def test_deprecated_09(cec_inverter_parameters, adr_inverter_parameters):
# deprecated function pvsystem.snlinverter
with pytest.warns(pvlibDeprecationWarning):
pvsystem.snlinverter(250, 40, cec_inverter_parameters)
# deprecated function pvsystem.adrinverter
with pytest.warns(pvlibDeprecationWarning):
pvsystem.adrinverter(1232, 154, adr_inverter_parameters)
# deprecated function pvsystem.spvwatts_ac
with pytest.warns(pvlibDeprecationWarning):
pvsystem.pvwatts_ac(90, 100, 0.95)
# for missing temperature_model_parameters
match = "Reverting to deprecated default: SAPM cell temperature"
system = pvsystem.PVSystem()
with pytest.warns(pvlibDeprecationWarning, match=match):
system.sapm_celltemp(1, 2, 3)
def test_pvwatts_ac_arrays():
pdc = np.array([[np.nan], [50], [100]])
pdc0 = 100
expected = np.array([[nan],
[47.60843624],
[95.]])
out = pvsystem.pvwatts_ac(pdc, pdc0, 0.95)
assert_allclose(out, expected, equal_nan=True)
def test_pvwatts_ac_arrays():
pdc = np.array([[np.nan], [50], [100]])
pdc0 = 100
expected = np.array([[ nan],
[ 47.60843624],
[ 95. ]])
out = pvsystem.pvwatts_ac(pdc, pdc0, 0.95)
assert_allclose(expected, out, equal_nan=True)
def test_pvwatts_ac_series():
pdc = pd.Series([np.nan, 50, 100])
pdc0 = 100
expected = pd.Series(np.array([ nan, 47.608436, 95. ]))
out = pvsystem.pvwatts_ac(pdc, pdc0, 0.95)
assert_series_equal(expected, out)
def test_pvwatts_ac_scalars():
expected = 85.58556604752516
out = pvsystem.pvwatts_ac(90, 100, 0.95)
assert_allclose(out, expected)
def test_pvwatts_ac_series():
pdc = pd.Series([np.nan, 50, 100])
pdc0 = 100
expected = pd.Series(np.array([ nan, 47.608436, 95. ]))
out = pvsystem.pvwatts_ac(pdc, pdc0, 0.95)
assert_series_equal(expected, out)
def test_pvwatts_ac_scalars():
expected = 85.58556604752516
out = pvsystem.pvwatts_ac(90, 100, 0.95)
assert_allclose(expected, out)
def aggregate(user_directory):
print("Processing {}".format(user_directory))
res = {}
# read mask
with rasterio.open(os.path.join(user_directory, "mask.tif")) as src:
mask = src.read(1)
area = np.sum(mask) * 0.5 * 0.5
print("area", area)
path = Path(user_directory)
res = {}
res['area'] = area
for SCEN in scenarios:
fpath = os.path.join(
output_dir, "solar_rad_house_{}_scenario_{}_v1.tif".format(
path.parts[-1], SCEN))
res[SCEN] = {}
with rasterio.open(fpath) as src:
bands = src.count
data = src.read(masked=True)
max_W = 0.0
roofWs = {}
for b in range(bands):
roof_W = np.sum(
data[b, :, :].filled(fill_value=0) * mask) * cell_area
roofWs[b] = roof_W
max_W = max(max_W, roof_W)
print(max_W)
year_Wh_dc = 0.0
year_Wh_ac = 0.0
for b in range(bands):
roof_W = roofWs[b]
# Convert radiation level per cell to Watt hours
roof_Wh = roof_W * hours_per_ts
year_Wh_dc += roof_Wh
roof_Wh_ac = pvwatts_ac(pdc=roof_Wh, pdc0=max_W)
year_Wh_ac += roof_Wh_ac
if roof_Wh_ac > 0:
res[SCEN]["band_{}_Wh".format(b)] = round(
float(roof_Wh_ac), 4)
res[SCEN]["max_W"] = max_W
res[SCEN]["year_Wh_dc"] = year_Wh_dc
res[SCEN]["year_Wh_ac"] = year_Wh_ac
res[SCEN]["year_inv_eff"] = round(year_Wh_ac / year_Wh_dc * 100.0,
3)
print(SCEN, max_W, year_Wh_dc, year_Wh_ac,
round(year_Wh_ac / year_Wh_dc * 100.0, 3))
pv_sys_effs = list(range(5, 30)) + [100]
for pv_sys_eff in pv_sys_effs:
res["ONLY_SOLAR_PVSYSEFF_{}".format(pv_sys_eff)] = {}
res["ONLY_SOLAR_PVSYSEFF_{}".format(pv_sys_eff)]["max_W"] = 0.0
res["ONLY_SOLAR_PVSYSEFF_{}".format(pv_sys_eff)]["year_Wh_ac"] = 0.0
fpath = os.path.join(
output_dir,
"solar_rad_house_{}_scenario_{}_v1.tif".format(path.parts[-1],
"ONLY_SOLAR"))
with rasterio.open(fpath) as src:
bands = src.count
data = src.read(masked=True)
for b in range(bands):
roof_W = np.sum(
data[b, :, :].filled(fill_value=0) * mask) * cell_area
for pv_sys_eff in pv_sys_effs:
roof_Wh_ac = roof_W * hours_per_ts * pv_sys_eff / 100.0
if roof_Wh_ac > 0:
res["ONLY_SOLAR_PVSYSEFF_{}".format(pv_sys_eff)][
"band_{}_Wh".format(b)] = round(float(roof_Wh_ac), 4)
res["ONLY_SOLAR_PVSYSEFF_{}".format(
pv_sys_eff)]["year_Wh_ac"] += roof_Wh_ac
res["ONLY_SOLAR_PVSYSEFF_{}".format(
pv_sys_eff)]["max_W"] = max(
roof_W, res["ONLY_SOLAR_PVSYSEFF_{}".format(
pv_sys_eff)]["max_W"])
with gzip.GzipFile(
os.path.join("data",
"solar_rad_{}.json.gz".format(path.parts[-1])),
'w') as f:
f.write(json.dumps(res).encode('utf-8'))
