An efficient fuzzy-logic based MPPT controller for grid-connected PV systems by farmland fertility optimization algorithm

Abstract

Solar energy has largely been penetrated into electric power systems due to its numerous merits such as zero emissions while having no noise. In this regard, the operation of such systems would not be a straightforward task as obtaining the maximum power point (MPP) in the presence of modules mismatching and partial shading (PS) problems would be very challenging. Accordingly, MPP tracking (MPPT) techniques have been introduced to address the problem while these techniques themselves also may have some issues to investigate, such as the tracking speed and conciseness. There have been numerous methods developed thus far for the MPPT applications in solar photovoltaic (PV) panels. In between, prevalent approaches are considered quick and straightforward algorithms, but they present rational performance with stable climatic conditions. Furthermore, usually, these methods are trapped into local maxima and global maxima would be overlooked. Hence, a combinatorial MPPT algorithm is proposed in this paper based on the fuzzy logic controller (FLC) and improved farmland fertility optimization (IFFO) method to optimally tune the parameters of the controller. This method would bring excellent performance to the system in the case of uniform irradiance (UI) and PS. The performance of the presented approach has been validated by making a comprehensive comparison with six other methods while it leads to the highest efficiencies of 99 % for UI, PS1, and PS2. It is also noteworthy the solar system is operated together with a battery energy storage (BES) system to effectively address the solar power generation deficit during the day.