An Iterative Procedure with Improved Initial Guess to Evaluate the Seven Parameters of the Two Diode Model for a Photovoltaic Module

Ziyue Liu, Purdue University

Abstract

Climate change and global warming indicate that reducing the use of traditional fossil energy and developing new renewable energy should be an essential matter. Solar energy has emerged as one of the renewable energy sources for electricity generation since the late 20th century. One way to utilize solar energy is to collect and convert it into electricity by solar photovoltaic devices through the photovoltaic effect. Due to the high cost of photovoltaic modules, it is essential to optimize the performance of photovoltaic modules by using accurate equivalent circuit models. Among the available equivalent circuit models, the single diode model is relatively simple and computationally efficient but would be inaccurate if the recombination loss were substantial. The double diode model includes more parameters to represent the recombination loss, so the accuracy improves, but at the cost of adding more parameters to the model. The primary challenge of applying the double diode model is obtaining the optimum value for the seven model parameters with a reasonable computational effort. The current study investigates the effect of each term in the double diode model. It then proposes a method to obtain an initial estimate for each of the seven model parameters from data provided by the manufacturer. Using these initial estimated parameters as inputs, the NewtonRaphson method is applied to improve parameter estimates and prediction accuracy. The performance of two PV modules from different manufacturers is then modeled using the initial parameter estimates and the Newton-Raphson updated parameters. Both are compared to the manufacturers’ data.

Degree

M.Sc.

Advisors

Kozel, Purdue University.

Subject Area

Climate Change|Alternative Energy|Condensed matter physics|Energy|Environmental management|Marketing|Mathematics|Physics

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