Open AccessA Comprehensive Review of Swarm Optimization Algorithms for MPPT Control of PV Systems under Partially Shaded Conditions
Author(s) -
Deepthi Pilakkat,
S. Kanthalakshmi,
S. Navaneethan
Publication year - 2020
Publication title -
electronics/elektronika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.128
H-Index - 10
eISSN - 2831-0128
pISSN - 1450-5843
DOI - 10.7251/els2024003p
Subject(s) - maximum power point tracking , photovoltaic system , swarm behaviour , computer science , swarm intelligence , network topology , control engineering , power (physics) , particle swarm optimization , control (management) , engineering , electronic engineering , algorithm , electrical engineering , artificial intelligence , voltage , physics , quantum mechanics , inverter , operating system
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.