A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system

• Autorzy: Mostafa Hazem H. , Ibrahim Amr M. , Anis Wagdi R.

Identyfikatory

DOI

10.24425/aee.2019.129345

• Języki publikacji: EN

Abstrakty

EN

This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS- PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.

Słowa kluczowe

EN

hybrid optimization; golden sections search; multi-verse optimization algorithm; maximum power point tracking; perturb and observe; photovoltaic (PV)

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2019
• Tom: Vol. 68, nr 3
• Strony: 611--627
• Opis fizyczny: Bibliogr. 22 poz., rys., tab., wz.

Twórcy

autor

Mostafa Hazem H.

• Energy and Renewable Energy Department Faculty of Engineering, Egyptian Chinese University Gesr ElSuez, 11724 Cairo, Egypt

autor

Ibrahim Amr M.

• Electrical Power and Machines Department Faculty of Engineering, Ain Shams University Cairo, Egypt

autor

Anis Wagdi R.

• Electronics and Communication Department Faculty of Engineering, Ain Shams University Cairo, Egypt

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).