Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm

Zhen Li, Jianke Hu, Yifeng Han, Hefeng Li, Jun Wang*, Peter Lund

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

30 Downloads (Pure)

Abstract

The aim of this study is to propose a photovoltaic (PV) module simulation model with high accuracy under practical working conditions and strong applicability in the engineering field to meet various PV system simulation needs. Unlike previous model-building methods, this study combines the advantages of analytical and metaheuristic algorithms. First, the applicability of various metaheuristic algorithms is comprehensively compared and the seven parameters of the PV cell under standard test conditions are extracted using the double diode model, which verifies that the artificial hummingbird algorithm has higher accuracy than other algorithms. Then, the seven parameters under different conditions are corrected using the analytical method. In terms of the correction method, the ideal factor correction is added on the basis of previous methods to solve the deviation between simulated data and measured data in the non-linear section. Finally, the root mean squared error between the simulated current data and the measured current data of the proposed model under three different temperatures and irradiance is 0.0697, 0.0570 and 0.0289 A, respectively.
Original languageEnglish
Pages (from-to)1219–1232
JournalClean Energy
Volume7
Issue number6
Early online date2023
DOIs
Publication statusPublished - 1 Dec 2023
MoE publication typeA1 Journal article-refereed

Fingerprint

Dive into the research topics of 'Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm'. Together they form a unique fingerprint.

Cite this