Open AccessParticle swarm optimisation‐based model and analysis of photovoltaic module characteristics in snowy conditions
Author(s) -
Khenar Mohammad,
Hosseini Seyedkazem,
Taheri Shamsodin,
Cretu AnaMaria,
Pouresmaeil Edris,
Taheri Hamed
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2018.5840
Subject(s) - photovoltaic system , snowpack , snow , environmental science , computer science , particle swarm optimization , electronic engineering , meteorology , engineering , electrical engineering , algorithm , physics
In this study, a novel methodology of photovoltaic (PV) modelling is proposed to represent the instantaneous electrical characteristics of PV modules covered with snow. The attenuation of the transmitted solar radiation penetrating a layer of snow is rigorously estimated based on the Giddings and LaChapelle theory. This theory introduced the level of radiation that reaches the surface of the PV module through the snowpack, significantly affected by the snow properties and thickness. The proposed modelling approach is based on the single‐diode‐five‐parameter equivalent circuit model. The parameters of the model are updated through instantaneous measurements of voltage and current that are optimised by the particle swarm optimisation algorithm. The proposed approach for modelling snow‐covered PV modules was successfully validated in outdoor tests using three different types of PV module technologies typically used in North America's PV farms under different cold weather conditions. In addition, the validity of the proposed model was investigated using real data obtained from the SCADA system of a 12‐MW grid‐connected PV farm. The proposed model can help to improve PV performance under snow conditions and can be considered a powerful tool for the design and selection of PV modules subjected to snow accretion.