Innovative and precise MPP estimation using P–V curve geometry for photovoltaics

This paper elaborates a direct maximum power point (MPP) finding method for solar photovoltaics (PV) based on quadratic regression analysis of the geometry of the power–voltage (P–V) curve of a typical PV cell or module. This method works in two stages for determination of the MPP parameters such as voltage (Vmp), power (Pmp) and fill factor with high level of accuracy. At first, it determines the approximate MPP parameters using a few data collected from the open-circuit and short-circuit regions of a current–voltage (I–V) characteristic, and further it refines the obtained parameters using quadratic regression analysis. This method is non-iterative and requires no prior knowledge of the physical and electrical parameters of the cell. Besides high accuracy, the method is also very precise in handling the noise level (up to 20%) in the data. The method was tested on a wide range of PV cells reported in the literature including silicon, copper indium gallium selenide (CIGS), copper zinc tin sulphide selenide (CZTSSe) and organic cells. The estimated MPP parameters are in excellent agreement with those of reported for the cells. The method is also employed for an experimental P–V characteristic of a 10 Wp silicon module and a synthesized P–V characteristic of a 120 Wp silicon module. The estimated fill factor for silicon modules exactly matches with those available in the datasheet specifications. Experimental evaluation of the method as compared to perturb-and-observe (P&O) in the passive mode exhibits quick response. Thus, the method is applicable for a wide category of PV cells to PV modules.