Maximum power point tracking controller for photovoltaic system based on chaos quantum particle swarm optimization – moth-flame optimization hybrid model

• Autorzy: Wang Zili , Yuan Weilu

Identyfikatory

DOI

10.24425/aee.2024.150889

• Języki publikacji: EN

Abstrakty

EN

To convert photovoltaic arrays to solar energy in a more efficient way, this paper has proposed a maximum power point tracking controller model based on the chaotic quantum particle swarm-mothballing hybrid algorithm. First, the optimization of the particle swarm algorithm is designed to solve defects, such as premature maturity by using the quantum and chaotic strategies. The mothballing algorithm is introduced to help the model find global optimization-seeking more quickly. After that, further optimization was made to operate the tracking model in both offline and real-time parameters. The conductivity increment method and the perturbation observation method were adopted to effectively track the model under different temperatures and light intensities. Finally, the simulation and analysis experiments were carried out on the Simulink platform. The study’s proposed maximum power point tracking controller achieved a steady-state accuracy η2 of 99.84%. In summary, the study has proposed a hybrid intelligent algorithm with extraction of internal parameters. The maximum power point tracker based on the proposed method is proved to be both effective and accurate.

Słowa kluczowe

EN

maximum power point tracking; moth-flame optimization; particle swarm optimization; photovoltaic system

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2024
• Tom: Vol. 73, nr 3
• Strony: 663--680
• Opis fizyczny: Bibliogr. 22 poz., rys., tab., wykr., wz.

Twórcy

autor

Wang Zili

• College of Electromechanical Engineering, Anyang Vocational and Technical College, Anyang 455000, China

autor

Yuan Weilu

• College of Electromechanical Engineering, Anyang Vocational and Technical College, Anyang 455000, China

Bibliografia

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