Improved PSO: A Comparative Study in MPPT Algorithm for PV System Control under Partial Shading Conditions

Wafa Hayder, Emanuele Ogliari, Alberto Dolara, Aycha Abid, Mouna Ben Hamed and Lasaad Sbita
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Wafa Hayder: Department of Electrical Engineering, National Engineering School of Gabes, 6029 Gabes, Tunisia
Emanuele Ogliari: Department of Energy, Politecnico di Milano, 20156 Milan, Italy
Alberto Dolara: Department of Energy, Politecnico di Milano, 20156 Milan, Italy
Aycha Abid: Department of Electrical Engineering, National Engineering School of Gabes, 6029 Gabes, Tunisia
Mouna Ben Hamed: Department of Electrical Engineering, National Engineering School of Gabes, 6029 Gabes, Tunisia
Lasaad Sbita: Department of Electrical Engineering, National Engineering School of Gabes, 6029 Gabes, Tunisia

Energies, 2020, vol. 13, issue 8, 1-22

Abstract: This paper deals with the implementation and analysis of a new maximum power point tracking (MPPT) control method, which is tested under variable climatic conditions. This new MPPT strategy has been created for photovoltaic systems based on Particle Swarm Optimization (PSO). The novel Improved Particle Swarm Optimization (IPSO) algorithm is tested in several simulations which have been implemented in view of the various system responses such as: voltage, current, and power. The performances of the proposed IPSO algorithm have been completed and compared with results of well-established methods adopted in the literature showing a higher accuracy.

Keywords: maximum power point tracking (MPPT); particle swarm optimization algorithm (PSO); photovoltaic (PV) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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