Bifacial Tests

Note

The manual approach described in this section can still be implemented, but the preferred approach to bifacial capacity testing as of v0.15.0 is to use one of the default test setups (bifi_e2848_etotal or bifi_power_tc) or write a regression_columns dictionary that will provide the calculated regressors when processed by process_regression_columns.

This section discusses how pvcaptest can be used to conduct a capacity test for a project with bifacial modules.

NREL Modified Bifacial Capacity Test

Pvcaptest can be used to conduct a bifacial capacity test following the NREL Suggested Modifications for Bifacial Capacity Testing.

The suggested approach uses the standard ASTM regression equation:

\[P = E_{POA}\left(a_{1} + a_{2} * E_{POA} + a_{3} * T_{a} + a_{4} * v\right)\]

but, replaces the \(E_{POA}\) term with \(E_{Total}\):

\[E_{Total} = E_{POA} + E_{Rear} * \varphi\]

where,

\(E_{Rear}\) is the rear POA irradiance and

\(\varphi\) is the bifaciality factor.

To conduct a bifacial capacity test you should make the following adjustments.

The regression equation default does not need to be changed.

You will need an \(E_{Total}\) term in the CapData.data and CapData.data_filtered dataframes.

CapData.data['E_Total'] = CapData.data['E_POA'] + CapData.data['E_Rear'] * bifaciality
# either of the below lines will copy the modified data `data_filtered`
CapData.data_filtered = CapData.data.copy()
CapData.reset_filter()

You will then also need to adjust the CapData.regression_columns to map the poa term of the regression equation to the new E_Total column in the dataframe.

CapData.set_regression_cols(
    power='real_power_column',
    poa='E_Total',
    t_amb='temp_col_or_group',
    w_vel='wind_speed_col_or_group'
)

Other Bifacial Capacity Test Approaches

The regression equation can be easily modified by simply assigning an new regression formula. For example, to conduct a regression of temperature corrected power against front side POA irradiance and rear side POA irradiance, you could use the following:

CapData.regression_formula = 'power_temp_adj ~ poa_front + poa_rear'

The regression columns would also need to be updated to map the regression terms to the correct columns or groups of columns. In this case a dictionary should be assigned to the regression_cols attribute directly rather than using the set_regression_cols method.

CapData.regression_cols = {
    'power_temp_adj': 'poa_front',
    'poa_front': 'E_POA',
    'poa_rear': 'E_Rear'
}