Analysis of Maximum Power Point Tracking (MPPT) Techniques under Different Atmospheric Conditions: Technical Review

Abstract

Solar photovoltaic (PV) use is on the rise, with benefits, like free fuel cost, low maintenance. However, it has some challenges: Low energy conversion efficiency and high cost. Further, it produces variable maximum power that is dependent on the atmospheric conditions that involve uniform radiation, rapidly varying radiations, temperature variations and partial shading conditions (PSCs). The maximum power is produced at the maximum power point (MP) varies constantly as the atmospheric conditions changes, it has different features under the different atmospheric conditions, and it is different from the operating point. Therefore, the extraction of the maximum power is crucial. This task is performed using Maximum power point tracking (MPS) techniques. This study investigated the effect of different atmospheric conditions and the load on the maximum power point (MPP, and it examined the performance of the MPPT techniques under different atmospheric conditions. The study reviewed published literature on MPPT techniques covering the three main categories of offline, online and hybrid MPPT techniques. Online MPPT techniques include Artificial intelligence and Emerging MPPT techniques. The study showed that not all the atmospheric condition have been fully considered, the uniform and PSCs were considered, while rapidly varying radiations had very few, and temperature variation almost nil. Also, offline and conventional MPPT techniques fail to track MPP under rapidly varying and partial shading conditions, on the other hand, artificial intelligence and emerging MPPT techniques could track MPP under PSCs. In addition, the case of oscillations about MPP reported some cases.