Comparison between ABC and ACO: Tunning of On-Off MPPT for wind systems

Author:

Hannachi Marwa1ORCID,Elbeji Omessaad1ORCID,Benhamed Mouna1,Sbita Lassaad1

Affiliation:

1. PEESE (Processes, Energetics, Environments & Electrical Systems) Research Laboratory LR18ES34, Department of Electrical Engineering, National Engineering School of Gabes, Gabes, Tunisia

Abstract

In this work, a comparative study between two optimization algorithms for On-Off MPPT (Maximum Power Point Tracking) in wind power systems will be presented. The two optimizers considered in this paper are: the artificial bee colony algorithm (ABC) and the ant colony algorithms (ACO). Both of these optimization techniques are formulated to minimize different performance such as Integral Absolute Error (IAE) to determine optimal PI regulator values. In order to improve the performance and robustness properties of the proposed PI, the two tuning mechanisms are used in the optimization part. The system is modeled and tested under MATLAB/SIMULINK environment. The comparison of the performances, either by the test function or by MPPT, between these two optimizers shows the efficiency and superiority of the ABC-based approach proposed in terms of the qualities of the solution obtained, the speed of convergence, and the simplicity compared to ACO.

Publisher

SAGE Publications

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

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