Research on MPPT of PV system based on IPSO algorithm

Yuefei Sun; Xianbo Sun; Yi Zhang; Yuhan Wu; Baofu Dai

doi:10.1117/12.2641002

2 December 2022 Research on MPPT of PV system based on IPSO algorithm

Yuefei Sun, Xianbo Sun, Yi Zhang, Yuhan Wu, Baofu Dai

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 122881T (2022) https://doi.org/10.1117/12.2641002
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

Under partial shadow conditions, in the use of PSO algorithm in MPPT, there are problems such as slowastrictionspeed, likely to access to local optimization and low tracking accuracy. This paper put forward an improved particle swarmoptimization algorithm apply to maximum power point tracking control method. This method introduces a randominertia weight factor and adds mutation disturbance to the update of the particle population position to enhancetheconvergence speed and search ability of particles, and enables the "premature" particles to quickly jump out of thelocal optimization, thereby enhancing the optimization of the PSO algorithm performance. After simulation analysis, theresults display that compared with the PSO algorithm, the method proposed in the article has a faster convergence speedand higher tracking accuracy in the process of system tracking, thereby enhance the output efficiency of the PVarray.

Citation Download Citation

Yuefei Sun, Xianbo Sun, Yi Zhang, Yuhan Wu, and Baofu Dai "Research on MPPT of PV system based on IPSO algorithm", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 122881T (2 December 2022); https://doi.org/10.1117/12.2641002

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