@ARTICLE{Mostafa_Hazem_H._A_2019,
 author={Mostafa, Hazem H. and Ibrahim, Amr M. and Anis, Wagdi R.},
 volume={vol. 68},
 number={No 3},
 journal={Archives of Electrical Engineering},
 pages={611-627},
 howpublished={online},
 year={2019},
 publisher={Polish Academy of Sciences},
 abstract={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.},
 type={Article},
 title={A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system},
 URL={http://czasopisma.pan.pl/Content/112889/PDF/11_AEE-2019-3_INTERNET.pdf},
 doi={10.24425/aee.2019.129345},
 keywords={hybrid optimization, golden sections search, multi-verse optimization algo-rithm, maximum power point tracking, perturb and observe, photovoltaic (PV)},
}