An Innovative MPPT Method Based on the Estimated Model of the Photovoltaic Cell considering the Environmental Conditions

Abstract

In this paper, a novel adaptive photovoltaic maximum power point tracking (MPPT) circuit is proposed, called AT2MPPT. The AT2MPPT circuit is based on a type two fuzzy logic set and utilizes a detailed two-diode model of a solar cell, as well as an innovative hybrid algorithm for designing the MPPT circuit. The effects of environmental conditions such as azimuth, wind speed, wind direction, and irradiation, as well as the uncertainty of radiation intensity, are taken into account in the solar cell model. It is demonstrated that changes in environmental conditions can cause up to a 20% change in the PV parameters. To optimize the AT2MPPT parameters and fuzzy membership functions (MFs), a hybrid lightning search algorithm and whale optimization algorithm (hLSA-WOA) are proposed. The accuracy of the hLSA-WOA is evaluated by comparing its results with those of other optimization algorithms on 10 standard benchmarks. The simulation results indicate that the hLSA-WOA has high accuracy and is nontrapping in local optima. Finally, the proposed AT2MPPT circuit is used to track the MPPT of a PV array in partial shade, and its performance is compared with that of P&O and fuzzy MPPT circuits. The results confirm the superior performance of the AT2MPPT circuit, which produces 1.1% more power than the other two circuits. Additionally, the AT2MPPT circuit has lower power ripple and tracking time compared to perturb, observation, and fuzzy MPPT circuits.