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An Enhanced Moth-Flame Optimization with Multiple Flame Guidance Mechanism for Parameter Extraction of Photovoltaic Models.

Wang, Z., Cao, Z., Liu, C., Jia, H., Tian, F. and Liu, F., 2022. An Enhanced Moth-Flame Optimization with Multiple Flame Guidance Mechanism for Parameter Extraction of Photovoltaic Models. Mathematical Problems in Engineering, 2022, 8398768.

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DOI: 10.1155/2022/8398768

Abstract

How to accurately and efficiently extract photovoltaic (PV) model parameters is the primary problem of photovoltaic system optimization. To accurately and efficiently extract the parameters of PV models, an enhanced moth-flame optimization (EMFO) with multiple flame guidance mechanism is proposed in this study. In EMFO, an adaptive flame number updating mechanism is used to adaptively control the flame number, which enhances the local and global exploration capabilities of MFO. Meanwhile, a multiple flame guidance mechanism is designed for the full use of the position information of flames, which enhances the global diversity of the population. The EMFO is evaluated with other variants of the MFO on 25 benchmark functions of CEC2005, 28 functions of CEC2017, and 5 photovoltaic model parameter extraction problems. Experimental results show that the EMFO has obtained a better performance than other compared algorithms, which proves the effectiveness of the proposed EMFO. The method proposed in this study provides MFO researchers with ideas for adaptive research and making full use of flame population information.

Item Type:Article
ISSN:1024-123X
Additional Information:This research was partially funded by the Shaanxi Natural Science Basic Research Project (grant no. 2020JM-565).
Group:Faculty of Science & Technology
ID Code:37145
Deposited By: Symplectic RT2
Deposited On:04 Jul 2022 15:35
Last Modified:04 Jul 2022 15:35

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