Development of a self-powered wireless I-V tracer for online inspection and modelling of individual photovoltaic modules

Chen, Zhicong, Zheng, Haoxin, Zhong, Shengquan, Yang, Jiangtao, Wu, Lijun, Cheng, Shuying, Lin, Peijie, Long, Chao ORCID: 0000-0002-5348-8404 and Jiang, Lin ORCID: 0000-0001-6531-2791 (2026) Development of a self-powered wireless I-V tracer for online inspection and modelling of individual photovoltaic modules Solar Energy, 303. p. 114097. ISSN 0038-092X, 1471-1257

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Abstract

Current-Voltage (I-V) characteristic testing is critical for inspecting the actual performance of photovoltaic (PV) modules to ensure the energy efficiency of PV power stations. However, conventional I-V tracers are offline and centralized, which need to manually disconnect PV string/array from the inverter leading to operational downtime and energy losses and incapability of automatic I-V testing in real time at module level. Therefore, this paper designs a self-powered wireless I-V tracer for in-situ online evaluation and parameter identification of individual PV modules of a PV string/array. Firstly, a wireless I-V tracer is designed to be installed in a PV module, which utilizes capacitors as the variable load to achieve I-V sweeping and uses power transistors as electronic switches to temporarily separate the measured PV module from its PV string. The I-V tracer is self-powered by the attached PV module without the need of extra battery and can be accessed through a two-level wide-coverage wireless sensors network. Secondly, a new hybrid optimization method is designed for model parameter identification of PV module, which is based on Cubic Chaos Rao-1 (CCRAO1) and Enhanced Nelder-Mead Simplex (ENMS) and thus named CCRAO1-ENMS. The ENMS algorithm mitigates local minima by using the main diagonal vector to replace the worst simplex vertex during the contraction phase. Finally, extensive experiment evaluation using both the benchmark and laboratory I-V curve datasets collected with the developed system demonstrates that the CCRAO1-ENMS achieves the lowest root mean square errors of 2.4251E-3 for the benchmark module while reducing CPU time by over 50% compared to existing methods. Furthermore, the acquired I-V curves are high-fidelity and noise-free, demonstrating that the developed I-V tracer is effective for high-quality monitoring of both the dynamic and static I-V characteristics of PV modules.

Item Type:	Article
Uncontrolled Keywords:	Photovoltaic modules, wireless self-powered I-V tracer, I-V characteristics monitoring, Parameter extraction, Metaheuristic optimization
Divisions:	Faculty of Science & Engineering Faculty of Science & Engineering > School of Engineering Faculty of Science & Engineering > School of Engineering > Electrical Engineering and Electronics
Depositing User:	Symplectic Admin
Date Deposited:	11 Nov 2025 10:34
Last Modified:	28 Feb 2026 13:47
DOI:	10.1016/j.solener.2025.114097
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3195316
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