Optimal reconstruction method of photovoltaic arrays based on improved mayfly algorithm

Xu-jiong Li; Guo-ming Yang

doi:10.1117/12.3004433

25 September 2023 Optimal reconstruction method of photovoltaic arrays based on improved mayfly algorithm

Xu-jiong Li, Guo-ming Yang

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 127880N (2023) https://doi.org/10.1117/12.3004433
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Partial shading is one of the main causes of output power loss and module mismatch of photovoltaic(PV) arrays. This paper proposes a reconfiguration method based on an improved mayfly algorithm(IMA) for PV arrays with a total crosstied(TCT) topology. The shadows on the PV array are uniformly distributed by changing the electrical connections inside the PV array as a way to equalize the line currents of the PV array. Under the shadow of a 10×10 photovoltaic array, the IMA reconstruction method and Sudoku reconstruction method and other heuristic algorithms were compared respectively by two evaluation criteria of mismatch loss and power increase percentage, and the radiation distribution diagram of the photovoltaic array reconstructed by IMA was given. The results show that IMA can effectively improve the PV array output power and reduce the mismatch loss. The output PV curves all tend to show a single peak, and the reconfiguration results are all superior to the other methods. In addition, hardware-in-the-loop experiments on the RTLAB-based platform verify the hardware feasibility

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xu-jiong Li and Guo-ming Yang "Optimal reconstruction method of photovoltaic arrays based on improved mayfly algorithm", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 127880N (25 September 2023); https://doi.org/10.1117/12.3004433

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