Optimization of fuzzy photovoltaic maximum power point tracking controller using chimp algorithm

Ammar Al-Gizi, Abbas Hussien Miry, Mohanad A. Shehab


In this paper, a photovoltaic (PV) fuzzy maximum power point tracking (MPPT) method optimized by the chimp algorithm is presented. The fuzzy logic controller (FLC) of seven triangular membership functions (MFs) is used. The optimization fitness function is composed of transient and steady-state indices under different irradiation and temperature operating conditions. By using MATLAB package, the performance of optimized method is examined and compared with asymmetrical FLC and well-known perturb and observe (P&O) tracking methods at different operating conditions in terms of: transient rising time (tr) and energy yield during 30 s. Moreover, the tracking methods are also compared in terms of the fitness function value. From the comparison of simulation results, a more energy can be harvested by using the proposed optimized tracking method compared to the other methods. Consequently, at the various operating conditions, the proposed method can be used as a more reliable tracking method for PV systems.


chimp algorithm; fuzzy logic controller; maximum power point tracking; optimization; photovoltaic;

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DOI: http://doi.org/10.11591/ijece.v12i5.pp4549-4558

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).