Adaptive Estimation Approach for Parameter Identification of Photovoltaic Modules

This paper presents a novel identification technique for estimation of unknown parameters in photovoltaic (PV) systems. A single-diode model is considered for the PV system, which consists of five unknown parameters. Using information about standard test conditions, three unknown parameters are written as functions of the other two parameters in a reduced model. An objective function and a set of inequality constraints are defined for the reduced model, considering limitations of the physical system. It is shown that the nonconvex optimization problem of PV systems is converted to a convex optimization one. The constraints are enforced using a modified barrier function that generates an augmented convex objective function. An adaptive identification technique is utilized to find the optimal values of the augmented cost. Unlike most identification techniques, the proposed algorithm has a precise and unique solution, which is easy to implement. The effectiveness of the proposed approach is confirmed using some simulation and experiments.