Nonlinear and multivariate regression models of current and voltage at maximum power point of bifacial photovoltaic strings

Abstract

The bifacial photovoltaic (PV) modules are able to convert the irradiance that hits both the front and the back side of the modules into electrical energy, this allows to increase the output power compared to monofacial modules. However, the mathematical models used for traditional PV modules do not consider the contribution of rear irradiance, even recent works deal with the modeling of the rear irradiance influence on bPV power output. In the present work some empirical models capable of estimating the current and voltage at maximum power point conditions are unveiled; the models consider only the front irradiance, as monofacial PV modules, or the back irradiance through the concept of equivalent irradiance and module temperature. In addition, some modifications to the current and voltage models have been proposed. In all cases, the optimal parameters of the models are obtained starting from a dataset of experimental data acquired from a string of bifacial photovoltaic modules installed in Catania (Italy). The PV plant under study was monitored for an entire year, thus allowing the use of data acquired in different weather conditions.

The method description includes the filtering of the input signals and the searching method of the empirical coefficients in order to estimate the current and voltage at the maximum power point (MPP) for bifacial photovoltaic modules.