Open AccessEnhanced energy harvesting from shaded PV systems using an improved particle swarm optimisation
Author(s) -
Gopalakrishnan Satheesh Krishnan,
Kinattingal Sundareswaran,
Simon Sishaj Pulikottil,
Ark Kumar Kevin
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2019.0936
Subject(s) - maximum power point tracking , photovoltaic system , particle swarm optimization , insolation , computer science , population , convergence (economics) , maximum power principle , shading , energy (signal processing) , control theory (sociology) , power (physics) , engineering , mathematics , artificial intelligence , algorithm , statistics , physics , electrical engineering , quantum mechanics , computer graphics (images) , inverter , economic growth , sociology , control (management) , climatology , demography , economics , geology
This research work is concerned with maximum power point tracking (MPPT) in photovoltaic (PV) systems under partially shaded conditions (PSCs) through an improved particle swarm optimisation (PSO). The traditional PSO is investigated toward MPPT and the reasons for delayed convergence characteristics are investigated. Then, a modified PSO is proposed, in which population is reduced sequentially by eliminating less‐promising particles. The new concept is applied to a 30 kW PV plant situated in a school building and the results are analysed. The new methodology is also experimentally verified on a 400 W prototype PV system in the laboratory. Enhanced energy harvesting from the existing 30 kW PV plant is highlighted considering realistic shading patterns and full bright conditions of solar insolation. The computed and measured results clearly demonstrate that the new PSO is a promising candidate for MPPT in PV systems under PSC.