Hybrid Maximum Power Point Tracking Technique for PV Modules Based on a Double-Diode Model

Abstract

Photovoltaic (PV) systems are more efficient when operated in its maximum power point (MPP). Even with the existence of high number of MPP tracking (MPPT) techniques, it is possible to improve the MPPT efficiency. One way to achieve this improvement is to use model-based MPPT techniques, since they can estimate the MPP with reasonable accuracy, accelerating the MPP search process. Based on this motivation, the main objective of this article is to propose an efficient double-diode model-based + perturb and observe (P&O) heuristic-based hybrid MPPT technique. The proposition has the following three unique features: the double-diode model used in the MPPT technique has the capability of extrapolating the I-V curves of the PV modules for any environmental condition, even for temperature and irradiance values not used during the model building process; a parameter estimation technique that uses a combination of analytical equations and pattern search optimization algorithm is also presented for this unique model; and an irradiance estimation algorithm is also proposed, avoiding the irradiance sensor usually needed in model-based and hybrid MPPT techniques. Experimental results demonstrate that the integration of the model, the irradiance estimator, and reduced step P&O algorithm is an effective hybrid MPPT solution for PV systems.