def test_slope_aware_backtracking():
"""
Test validation data set from https://www.nrel.gov/docs/fy20osti/76626.pdf
"""
index = pd.date_range('2019-01-01T08:00', '2019-01-01T17:00', freq='h')
index = index.tz_localize('Etc/GMT+5')
expected_data = pd.DataFrame(index=index,
data=[
(2.404287, 122.79177, -84.440, -10.899),
(11.263058, 133.288729, -72.604, -25.747),
(18.733558, 145.285552, -59.861, -59.861),
(24.109076, 158.939435, -45.578, -45.578),
(26.810735, 173.931802, -28.764, -28.764),
(26.482495, 189.371536, -8.475, -8.475),
(23.170447, 204.13681, 15.120, 15.120),
(17.296785, 217.446538, 39.562, 39.562),
(9.461862, 229.102218, 61.587, 32.339),
(0.524817, 239.330401, 79.530, 5.490),
],
columns=[
'ApparentElevation', 'SolarAzimuth',
'TrueTracking', 'Backtracking'
])
expected_axis_tilt = 9.666
expected_slope_angle = -2.576
slope_azimuth, slope_tilt = 180.0, 10.0
axis_azimuth = 195.0
axis_tilt = tracking.calc_axis_tilt(slope_azimuth, slope_tilt,
axis_azimuth)
assert np.isclose(axis_tilt, expected_axis_tilt, rtol=1e-3, atol=1e-3)
cross_axis_tilt = tracking.calc_cross_axis_tilt(slope_azimuth, slope_tilt,
axis_azimuth, axis_tilt)
assert np.isclose(cross_axis_tilt,
expected_slope_angle,
rtol=1e-3,
atol=1e-3)
sat = tracking.singleaxis(90.0 - expected_data['ApparentElevation'],
expected_data['SolarAzimuth'],
axis_tilt,
axis_azimuth,
max_angle=90.0,
backtrack=True,
gcr=0.5,
cross_axis_tilt=cross_axis_tilt)
assert_series_equal(sat['tracker_theta'],
expected_data['Backtracking'].rename('tracker_theta'),
check_less_precise=True)
truetracking = tracking.singleaxis(90.0 -
expected_data['ApparentElevation'],
expected_data['SolarAzimuth'],
axis_tilt,
axis_azimuth,
max_angle=90.0,
backtrack=False,
gcr=0.5,
cross_axis_tilt=cross_axis_tilt)
assert_series_equal(truetracking['tracker_theta'],
expected_data['TrueTracking'].rename('tracker_theta'),
check_less_precise=True)
def test_slope_aware_backtracking():
"""
Test validation data set from https://www.nrel.gov/docs/fy20osti/76626.pdf
"""
expected_data = np.array(
[('2019-01-01T08:00-0500', 2.404287, 122.79177, -84.440, -10.899),
('2019-01-01T09:00-0500', 11.263058, 133.288729, -72.604, -25.747),
('2019-01-01T10:00-0500', 18.733558, 145.285552, -59.861, -59.861),
('2019-01-01T11:00-0500', 24.109076, 158.939435, -45.578, -45.578),
('2019-01-01T12:00-0500', 26.810735, 173.931802, -28.764, -28.764),
('2019-01-01T13:00-0500', 26.482495, 189.371536, -8.475, -8.475),
('2019-01-01T14:00-0500', 23.170447, 204.13681, 15.120, 15.120),
('2019-01-01T15:00-0500', 17.296785, 217.446538, 39.562, 39.562),
('2019-01-01T16:00-0500', 9.461862, 229.102218, 61.587, 32.339),
('2019-01-01T17:00-0500', 0.524817, 239.330401, 79.530, 5.490)],
dtype=[('Time', '<M8[h]'), ('ApparentElevation', '<f8'),
('SolarAzimuth', '<f8'), ('TrueTracking', '<f8'),
('Backtracking', '<f8')])
expected_axis_tilt = 9.666
expected_slope_angle = -2.576
slope_azimuth, slope_tilt = 180.0, 10.0
axis_azimuth = 195.0
axis_tilt = tracking.calc_axis_tilt(slope_azimuth, slope_tilt,
axis_azimuth)
assert np.isclose(axis_tilt, expected_axis_tilt, rtol=1e-3, atol=1e-3)
cross_axis_tilt = tracking.calc_cross_axis_tilt(slope_azimuth, slope_tilt,
axis_azimuth, axis_tilt)
assert np.isclose(cross_axis_tilt,
expected_slope_angle,
rtol=1e-3,
atol=1e-3)
sat = tracking.singleaxis(90.0 - expected_data['ApparentElevation'],
expected_data['SolarAzimuth'],
axis_tilt,
axis_azimuth,
max_angle=90.0,
backtrack=True,
gcr=0.5,
cross_axis_tilt=cross_axis_tilt)
np.testing.assert_allclose(sat['tracker_theta'],
expected_data['Backtracking'],
rtol=1e-3,
atol=1e-3)
truetracking = tracking.singleaxis(90.0 -
expected_data['ApparentElevation'],
expected_data['SolarAzimuth'],
axis_tilt,
axis_azimuth,
max_angle=90.0,
backtrack=False,
gcr=0.5,
cross_axis_tilt=cross_axis_tilt)
np.testing.assert_allclose(truetracking['tracker_theta'],
expected_data['TrueTracking'],
rtol=1e-3,
atol=1e-3)
def test_calc_axis_tilt():
# expected values
expected_axis_tilt = 2.239 # [degrees]
expected_side_slope = 9.86649274360294 # [degrees]
expected = DATA_DIR / 'singleaxis_tracker_wslope.csv'
expected = pd.read_csv(expected, index_col='timestamp', parse_dates=True)
# solar positions
starttime = '2017-01-01T00:30:00-0300'
stoptime = '2017-12-31T23:59:59-0300'
lat, lon = -27.597300, -48.549610
times = pd.DatetimeIndex(pd.date_range(starttime, stoptime, freq='H'))
solpos = pvlib.solarposition.get_solarposition(times, lat, lon)
# singleaxis tracker w/slope data
slope_azimuth, slope_tilt = 77.34, 10.1149
axis_azimuth = 0.0
max_angle = 75.0
# Note: GCR is relative to horizontal distance between rows
gcr = 0.33292759 # GCR = length / horizontal_pitch = 1.64 / 5 / cos(9.86)
# calculate tracker axis zenith
axis_tilt = tracking.calc_axis_tilt(slope_azimuth,
slope_tilt,
axis_azimuth=axis_azimuth)
assert np.isclose(axis_tilt, expected_axis_tilt)
# calculate cross-axis tilt and relative rotation
cross_axis_tilt = tracking.calc_cross_axis_tilt(slope_azimuth, slope_tilt,
axis_azimuth, axis_tilt)
assert np.isclose(cross_axis_tilt, expected_side_slope)
sat = tracking.singleaxis(solpos.apparent_zenith,
solpos.azimuth,
axis_tilt,
axis_azimuth,
max_angle,
backtrack=True,
gcr=gcr,
cross_axis_tilt=cross_axis_tilt)
np.testing.assert_allclose(sat['tracker_theta'],
expected['tracker_theta'],
atol=1e-7)
np.testing.assert_allclose(sat['aoi'], expected['aoi'], atol=1e-7)
np.testing.assert_allclose(sat['surface_azimuth'],
expected['surface_azimuth'],
atol=1e-7)
np.testing.assert_allclose(sat['surface_tilt'],
expected['surface_tilt'],
atol=1e-7)
# with north-south axes on terrain that slopes down to the south-south-east.
# Assuming the axes are installed parallel to the ground, the northern ends
# of the axes will be higher than the southern ends. But because the slope
# isn't purely parallel or perpendicular to the axes, the axis tilt and
# cross-axis tilt angles are not immediately obvious. We can use pvlib
# to calculate them for us:
# terrain slopes 10 degrees downward to the south-south-east. note: because
# slope_azimuth is defined in the direction of falling slope, slope_tilt is
# always positive.
slope_azimuth = 155
slope_tilt = 10
axis_azimuth = 180 # tracker axis is still N-S
# calculate the tracker axis tilt, assuming that the axis follows the terrain:
axis_tilt = tracking.calc_axis_tilt(slope_azimuth, slope_tilt, axis_azimuth)
# calculate the cross-axis tilt:
cross_axis_tilt = tracking.calc_cross_axis_tilt(slope_azimuth, slope_tilt,
axis_azimuth, axis_tilt)
print('Axis tilt:', '{:0.01f}°'.format(axis_tilt))
print('Cross-axis tilt:', '{:0.01f}°'.format(cross_axis_tilt))
# %%
# And now we can pass use these values to generate the tracker curve as
# before:
tracker_data = tracking.singleaxis(
apparent_zenith=solpos['apparent_zenith'],
apparent_azimuth=solpos['azimuth'],
