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 of standard test condition (STC), 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 non-convex optimization problem of
PV systems is converted to a convex constrained optimization one. The constraints are enforced
using a modified barrier function that generates an augmented 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.