This research paper proposes the new multi-criteria search based enhanced firefly algorithm for solving selective harmonic elimination in a multilevel inverter. This new enhanced firefly utilizes adaptive nature of social and cognitive components to find the global optima. To see the effectiveness of the proposed algorithm and for the evaluation of results, a three phase nine level cascaded multilevel inverter is used. It is compared with existing meta-heuristic algorithms namely particle swarm optimization and firefly algorithm to validate its effectiveness. Crucial parameters for optimization, including population size and number of iterations, are kept same for comparison. For comparison, total harmonic distortion and convergence behaviour of algorithms against various modulation index values are considered. Moreover, results have clearly indicated that the proposed algorithm has surpassed particle swarm optimization and firefly algorithms in terms of convergence behaviour by attaining lower fitness value in lesser number of iterations. Finally, the experimental validation of selective harmonic elimination in multi-level inverter is also performed and analyzed.
CITATION STYLE
Khizer, M., Liaquat, S., Zia, M. F., Kanukollu, S., Al-Durra, A., & Muyeen, S. M. (2023). Selective Harmonic Elimination in a Multilevel Inverter Using Multi-Criteria Search Enhanced Firefly Algorithm. IEEE Access, 11, 3706–3716. https://doi.org/10.1109/ACCESS.2023.3234918
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