.vectorize(
calc_absorbed_radiation_PV)(radiation_Wperm2.I_sol,
radiation_Wperm2.I_direct,
radiation_Wperm2.I_diffuse, tilt_rad,
Sz_rad, teta_rad, teta_ed_rad,
teta_eg_rad, panel_properties_PV)
T_cell_C = np.vectorize(calc_cell_temperature)(
absorbed_radiation_PV_Wperm2, weather_data.drybulb_C,
panel_properties_PV)
## SC heat generation
# calculate incidence angle modifier for beam radiation
IAM_b = calc_IAM_beam_SC(solar_properties, teta_z_deg, tilt_angle_deg,
panel_properties_SC['type'], latitude)
list_results_from_PVT[group] = calc_PVT_module(
config, radiation_Wperm2, panel_properties_SC, panel_properties_PV,
weather_data.drybulb_C, IAM_b, tilt_angle_deg, total_pipe_lengths,
absorbed_radiation_PV_Wperm2, T_cell_C, module_area_per_group_m2)
# calculate results from each group
panel_orientation = prop_observers.loc[group, 'type_orientation']
number_modules_per_group = module_area_per_group_m2 / (
panel_properties_PV['module_length_m']**2)
PVT_Q_kWh = list_results_from_PVT[group][1] * number_modules_per_group
PVT_E_kWh = list_results_from_PVT[group][6]
# write results
potential['PVT_' + panel_orientation +
'_Q_kWh'] = potential['PVT_' + panel_orientation +
'_Q_kWh'] + PVT_Q_kWh
potential['PVT_' + panel_orientation +
'_E_kWh'] = potential['PVT_' + panel_orientation +
'_E_kWh'] + PVT_E_kWh
potential['PVT_' + panel_orientation +
'_m2'] = potential['PVT_' + panel_orientation +
'_m2'] + module_area_per_group_m2
# aggregate results from all modules
list_groups_area[group] = module_area_per_group_m2
total_mcp_kWperC[
group] = list_results_from_PVT[group][5] * number_modules_per_group
total_qloss_kWh[
group] = list_results_from_PVT[group][0] * number_modules_per_group
total_aux_el_kWh[
group] = list_results_from_PVT[group][2] * number_modules_per_group
total_Qh_output_kWh[
group] = list_results_from_PVT[group][1] * number_modules_per_group
total_el_output_PV_kWh[group] = list_results_from_PVT[group][6]
total_radiation_kWh[group] = hourly_radiation_Wperm2[
group] * module_area_per_group_m2 / 1000
potential['Area_PVT_m2'] = sum(list_groups_area)
potential['radiation_kWh'] = sum(total_radiation_kWh).values
potential['E_PVT_gen_kWh'] = sum(total_el_output_PV_kWh)
potential['Q_PVT_gen_kWh'] = sum(total_Qh_output_kWh)
potential['mcp_PVT_kWperC'] = sum(total_mcp_kWperC)
potential['Eaux_PVT_kWh'] = sum(total_aux_el_kWh)
potential['Q_PVT_l_kWh'] = sum(total_qloss_kWh)
potential['T_PVT_sup_C'] = np.zeros(HOURS_IN_YEAR) + T_in_C
T_out_C = (potential['Q_PVT_gen_kWh'] /
potential['mcp_PVT_kWperC']) + T_in_C
potential[
'T_PVT_re_C'] = T_out_C if T_out_C is not np.nan else np.nan # assume parallel connections for all panels
potential['Date'] = date_local
potential = potential.set_index('Date')
return potential
def calc_pv_generation(sensor_groups, weather_data, date_local, solar_properties, latitude, panel_properties_PV):
"""
To calculate the electricity generated from PV panels.
:param hourly_radiation: mean hourly radiation of sensors in each group [Wh/m2]
:type hourly_radiation: dataframe
:param number_groups: number of groups of sensor points
:type number_groups: float
:param number_points: number of sensor points in each group
:type number_points: float
:param prop_observers: mean values of sensor properties of each group of sensors
:type prop_observers: dataframe
:param weather_data: weather data read from the epw file
:type weather_data: dataframe
:param g: declination
:type g: float
:param Sz: zenith angle
:type Sz: float
:param Az: solar azimuth
:param ha: hour angle
:param latitude: latitude of the case study location
:return:
"""
# local variables
number_groups = sensor_groups['number_groups'] # number of groups of sensor points
prop_observers = sensor_groups['prop_observers'] # mean values of sensor properties of each group of sensors
hourly_radiation = sensor_groups['hourlydata_groups'] # mean hourly radiation of sensors in each group [Wh/m2]
# convert degree to radians
lat = radians(latitude)
g_rad = np.radians(solar_properties.g)
ha_rad = np.radians(solar_properties.ha)
Sz_rad = np.radians(solar_properties.Sz)
Az_rad = np.radians(solar_properties.Az)
# empty list to store results
list_groups_area = [0 for i in range(number_groups)]
total_el_output_PV_kWh = [0 for i in range(number_groups)]
total_radiation_kWh = [0 for i in range(number_groups)]
potential = pd.DataFrame(index=[range(HOURS_IN_YEAR)])
panel_orientations = ['walls_south', 'walls_north', 'roofs_top', 'walls_east', 'walls_west']
for panel_orientation in panel_orientations:
potential['PV_' + panel_orientation + '_E_kWh'] = 0
potential['PV_' + panel_orientation + '_m2'] = 0
eff_nom = panel_properties_PV['PV_n']
Bref = panel_properties_PV['PV_Bref']
misc_losses = panel_properties_PV['misc_losses'] # cabling, resistances etc..
for group in prop_observers.index.values:
# calculate radiation types (direct/diffuse) in group
radiation_Wperm2 = solar_equations.cal_radiation_type(group, hourly_radiation, weather_data)
# read panel properties of each group
teta_z_deg = prop_observers.loc[group, 'surface_azimuth_deg']
tot_module_area_m2 = prop_observers.loc[group, 'area_installed_module_m2']
tilt_angle_deg = prop_observers.loc[group, 'B_deg'] # tilt angle of panels
# degree to radians
tilt_rad = radians(tilt_angle_deg) # tilt angle
teta_z_deg = radians(teta_z_deg) # surface azimuth
# calculate effective indicent angles necessary
teta_rad = np.vectorize(solar_equations.calc_angle_of_incidence)(g_rad, lat, ha_rad, tilt_rad, teta_z_deg)
teta_ed_rad, teta_eg_rad = calc_diffuseground_comp(tilt_rad)
absorbed_radiation_Wperm2 = np.vectorize(calc_absorbed_radiation_PV)(radiation_Wperm2.I_sol,
radiation_Wperm2.I_direct,
radiation_Wperm2.I_diffuse, tilt_rad,
Sz_rad, teta_rad, teta_ed_rad,
teta_eg_rad, panel_properties_PV)
T_cell_C = np.vectorize(calc_cell_temperature)(absorbed_radiation_Wperm2, weather_data.drybulb_C,
panel_properties_PV)
el_output_PV_kW = np.vectorize(calc_PV_power)(absorbed_radiation_Wperm2, T_cell_C, eff_nom, tot_module_area_m2,
Bref, misc_losses)
# write results from each group
panel_orientation = prop_observers.loc[group, 'type_orientation']
potential['PV_' + panel_orientation + '_E_kWh'] = potential[
'PV_' + panel_orientation + '_E_kWh'] + el_output_PV_kW
potential['PV_' + panel_orientation + '_m2'] = potential['PV_' + panel_orientation + '_m2'] + tot_module_area_m2
# aggregate results from all modules
list_groups_area[group] = tot_module_area_m2
total_el_output_PV_kWh[group] = el_output_PV_kW
total_radiation_kWh[group] = (radiation_Wperm2['I_sol'] * tot_module_area_m2 / 1000) # kWh
# check for missing groups and asign 0 as el_output_PV_kW
# panel_orientations = ['walls_south', 'walls_north', 'roofs_top', 'walls_east', 'walls_west']
# for panel_orientation in panel_orientations:
# if panel_orientation not in prop_observers['type_orientation'].values:
# potential['PV_' + panel_orientation + '_E_kWh'] = 0
# potential['PV_' + panel_orientation + '_m2'] = 0
potential['E_PV_gen_kWh'] = sum(total_el_output_PV_kWh)
potential['radiation_kWh'] = sum(total_radiation_kWh).values
potential['Area_PV_m2'] = sum(list_groups_area)
potential['Date'] = date_local
potential = potential.set_index('Date')
return potential
def calc_SC_generation(sensor_groups, weather_data, date_local, solar_properties, tot_bui_height, panel_properties_SC,
latitude_deg, config):
"""
To calculate the heat generated from SC panels.
:param sensor_groups: properties of sensors in each group
:type sensor_groups: dict
:param weather_data: weather data read from the epw file
:type weather_data: dataframe
:param solar_properties:
:param tot_bui_height: total height of all buildings [m]
:param panel_properties_SC: properties of solar panels
:type panel_properties_SC: dataframe
:param latitude_deg: latitude of the case study location
:param config: user settings from cea.config
:return: dataframe
"""
# local variables
number_groups = sensor_groups['number_groups'] # number of groups of sensor points
prop_observers = sensor_groups['prop_observers'] # mean values of sensor properties of each group of sensors
hourly_radiation = sensor_groups['hourlydata_groups'] # mean hourly radiation of sensors in each group [Wh/m2]
T_in_C = get_t_in_sc(config)
Tin_array_C = np.zeros(8760) + T_in_C
# create lists to store results
list_results_from_SC = [0 for i in range(number_groups)]
list_areas_groups = [0 for i in range(number_groups)]
total_radiation_kWh = [0 for i in range(number_groups)]
total_mcp_kWperC = [0 for i in range(number_groups)]
total_qloss_kWh = [0 for i in range(number_groups)]
total_aux_el_kWh = [0 for i in range(number_groups)]
total_Qh_output_kWh = [0 for i in range(number_groups)]
potential = pd.DataFrame(index=[range(8760)])
panel_orientations = ['walls_south', 'walls_north', 'roofs_top', 'walls_east', 'walls_west']
for panel_orientation in panel_orientations:
potential['SC_' + panel_orientation + '_Q_kWh'] = 0
potential['SC_' + panel_orientation + '_m2'] = 0
# calculate equivalent length of pipes
total_area_module_m2 = prop_observers['area_installed_module_m2'].sum() # total area for panel installation
total_pipe_length = cal_pipe_equivalent_length(tot_bui_height, panel_properties_SC, total_area_module_m2)
# assign default number of subsdivisions for the calculation
if panel_properties_SC['type'] == 'ET': # ET: evacuated tubes
panel_properties_SC['Nseg'] = 100 # default number of subsdivisions for the calculation
else:
panel_properties_SC['Nseg'] = 10
for group in range(number_groups):
# calculate radiation types (direct/diffuse) in group
radiation_Wperm2 = solar_equations.cal_radiation_type(group, hourly_radiation, weather_data)
# load panel angles from each group
teta_z_deg = prop_observers.loc[group, 'surface_azimuth_deg'] # azimuth of panels of group
tilt_angle_deg = prop_observers.loc[group, 'B_deg'] # tilt angle of panels
# calculate incidence angle modifier for beam radiation
IAM_b = calc_IAM_beam_SC(solar_properties, teta_z_deg, tilt_angle_deg, panel_properties_SC['type'],
latitude_deg)
# calculate heat production from a solar collector of each group
list_results_from_SC[group] = calc_SC_module(config, radiation_Wperm2, panel_properties_SC,
weather_data.drybulb_C,
IAM_b, tilt_angle_deg, total_pipe_length)
# calculate results from each group
panel_orientation = prop_observers.loc[group, 'type_orientation']
module_area_per_group_m2 = prop_observers.loc[group, 'area_installed_module_m2']
number_modules_per_group = module_area_per_group_m2 / panel_properties_SC['module_area_m2']
SC_Q_kWh = list_results_from_SC[group][1] * number_modules_per_group
potential['SC_' + panel_orientation + '_Q_kWh'] = potential['SC_' + panel_orientation + '_Q_kWh'] + SC_Q_kWh
potential['SC_' + panel_orientation + '_m2'] = potential[
'SC_' + panel_orientation + '_m2'] + module_area_per_group_m2 # assume parallel connections in this group
# aggregate results from all modules
list_areas_groups[group] = module_area_per_group_m2
total_mcp_kWperC[group] = list_results_from_SC[group][5] * number_modules_per_group
total_qloss_kWh[group] = list_results_from_SC[group][0] * number_modules_per_group
total_aux_el_kWh[group] = list_results_from_SC[group][2] * number_modules_per_group
total_Qh_output_kWh[group] = list_results_from_SC[group][1] * number_modules_per_group
total_radiation_kWh[group] = (radiation_Wperm2['I_sol'] * module_area_per_group_m2 / 1000)
potential['Area_SC_m2'] = sum(list_areas_groups)
potential['radiation_kWh'] = sum(total_radiation_kWh)
potential['Q_SC_gen_kWh'] = sum(total_Qh_output_kWh)
potential['mcp_SC_kWperC'] = sum(total_mcp_kWperC)
potential['Eaux_SC_kWh'] = sum(total_aux_el_kWh)
potential['Q_SC_l_kWh'] = sum(total_qloss_kWh)
potential['T_SC_sup_C'] = Tin_array_C
T_out_C = (potential['Q_SC_gen_kWh'] / potential['mcp_SC_kWperC']) + T_in_C
potential[
'T_SC_re_C'] = T_out_C if T_out_C is not np.nan else np.nan # assume parallel connections for all panels #FIXME: change here when the flow rate is zero
potential['Date'] = date_local
potential = potential.set_index('Date')
return potential
