def evaluate(self, x):
light_source = LightSource(source_type='standard', version='AM1.5g')
wl = np.linspace(300, 1850, 500) * 1e-9
solar_cell = self.make_cell(x)
position = [1e-10] * 10 + [5e-8]
V = np.linspace(0, 3.5, 300)
solar_cell_solver(solar_cell,
'iv',
user_options={
'voltages': V,
'light_iv': True,
'wavelength': wl,
'mpp': True,
'light_source': light_source,
'optics_method': 'TMM',
'BL_correction': True,
'position': position
})
efficiency = solar_cell.iv["Eta"]
# print('Efficiency =', efficiency)
return -efficiency
def test_light_iv(AlGaAs, light_source):
import numpy as np
from solcore.solar_cell import SolarCell, default_GaAs
from solcore import material
from solcore.solar_cell_solver import solar_cell_solver
expected = np.array([
142.68025180227374,
2.519346556870366,
0.9169672186977382,
329.61395441947565,
2.347826086956522,
140.3911287342211,
0.3294918264376029,
])
T = AlGaAs.T
Vin = np.linspace(-2, 2.61, 201)
V = np.linspace(0, 2.6, 300)
substrate = material("GaAs")(T=T)
my_solar_cell = SolarCell([AlGaAs, default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(
my_solar_cell,
"iv",
user_options={
"T_ambient": T,
"db_mode": "boltzmann",
"voltages": V,
"light_iv": True,
"wavelength": light_source.x,
"optics_method": "BL",
"mpp": True,
"internal_voltages": Vin,
"light_source": light_source,
},
)
output = [
my_solar_cell.iv.Isc,
my_solar_cell.iv.Voc,
my_solar_cell.iv.FF,
my_solar_cell.iv.Pmpp,
my_solar_cell.iv.Vmpp,
my_solar_cell.iv.Impp,
my_solar_cell.iv.Eta,
]
assert np.array(output) == approx(expected, rel=1e-2)
def solve_MJ(EgBot, EgMid, EgTop):
db_junction0 = Junction(kind='DB', T=T, Eg=EgBot, A=1, R_shunt=np.inf, n=3.5)
db_junction1 = Junction(kind='DB', T=T, Eg=EgMid, A=1, R_shunt=np.inf, n=3.5)
db_junction2 = Junction(kind='DB', T=T, Eg=EgTop, A=1, R_shunt=np.inf, n=3.5)
my_solar_cell = SolarCell([db_junction2, db_junction1, db_junction0], T=T, R_series=0)
solar_cell_solver(my_solar_cell, 'iv',
user_options={'T_ambient': T, 'db_mode': 'top_hat', 'voltages': V, 'light_iv': True,
'internal_voltages': np.linspace(-6, 5, 1100), 'wavelength': wl,
'mpp': True, 'light_source': light})
return my_solar_cell
def test_light_iv():
answer = [
142.68025180227374,
2.519346556870366,
0.9169672186977382,
329.61395441947565,
2.347826086956522,
140.3911287342211,
0.3294918264376029,
]
with tempfile.TemporaryDirectory(prefix="tmp",
suffix="_sc3TESTS") as working_directory:
filename = os.path.join(working_directory, "solcore_log.txt")
PDD.log(filename)
my_solar_cell = SolarCell([AlGaAs(T), default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(
my_solar_cell,
"iv",
user_options={
"T_ambient": T,
"db_mode": "boltzmann",
"voltages": V,
"light_iv": True,
"wavelength": wl,
"optics_method": "BL",
"mpp": True,
"internal_voltages": Vin,
"light_source": light_source,
},
)
output = [
my_solar_cell.iv.Isc,
my_solar_cell.iv.Voc,
my_solar_cell.iv.FF,
my_solar_cell.iv.Pmpp,
my_solar_cell.iv.Vmpp,
my_solar_cell.iv.Impp,
my_solar_cell.iv.Eta,
]
for i in range(len(output)):
assert output[i] == approx(answer[i])
def test_quantum_efficiency(AlGaAs, light_source):
import numpy as np
from solcore.solar_cell import SolarCell, default_GaAs
from solcore import material
from solcore.solar_cell_solver import solar_cell_solver
expected = np.array([
0.9866334968497021,
2.1512408472022467e-14,
0.9779769012349702,
0.03506561338387434,
])
T = AlGaAs.T
Vin = np.linspace(-2, 2.61, 201)
V = np.linspace(0, 2.6, 300)
substrate = material("GaAs")(T=T)
my_solar_cell = SolarCell([AlGaAs, default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(
my_solar_cell,
"qe",
user_options={
"T_ambient": T,
"db_mode": "boltzmann",
"voltages": V,
"light_iv": True,
"wavelength": light_source.x,
"optics_method": "BL",
"mpp": True,
"internal_voltages": Vin,
"light_source": light_source,
},
)
output = [
my_solar_cell[0].eqe(500e-9),
my_solar_cell[0].eqe(800e-9),
my_solar_cell[1].eqe(700e-9),
my_solar_cell[1].eqe(900e-9),
]
assert np.array(output) == approx(expected, abs=1e-3)
def test_substrate_presence_profile():
wavelength = np.linspace(300, 800, 3) * 1e-9
GaAs = material("GaAs")(T=300)
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)],
substrate=GaAs)
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflection": False,
},
)
z_pos = np.linspace(0, my_structure.width, 10)
profile_subs = my_structure[0].absorbed(z_pos)
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)])
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflection": False,
},
)
profile_nosubs = my_structure[0].absorbed(z_pos)
profile = np.vstack((profile_subs, profile_nosubs))
data_path = Path(
__file__).parent / "data" / "substrate_presence_profile.csv"
expected = np.loadtxt(data_path, delimiter=",")
assert profile.shape == expected.shape
assert profile == approx(expected)
def test_substrate_presence_A():
wavelength = np.linspace(300, 800, 3) * 1e-9
GaAs = material("GaAs")(T=300)
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)],
substrate=GaAs)
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflexion": False,
},
)
z_pos = np.linspace(0, my_structure.width, 10)
A_subs = my_structure[0].layer_absorption
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)])
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflexion": False,
},
)
A_nosubs = my_structure[0].layer_absorption
A = np.vstack((A_subs, A_nosubs))
A_data = np.array([[0.56610281, 0.62692985, 0.41923175],
[0.56610281, 0.62711355, 0.37837737]])
assert all([d == approx(o) for d, o in zip(A, A_data)])
def test_quantum_efficiency():
answer = [
0.9866334968497021,
2.1512408472022467e-14,
0.9779769012349702,
0.03506561338387434,
]
with tempfile.TemporaryDirectory(prefix="tmp",
suffix="_sc3TESTS") as working_directory:
filename = os.path.join(working_directory, "solcore_log.txt")
PDD.log(filename)
my_solar_cell = SolarCell([AlGaAs(T), default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(
my_solar_cell,
"qe",
user_options={
"T_ambient": T,
"db_mode": "boltzmann",
"voltages": V,
"light_iv": True,
"wavelength": wl,
"optics_method": "BL",
"mpp": True,
"internal_voltages": Vin,
"light_source": light_source,
},
)
output = [
my_solar_cell[0].eqe(500e-9),
my_solar_cell[0].eqe(800e-9),
my_solar_cell[1].eqe(700e-9),
my_solar_cell[1].eqe(900e-9),
]
for i in range(len(output)):
assert output[i] == approx(answer[i])
def test_inc_coh_tmm():
GaInP = material("GaInP")(In=0.5)
GaAs = material("GaAs")()
Ge = material("Ge")()
optical_struct = SolarCell([
Layer(material=GaInP, width=si("5000nm")),
Layer(material=GaAs, width=si("200nm")),
Layer(material=GaAs, width=si("5um")),
Layer(material=Ge, width=si("50um")),
])
wl = np.linspace(400, 1200, 5) * 1e-9
options = State()
options.wavelength = wl
options.optics_method = "TMM"
options.no_back_reflection = False
options.BL_correction = True
options.recalculate_absorption = True
c_list = [
["c", "c", "c", "c"],
["c", "c", "c", "i"],
["c", "i", "i", "c"],
["i", "i", "i", "i"],
]
results = []
for i1, cl in enumerate(c_list):
options.coherency_list = cl
solar_cell_solver(optical_struct, "optics", options)
results.append(optical_struct.absorbed)
A_calc = np.stack(results)
A_data = np.array(
[[0.5742503, 0.67956899, 0.73481184, 0.725372, 0.76792856],
[0.5742503, 0.67956899, 0.73481184, 0.725372, 0.76792856],
[0.5742503, 0.67956899, 0.73474943, 0.70493469, 0.70361194],
[0.5742503, 0.67956899, 0.70927724, 0.71509221, 0.71592772]])
assert A_calc == approx(A_data)
def solve_MJ(EgBot, EgMid, EgTop):
db_junction0 = Junction(kind="DB",
T=T,
Eg=EgBot,
A=1,
R_shunt=np.inf,
n=3.5)
db_junction1 = Junction(kind="DB",
T=T,
Eg=EgMid,
A=1,
R_shunt=np.inf,
n=3.5)
db_junction2 = Junction(kind="DB",
T=T,
Eg=EgTop,
A=1,
R_shunt=np.inf,
n=3.5)
my_solar_cell = SolarCell([db_junction2, db_junction1, db_junction0],
T=T,
R_series=0)
solar_cell_solver(
my_solar_cell,
"iv",
user_options={
"T_ambient": T,
"db_mode": "top_hat",
"voltages": V,
"light_iv": True,
"internal_voltages": np.linspace(-6, 5, 1100),
"wavelength": wl,
"mpp": True,
"light_source": light,
},
)
return my_solar_cell
def test_92_light_iv(self):
answer = [
142.68025180227374, 2.519346556870366, 0.9169672186977382,
329.61395441947565, 2.347826086956522, 140.3911287342211,
0.3294918264376029
]
with tempfile.TemporaryDirectory(
prefix="tmp", suffix="_sc3TESTS") as working_directory:
filename = os.path.join(working_directory, 'solcore_log.txt')
PDD.log(filename)
my_solar_cell = SolarCell([AlGaAs(T), default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(my_solar_cell,
'iv',
user_options={
'T_ambient': T,
'db_mode': 'boltzmann',
'voltages': V,
'light_iv': True,
'wavelength': wl,
'optics_method': 'BL',
'mpp': True,
'internal_voltages': Vin,
'light_source': light_source
})
output = [
my_solar_cell.iv.Isc, my_solar_cell.iv.Voc,
my_solar_cell.iv.FF, my_solar_cell.iv.Pmpp,
my_solar_cell.iv.Vmpp, my_solar_cell.iv.Impp,
my_solar_cell.iv.Eta
]
for i in range(len(output)):
self.assertAlmostEqual(output[i], answer[i])
def test_92_light_iv(self):
answer = [
141.434980729, 2.46952886616, 0.91434377329, 319.359951949,
2.29565217391, 139.115130584, 0.319241623262
]
with tempfile.TemporaryDirectory(
prefix="tmp", suffix="_sc3TESTS") as working_directory:
filename = os.path.join(working_directory, 'solcore_log.txt')
PDD.log(filename)
my_solar_cell = SolarCell([AlGaAs(T), default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(my_solar_cell,
'iv',
user_options={
'T_ambient': T,
'db_mode': 'boltzmann',
'voltages': V,
'light_iv': True,
'wavelength': wl,
'optics_method': 'BL',
'mpp': True,
'internal_voltages': Vin,
'light_source': light_source
})
output = [
my_solar_cell.iv.Isc, my_solar_cell.iv.Voc,
my_solar_cell.iv.FF, my_solar_cell.iv.Pmpp,
my_solar_cell.iv.Vmpp, my_solar_cell.iv.Impp,
my_solar_cell.iv.Eta
]
for i in range(len(output)):
self.assertAlmostEqual(output[i], answer[i])
def test_93_qe(self):
answer = [
0.9866334968497021, 2.1512408472022467e-14, 0.9779769012349702,
0.03506561338387434
]
with tempfile.TemporaryDirectory(
prefix="tmp", suffix="_sc3TESTS") as working_directory:
filename = os.path.join(working_directory, 'solcore_log.txt')
PDD.log(filename)
my_solar_cell = SolarCell([AlGaAs(T), default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(my_solar_cell,
'qe',
user_options={
'T_ambient': T,
'db_mode': 'boltzmann',
'voltages': V,
'light_iv': True,
'wavelength': wl,
'optics_method': 'BL',
'mpp': True,
'internal_voltages': Vin,
'light_source': light_source
})
output = [
my_solar_cell[0].eqe(500e-9), my_solar_cell[0].eqe(800e-9),
my_solar_cell[1].eqe(700e-9), my_solar_cell[1].eqe(900e-9)
]
for i in range(len(output)):
self.assertAlmostEqual(output[i], answer[i])
def test_93_qe(self):
answer = [
0.9831923128532823, 1.315965183418519e-13, 0.9672990699170962,
0.032767290395462376
]
with tempfile.TemporaryDirectory(
prefix="tmp", suffix="_sc3TESTS") as working_directory:
filename = os.path.join(working_directory, 'solcore_log.txt')
PDD.log(filename)
my_solar_cell = SolarCell([AlGaAs(T), default_GaAs(T)],
T=T,
R_series=0,
substrate=substrate)
solar_cell_solver(my_solar_cell,
'qe',
user_options={
'T_ambient': T,
'db_mode': 'boltzmann',
'voltages': V,
'light_iv': True,
'wavelength': wl,
'optics_method': 'BL',
'mpp': True,
'internal_voltages': Vin,
'light_source': light_source
})
output = [
my_solar_cell[0].eqe(500e-9), my_solar_cell[0].eqe(800e-9),
my_solar_cell[1].eqe(700e-9), my_solar_cell[1].eqe(900e-9)
]
for i in range(len(output)):
self.assertAlmostEqual(output[i], answer[i])
GaAs = material('GaAs')(T=T)
thin_GaAs = SolarCell([Layer(material=GaAs, width=si('500nm'))])
GaAs_on_substrate = SolarCell([Layer(material=GaAs, width=si('500nm'))],
substrate=GaAs)
wl = si(np.linspace(300, 900, 200), 'nm')
# Thin solar cell, no substrate - will get significant absorption enhancement from reflection at the GaAs/air interface at the back
# MUST specify no_back_reflection = False, so that Solcore does not automatically suppress reflections from the back
# (currently, the default setting in solcore is to suppress reflections from the back, so no_back_reflection = True
solar_cell_solver(thin_GaAs,
'optics',
user_options={
'wavelength': wl,
'optics_method': 'TMM',
'no_back_reflection': False
})
z_pos = np.linspace(0, thin_GaAs.width, 201)
profiles_thin = thin_GaAs[0].absorbed(z_pos)
# Same thin solar cell, but now on a GaAs substrate. In this case, we get the same result whether or not we specify
# no_back_reflection to be True or False, since with a GaAs on GaAs cell we don't get any reflection at the back interface anyway
solar_cell_solver(GaAs_on_substrate,
'optics',
user_options={
'wavelength': wl,
'optics_method': 'TMM'
})
profiles_thick = GaAs_on_substrate[0].absorbed(z_pos)
solar_cell = SolarCell(
[
Junction([Layer(si("25nm"), material=window_material, role='window'),
Layer(si("100nm"), material=top_cell_n_material, role='emitter'),
Layer(si("600nm"), material=top_cell_p_material, role='base'),
], sn=1, sp=1, kind='DA'),
Junction([Layer(si("200nm"), material=mid_cell_n_material, role='emitter'),
Layer(si("3000nm"), material=mid_cell_p_material, role='base'),
], sn=1, sp=1, kind='DA'),
Junction([Layer(si("400nm"), material=bot_cell_n_material, role='emitter'),
Layer(si("100um"), material=bot_cell_p_material, role='base'),
], sn=1, sp=1, kind='DA'),
], reflectivity=ref, shading=0.08, cell_area=0.7 * 0.7 / 1e4)
wl = np.linspace(300, 1800, 700) * 1e-9
solar_cell_solver(solar_cell, 'qe', user_options={'wavelength': wl})
plt.figure(1)
plt.plot(wl * 1e9, solar_cell[0].eqe(wl) * 100, 'b', label='GaInP')
plt.plot(wl * 1e9, solar_cell[1].eqe(wl) * 100, 'g', label='InGaAs')
plt.plot(wl * 1e9, solar_cell[2].eqe(wl) * 100, 'r', label='Ge')
plt.legend()
plt.ylim(0, 100)
plt.ylabel('EQE (%)')
plt.xlabel('Wavelength (nm)')
V = np.linspace(0, 3, 300)
solar_cell_solver(solar_cell, 'iv', user_options={'voltages': V, 'light_iv': True, 'wavelength': wl})
plt.figure(2)
V = np.linspace(0, 2.6, 300)
wl = np.linspace(350, 1000, 301) * 1e-9
light_source = LightSource(source_type='standard',
version='AM1.5g',
x=wl,
output_units='photon_flux_per_m',
concentration=1)
# We calculate the IV curve under illumination
solar_cell_solver(my_solar_cell,
'iv',
user_options={
'T_ambient': T,
'db_mode': 'boltzmann',
'voltages': V,
'light_iv': True,
'wavelength': wl,
'optics_method': 'BL',
'mpp': True,
'internal_voltages': Vin,
'light_source': light_source
})
# We can plot the electron and hole densities in equilibrium and at short circuit, both calculated automatically
# before calculating the IV curve
plt.figure(1)
for j in my_solar_cell.junction_indices:
zz = my_solar_cell[j].short_circuit_data.Bandstructure[
'x'] + my_solar_cell[j].offset
n = my_solar_cell[j].short_circuit_data.Bandstructure['n']
p = my_solar_cell[j].short_circuit_data.Bandstructure['p']
["c", "c", "c", "i"],
["c", "i", "i", "c"],
["i", "i", "i", "i"],
]
titles = [
"All coherent",
"Bottom Ge layer explicity incoherent",
"Both layers of GaAs junction incoherent",
"All layers incoherent",
]
for i1, cl in enumerate(c_list):
plt.figure(i1)
options.coherency_list = cl
solar_cell_solver(optical_struct, "optics", options)
plt.plot(wl * 1e9, optical_struct[0].layer_absorption)
plt.plot(wl * 1e9, optical_struct[1].layer_absorption)
plt.plot(wl * 1e9, optical_struct[2].layer_absorption)
plt.plot(wl * 1e9, optical_struct.reflected, "--")
plt.plot(wl * 1e9, optical_struct.transmitted, "--")
plt.plot(
wl * 1e9,
optical_struct[0].layer_absorption +
optical_struct[1].layer_absorption +
optical_struct[2].layer_absorption + optical_struct.reflected +
optical_struct.transmitted,
)
plt.legend(["GaInP", "GaAs", "Ge", "R", "T", "R+A+T"], loc="upper left")
plt.title(titles[i1])
plt.xlabel("Wavelength (nm)")
def plot(self, x):
light_source = LightSource(source_type='standard', version='AM1.5g')
wl = np.linspace(300, 1850, 500) * 1e-9
solar_cell = self.make_cell(x)
position = [1e-10] * 10 + [5e-8]
V = np.linspace(0, 3.5, 300)
solar_cell_solver(solar_cell,
'iv',
user_options={
'voltages': V,
'light_iv': True,
'wavelength': wl,
'mpp': True,
'light_source': light_source,
'optics_method': 'TMM',
'BL_correction': True,
'position': position
})
efficiency = solar_cell.iv["Eta"]
pmax = solar_cell.iv["Pmpp"]
ff = solar_cell.iv["FF"]
voc = solar_cell.iv["Voc"]
isc = solar_cell.iv["Isc"]
plt.figure()
plt.plot(V,
solar_cell.iv['IV'][1] / 10,
'k',
linewidth=3,
label='Total')
plt.plot(V, -solar_cell[2].iv(V) / 10, 'b', label='GaInP')
plt.plot(V, -solar_cell[3].iv(V) / 10, 'g', label='GaAs')
plt.plot(V, -solar_cell[4].iv(V) / 10, 'r', label='SiGeSn')
plt.plot(V, -solar_cell[5].iv(V) / 10, 'y', label='Ge')
plt.text(2, 10, '$\eta = $' + str(round(efficiency * 100, 1)) + '%')
plt.text(2, 8, 'Pmax=' + str(round(pmax, 1)) + 'W/m$^2$')
plt.text(2, 9, 'FF = ' + str(round(ff * 100, 1)) + '%')
plt.text(2, 7, 'Voc=' + str(round(voc, 1)) + 'V')
plt.text(2, 6, 'Jsc=' + str(round(0.1 * isc, 1)) + 'mA/cm$^2$')
plt.legend()
plt.ylim(0, 18)
plt.xlim(0, 3.5)
plt.ylabel('Current (mA/cm$^2$)')
plt.xlabel('Voltage (V)')
plt.show()
# print('Efficiency =', efficiency)
solar_cell_solver(solar_cell,
'qe',
user_options={
'wavelength': wl,
'optics_method': 'TMM',
'BL_correction': True,
'position': position
})
plt.figure()
plt.plot(wl * 1e9, solar_cell[2].eqe(wl) * 100, 'b', label='InGaP')
plt.plot(wl * 1e9, solar_cell[3].eqe(wl) * 100, 'g', label='InGaAs')
plt.plot(wl * 1e9, solar_cell[4].eqe(wl) * 100, 'r', label='SiGeSn')
plt.plot(wl * 1e9, solar_cell[5].eqe(wl) * 100, 'y', label='Ge')
plt.plot(wl * 1e9,
solar_cell.absorbed * 100,
'k--',
label='Absorption')
# plt.plot(wl * 1e9, solar_cell[5].eqe(wl)*100, 'y', label='Ge')
plt.legend(loc='upper right')
plt.xlim(290, 1850)
plt.ylim(0, 100)
plt.ylabel('EQE (%)')
plt.xlabel('Wavelength (nm)')
plt.show()
plt.show()
# Compare performance as a back mirror on a GaAs 'cell'
# Solid line: absorption in GaAs
# Dashed line: absorption in Ag
GaAs = material('GaAs')()
colors = ['b', 'r', 'k', 'm', 'y']
plt.figure()
for c, Ag_mat in enumerate([Ag_Joh, Ag_McP, Ag_Hag, Ag_Rak, Ag_Sol]):
my_solar_cell = SolarCell([Layer(width=si('50nm'), material=GaAs)] +
[Layer(width=si('100nm'), material=Ag_mat)])
solar_cell_solver(my_solar_cell, 'optics', opts)
GaAs_positions = np.linspace(
my_solar_cell[0].offset,
my_solar_cell[0].offset + my_solar_cell[0].width, 1000)
Ag_positions = np.linspace(
my_solar_cell[1].offset,
my_solar_cell[1].offset + my_solar_cell[1].width, 1000)
GaAs_abs = np.trapz(my_solar_cell[0].diff_absorption(GaAs_positions),
GaAs_positions)
Ag_abs = np.trapz(my_solar_cell[1].diff_absorption(Ag_positions),
Ag_positions)
plt.plot(wl * 1e9,
GaAs_abs,
color=colors[c],
linestyle='-',
label=names[c])
light_source = LightSource(
source_type="standard",
version="AM1.5g",
x=wl,
output_units="photon_flux_per_m",
concentration=1,
)
# The definitions are all done, so we just start solving the properties,
# starting with the QE. We calculate the QE curve under illumination
solar_cell_solver(
my_solar_cell,
"qe",
user_options={
"light_source": light_source,
"wavelength": wl,
"optics_method": "TMM",
},
)
# And now, the IV curves under various concentration levels.
# NOTE: Due to the presence of QWs and the fact we calculate things a 19 different
# concentrations, this might take a while (~4 hours).
# Remove the QWs as indicated above to test the code much faster.
num_con = 19
con = np.logspace(0, 3, num_con)
vint = np.linspace(-3.5, 4, 600)
V = np.linspace(-3.5, 0, 300)
A=1,
R_shunt=np.inf,
n=3.5)
my_solar_cell = SolarCell([db_junction3, db_junction2, db_junction],
T=T,
R_series=0)
solar_cell_solver(my_solar_cell,
'iv',
user_options={
'T_ambient': T,
'db_mode': 'boltzmann',
'voltages': V,
'light_iv': True,
'wavelength': wl,
'optics_method': 'BL',
'light_source': light_source,
'position': z,
'radiative_coupling': rad,
'mpp': True,
'internal_voltages': Vin
})
# This is the total junction IV
ax[k].plot(my_solar_cell.iv['IV'][0],
my_solar_cell.iv['IV'][1],
marker='o',
color=colours("Black"),
ls='-',
markerfacecolor='none',
# setting kind = 'DA' in the Junction definition tells the electrical solver later to use the depletion approximation
optical_struct = SolarCell(ARC + top_junction + middle_junction + DBRa + DBRb +
DBRc + bottom_junction,
shading=0.05)
wl = np.linspace(250, 1700, 400) * 1e-9
options = State()
options.wavelength = wl
options.optics_method = 'TMM'
options.no_back_reflection = False
options.pol = 'p'
options.BL_correction = True
options.coherency_list = 111 * ['c']
options.theta = 30
solar_cell_solver(optical_struct, 'qe', options)
plt.figure()
plt.plot(
wl * 1e9,
optical_struct[0].layer_absorption + optical_struct[1].layer_absorption)
plt.plot(wl * 1e9, optical_struct[2].layer_absorption)
plt.plot(wl * 1e9, optical_struct[3].layer_absorption)
plt.plot(wl * 1e9, optical_struct[100].layer_absorption)
plt.plot(wl * 1e9, optical_struct.absorbed, '--')
plt.plot(wl * 1e9, optical_struct.transmitted, '--')
plt.plot(wl * 1e9, optical_struct.reflected, '--')
plt.legend(['ARC', 'top', 'middle', 'bottom', 'A', 'T', 'R'])
plt.ylim(0, 1)
plt.ylabel('Absorption/Transmission/Reflection')
plt.xlabel('Wavelength (nm)')
T=T,
substrate=n_GaAs)
light_source = LightSource(source_type='standard',
version='AM1.5g',
x=wl,
output_units='photon_flux_per_m',
concentration=1)
# The definitions are all done, so we just start solving the properties, starting with the QE.
# We calculate the QE curve under illumination
solar_cell_solver(my_solar_cell,
'qe',
user_options={
'light_source': light_source,
'wavelength': wl,
'optics_method': 'TMM'
})
# And now, the IV curves under various concentration levels.
# NOTE: Due to the presence of QWs and the fact we calculate things a 19 different concentrations, this might take a
# while (~4 hours). Remove the QWs as indicated above to test the code much faster.
num_con = 3
con = np.logspace(0, 3, num_con)
vint = np.linspace(-3.5, 4, 600)
V = np.linspace(-3.5, 0, 300)
allI = []
isc = []
Air,
geometry=[{
'type': 'circle',
'mat': TiO2,
'center': (200, 200),
'radius': 50
}])
]
substrate = [Layer(width=si('50um'), material=GaAs)]
spacer = [Layer(width=si('25nm'), material=SiO2)]
solar_cell = SolarCell(spacer + GaAs_junction +
substrate) # solar cell with SiO2 coating
opts.optics_method = 'TMM'
solar_cell_solver(solar_cell, 'qe', opts)
TMM_EQE = solar_cell[1].eqe(opts.wavelength)
opts.optics_method = 'BL'
solar_cell_solver(solar_cell, 'qe', opts)
BL_EQE = solar_cell[1].eqe(opts.wavelength)
solar_cell = SolarCell(spacer + GaAs_junction + DBR +
substrate) # as above, with a DBR on the back
opts.optics_method = 'TMM'
solar_cell_solver(solar_cell, 'qe', opts)
TMM_EQE_DBR = solar_cell[1].eqe(opts.wavelength)
solar_cell = SolarCell(NP_layer + spacer + GaAs_junction + DBR + substrate)
# cell with TiO2 nanocylinder array on the front
opts.optics_method = 'RCWA'
opts.orders = 49 # number of diffraction orders to keep in the RCWA solver
color = ['b', 'g', 'r']
label = ['Top', 'Mid', 'Bot']
fig, ax = plt.subplots(1, 2, sharey='all', figsize=(7, 4.5))
for k, rad in enumerate([False, True]):
# Input data for the 2D kind of junction
db_junction = Junction(kind='2D', T=T, reff=0.3, jref=300, Eg=0.66, A=1, R_shunt=np.inf, n=3.5)
db_junction2 = Junction(kind='2D', T=T, reff=1, jref=300, Eg=1.4, A=1, R_shunt=np.inf, n=3.5)
db_junction3 = Junction(kind='2D', T=T, reff=1, jref=300, Eg=1.8, A=1, R_shunt=np.inf, n=3.5)
my_solar_cell = SolarCell([db_junction3, db_junction2, db_junction], T=T, R_series=0)
solar_cell_solver(my_solar_cell, 'iv',
user_options={'T_ambient': T, 'voltages': V, 'light_iv': True, 'wavelength': wl,
'light_source': light_source, 'radiative_coupling': rad, 'mpp': True,
'internal_voltages': Vin})
# This is the total junction IV
ax[k].plot(my_solar_cell.iv['IV'][0], my_solar_cell.iv['IV'][1], marker='o', color=colours("Black"), ls='-',
markerfacecolor='none', markeredgecolor=colours("Black"))
# This is the junciton IV when it is in the MJ device, including coupling if it is enabled.
for i, data in enumerate(my_solar_cell.iv['junction IV']):
ax[k].plot(data[0], data[1], color[i] + '--', linewidth=2)
# This is the junction IV as if it were an isolated device and therefore not affected by coupling or current limiting.
for i in range(my_solar_cell.junctions):
ax[k].plot(V, -my_solar_cell(i).iv(V), color[i], linewidth=2, label=label[i])
ax[k].set_ylim(0, 300)
],
sn=1,
sp=1,
kind='DA'),
])
total_width = ARC_width + n_material_width + p_material_width
options = default_options
options.optics_method = "TMM"
options.wavelength = wavelengths_optics
# options.position = np.linspace(0, total_width, 100000)
options.light_iv = True
V = np.linspace(0, 1.2, 200)
solar_cell_solver(solar_cell, 'iv', options)
reflected = solar_cell.reflected
absorbed_in_Si = solar_cell[1].layer_absorption
interp_ref = interp1d(options.wavelength, reflected)
interp_totalA = interp1d(options.wavelength, solar_cell[1].layer_absorption)
wavelengths_external = np.linspace(301, 1199, 800) * 1e-9
alpha = n_material.alpha(wavelengths_external)
A_layer = interp_totalA(wavelengths_external)
junction_width = n_material_width + p_material_width
def run_solar_cell_model(task, model):
"""
:param model:
:return: a Solar cell object
"""
# First, we take care of the options
# ----------------------------------
options = copy.copy(model['Global'])
options.update(model['Electrical'])
options.update(model['Optical'])
T = float(options['T'])
# We have to validate the options and check they have the correct format and type
array_based_options = ['voltages', 'internal_voltages', 'position', 'wavelength']
float_options = ['T', 'T_ambient']
bool_options = ['mpp', 'light_iv', 'radiative_coupling']
try:
for p in options:
# For the options that should be arrays, we create the arrays. The wavelength need ot be converted to meters
if p in array_based_options:
c = options[p].split(', ')
ini = float(c[0])
end = float(c[1])
num = int(c[2])
options[p] = np.linspace(ini, end, num) * 1e-9 ** (p == 'wavelength')
# For the options that need to be floats
elif p in float_options:
options[p] = float(options[p])
elif p in bool_options:
options[p] = options[p].lower() in ['true', 'yes', 't', 1]
except Exception as err:
print('ERROR parsing the solver options: Option format not recognised')
print(err)
raise
# Now we create the layers and junctions to the solar cell object
# ---------------------------------------------------------------
sc_data = model['Solar cell']
all_layers = []
all_materials = []
for i in sc_data['structure']:
current_element = sc_data[i[0]]
# First the individual layers
if 'Layer' in current_element['type']:
layer_properties = {}
width = current_element['width'] * 1e-9
# Set the composition and get the properties, converting them to the correct units
for key in current_element['options']:
if key in ['element', 'x']:
layer_properties[current_element['options']['element']] = current_element['options']['x']
else:
layer_properties[key] = current_element['options'][key] * conversion[key]
all_materials.append(material(current_element['material'])(T=T, **layer_properties))
all_layers.append(Layer(width, all_materials[-1], role=current_element['name']))
continue
# Unless it is an individual layer, we have junctions
properties = {}
for p in properties_junctions[current_element['type']]:
properties[p] = default_junction_properties[p]
properties.update(**current_element['options'])
kind = current_element['type'].split('-')[-1]
if 'TJ' in current_element['type']:
new_junction = TunnelJunction(name=current_element['name'], kind=kind, T=T, **properties)
else:
new_junction = Junction(name=current_element['name'], kind=kind, T=T, **properties)
# Now we add the layers, if any
for l in i[1:]:
current_child = sc_data[l]
width = current_child['width'] * 1e-9
layer_properties = {}
# Set the composition and get the properties, converting them to the correct units
for key in current_child['options']:
if key in ['element', 'x']:
layer_properties[current_child['options']['element']] = current_child['options']['x']
else:
layer_properties[key] = current_child['options'][key] * conversion[key]
all_materials.append(material(current_child['material'])(T=T, **layer_properties))
new_junction.append(Layer(width, all_materials[-1], role=current_child['name']))
all_layers.append(new_junction)
# Now we have to create the solar cell
# ------------------------------------
reflectivity = create_reflectivity(sc_data['reflectivity']) if sc_data['reflectivity'] != '' else None
try:
substrate = material(sc_data['substrate'])(T=T, **{sc_data['element']: sc_data['composition']})
except KeyError:
substrate = material(sc_data['substrate'])(T=T)
sc = SolarCell(layers=all_layers, name=sc_data['name'], substrate=substrate, T=T, cell_area=sc_data['size'],
shading=sc_data['shading'], R_series=sc_data['r_series'], reflectivity=reflectivity)
# With all said and done, we can run the solver
# ---------------------------------------------
solar_cell_solver(sc, task, user_options=options)
print('Done!')
return sc
def solve_quasi_3D(solar_cell,
injection,
contacts,
options=None,
Lx=10e-6,
Ly=10e-6,
h=2e-6,
R_back=1e-16,
R_contact=1e-16,
R_line=1e-16,
bias_start=0,
bias_end=1.8,
bias_step=0.01):
""" Entry function for the quasi-3D solver
:param solar_cell: A solar cell object
:param injection: 2D array indicating the (optical) injection mask
:param contacts: 2D array indicating the electrical contacts
:param options: Options for the 1D solar cell solver
:param Lx: Pixel size in the X direction
:param Ly: Pixel size in the Y direction
:param h: Height of the metal fingers
:param R_back: Resistance back contact
:param R_contact: Contact resistance
:param R_line: Resistivity metal fingers
:param bias_start: Initial voltage (V)
:param bias_end: Final voltage (V)
:param bias_step: Voltage step (V)
:return: A tuple with:
- V [steps + 1] : 1D Array with the external voltages
- I [steps + 1] : 1D Array with the current at all external V
- Vall [xnodes, ynodes, 2 * junctions, steps + 1] : 4D Array with the voltages in all nodes, at all external V
- Vmet [xnodes, ynodes, steps + 1] : 3D Array with the voltages in the metal nodes, at all external V
"""
# We first start by the solar cell as if it were a normal, isolated cell
print("Solving 1D Solar Cell...")
solar_cell_solver(solar_cell, 'iv', user_options=options)
print("... Done!\n")
# We don't care about this IV curve, in principle, but we care about some of the parameters calculated, like jsc,
# j01 or j02 if calculated from detailed balance. We extract those parameters from the cell
totaljuncs = solar_cell.junctions
Isc_array = np.zeros(totaljuncs)
I01_array = np.zeros(totaljuncs)
n1_array = np.zeros(totaljuncs)
I02_array = np.zeros(totaljuncs)
n2_array = np.zeros(totaljuncs)
Eg_array = np.zeros(totaljuncs)
rsh_array = np.zeros(totaljuncs)
rshTop_array = np.zeros(totaljuncs)
rshBot_array = np.zeros(totaljuncs)
rseries_array = np.ones(totaljuncs) * 1e-16
for i in range(totaljuncs):
n1_array[i] = solar_cell(i).n1 if hasattr(solar_cell(i), 'n1') else 1
n2_array[i] = solar_cell(i).n2 if hasattr(solar_cell(i), 'n2') else 2
rsh_array[i] = min(solar_cell(i).R_shunt, 1e16) if hasattr(
solar_cell(i), 'R_shunt') else 1e16
rshTop_array[i] = max(solar_cell(i).R_sheet_top, 1e-16) if hasattr(
solar_cell(i), 'R_sheet_top') else 1e-16
rshBot_array[i] = max(solar_cell(i).R_sheet_bot, 1e-16) if hasattr(
solar_cell(i), 'R_sheet_bot') else 1e-16
try:
Isc_array[i] = solar_cell(i).jsc
I01_array[i] = solar_cell(i).j01
I02_array[i] = solar_cell(i).j02
Eg_array[i] = solar_cell(i).Eg
except AttributeError as err:
raise AttributeError(
'ERROR in quasi-3D solver: Junction is missing one essential argument. {}'
.format(err))
j = 0
for i in solar_cell.tunnel_indices:
rseries_array[j] = max(solar_cell[i].R_series, 1e-16) if hasattr(
solar_cell[i], 'R_series') else 1e-16
j += 1
rseries_array[-1] = max(R_back, 1e-16)
print("Solving quasi-3D Solar Cell...")
V, I, Vall, Vmet = solve_circuit_quasi3D(
bias_start, bias_end, bias_step, Isc_array, I01_array, I02_array,
n1_array, n2_array, Eg_array, rsh_array, rseries_array, injection,
contacts, rshTop_array, rshBot_array, R_line / h, R_contact, Lx, Ly)
print("... Done!!")
return V, I, Vall, Vmet
T=T,
R_series=0,
substrate=substrate)
Vin = np.linspace(-2, 2.61, 201)
V = np.linspace(0, 2.6, 300)
wl = np.linspace(350, 1000, 301) * 1e-9
light_source = LightSource(source_type='standard',
version='AM1.5g',
x=wl,
output_units='photon_flux_per_m',
concentration=1)
if __name__ == '__main__':
# We calculate the IV curve under illumination
solar_cell_solver(my_solar_cell, 'equilibrium')
# ,
# user_options={'T_ambient': T, 'db_mode': 'boltzmann', 'voltages': V, 'light_iv': True,
# 'wavelength': wl, 'optics_method': 'BL', 'mpp': True, 'internal_voltages': Vin,
# 'light_source': light_source})
# We can plot the electron and hole densities in equilibrium and at short circuit, both calculated automatically
# before calculating the IV curve
plt.figure(1)
for j in my_solar_cell.junction_indices:
zz = my_solar_cell[j].equilibrium_data.Properties['x'] + my_solar_cell[
j].offset
n = my_solar_cell[j].equilibrium_data.Properties['Nd']
p = my_solar_cell[j].equilibrium_data.Properties['Na']
plt.semilogy(zz, n, 'b')
plt.semilogy(zz, p, 'r')
