Study Comparison Between Enhanced Firefly and Differential Evolution to Solve the Maximum Power Point Tracking Problem

• Published in: Journal Europeen des Systemes Automatises Vol. 55; no. 5; p. 641
• Main Authors: Issa Ahmed Abed, May Mohammed Ali, Ali Ahmed Abed
• Format: Journal Article
• Language: English
• Published: Edmonton International Information and Engineering Technology Association (IIETA) 30.11.2022
• Subjects: Control algorithms; Energy resources; Genetic algorithms; Mutation; Optimization algorithms; Optimization techniques; Power
• ISSN: 1269-6935; 2116-7087; 2116-7087
• DOI: 10.18280/jesa.550509

The penetration of photovoltaic (PV) in electric power generation is continually increasing. On the other side, the load will receive the actual power, which is a part of power supplied by the photovoltaic. Therefore, it is necessary to extract maximum power from PV. One of a defy problem, is the tracking maximum power point (MPPT) in photovoltaic frameworks and it is a significant task. It can be a reproducer of maximum power from a photovoltaic system, which it depends on the adjusting of duty cycle of DC-DC converter. In order to produce a maximum power transfer, the impedance between the source and the load should be coincide by using of a buck boost converter. In this work, the proposed methods; Firefly algorithm (FA), Enhanced Firefly (EFA), Differential Evolution Scheme1, Differential Evolution Scheme2, and Differential Evolution Scheme 3 were tested for their performances in different conditions. Finally, the simulation results confirm that the second scheme of DE outperforms the others. Visual Basic. Net has been used to simulate the results and proceed with algorithms.