A Comprehensive Review of Swarm Optimization Algorithms for MPPT Control of PV Systems under Partially Shaded Conditions

Abstract

Nowadays many researchers have been investigating on different photovoltaic (PV) modeling methods, various configurations of arrays, numerous algorithms, converter topologies etc to improve the efficiency of solar system. Improving the efficiency of solar panel by utilizing the correct maximum power point tracking (MPPT) control has become more important for conceiving the solar power reasonably. For designing an efficient PV system, an appropriate literature review is necessary for all the researchers. In this paper, a compendious study of different Swarm Intelligence (SI) based MPPT algorithms for PV systems feasible under partially shaded conditions are presented. SI algorithms use motivation from the foraging nature of animals and insects. In the last few decades, SI has gained tremendous attention as it has been proven as an efficient control technique for global optimization problems.

A State-of-Art-Review on Machine-Learning Based Methods for PV

“…The second group includes the intelligent techniques that explain the fuzzy-based MPPT, ANN-based MPPT evolutionary techniques, hybrid methods and MPPT techniques used in energy harvesting. 2020 [84] In the presented paper, a compendious study of different Swarm Intelligence (SI)-based MPPT algorithms for PV systems feasible under partially shaded conditions are presented. The methods are compared in terms of their swarm intelligence and advantages.…”

Design And Comparison of Mppt Controller for Pv Systems

“…Pilakkat et al (2020) and TIRTH et al (2020) provide comprehensive reviews of a wide range of MPPT algorithms. figure6shows the most frequent algorithm strategies.…”