A Hybrid Marine Predator Sine Cosine Algorithm for Parameter Selection of Hybrid Active Power Filter

Power quality issues are handled very well by filter technologies. In recent years, the advancement of hybrid active power filters (HAPF) has been enhanced due to ease of control and flexibility as compared to other filter technologies. These filters are a beneficial asset for a power producer that requires a smooth filtered output of power. However, the design of these filters is a daunting task to perform. Often, metaheuristic algorithms are employed for dealing with this nonlinear optimization problem. In this work, a new hybrid metaheuristic algorithm (Marine Predator Algorithm and Sine Cosine Algorithm) has been proposed for selecting the best parameters for HAPF. The comparison of different algorithms for obtaining the HAPF parameters is also performed to show case efficacy of the proposed hybrid algorithm. It can be concluded that the proposed algorithm produces robust results and can be a potential tool for estimating the HAPF parameters. The confirmation of the performance of the proposed algorithm is conducted with the results of fitness statistical results, boxplots, and different numerical analyses.

Automated summary

Power quality issues can be effectively addressed using filter technologies. The development of hybrid active power filters (HAPF) has been improved due to their ease of control and flexibility. These filters are beneficial for power producers who need a stable and filtered power output. However, designing these filters is challenging and often requires metaheuristic algorithms. This study proposes a new hybrid metaheuristic algorithm (Marine Predator Algorithm and Sine Cosine Algorithm) to optimize the selection of HAPF parameters. The proposed algorithm demonstrates robust results and holds potential for estimation of HAPF parameters, as confirmed by fitness statistical results, boxplots, and numerical analyses.