@inproceedings{2b1c78e2cd0946189989e6dec6f22858,
title = "Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm",
abstract = "The solar photovoltaic (PV) array is one of the main components of the solar PV system. The accuracy of the solar PV cell parameters and models is directly affected to the operation and control of the solar PV system. It is obvious that the solar PV cell parameters may change with various operation conditions. Thus, it is important to estimate parameters of the solar PV cell model. Due to the non-linearity, multivariable and multimodal features of the solar PV cell model, the existing approaches are incapable to estimate parameters of the solar PV cell model with a high accuracy. This paper proposes an improved artificial bee colony (ABC) algorithm for estimating parameters of the solar PV cell model. The estimation results obtained by using the improved ABC algorithm are promising and better than those found by other existing approaches.",
keywords = "Artificial bee colony algorithm, Parameter estimation, Solar photovoltaic cell",
author = "Huynh, {Duy C.} and Ho, {Loc D.} and Dunnigan, {Matthew W.}",
year = "2021",
doi = "10.1007/978-3-030-62324-1_24",
language = "English",
isbn = "9783030623234",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "281--292",
editor = "Yo-Ping Huang and Wen-June Wang and Quoc, {Hoang An} and Giang, {Le Hieu} and Nguyen-Le Hung",
booktitle = "Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020",
note = "5th International Conference on Green Technology and Sustainable Development 2020, GTSD 2020 ; Conference date: 27-11-2020 Through 28-11-2020",
}
