Estimation of PV module parameters from datasheet information using optimization techniques

The paper presents a technique for parameter estimation of photovoltaic (PV) modules from datasheet information. The manufacturer normally provides open-circuit voltage, short-circuit current, maximum power, and voltage at maximum power under the standard test conditions (STC). The four datasheet values represent the targeted performance of the module. Parameter estimation is formulated as an optimization problem solved by traditional nonlinear programming techniques as well as global search algorithms. The objective is to search a set of parameters that minimizes the error between targeted and computed performance. The methodology is successfully applied to single- and double-diode equivalent circuits of PV modules. Evidently, the need to perform prototype lab testing, for the purpose of parameter estimation, is eliminated. Results show that genetic algorithms (GA) outperform other optimization techniques in obtaining the equivalent circuit parameters of a commercially available PV module.