An enhanced approach for power quality improvement of unified power quality conditioner connected wind energy conversion system

This manuscript proposed a hybrid system for enhancing the control strategy of a unified power quality conditioner connected to a wind energy conversion system. The proposed method is combined with honey badger algorithm (HBA) and reptile search algorithm (RSA). Therefore, it is known as the Enhanced HBA (EnHBA) technique. The key aim of the EnHBA technique is to alleviating the PQ issue exhibited in the WECS. The EnHBA approach is utilized in the non-linear load condition to find the best solutions from the available searching space in light of the goal function and generates the output. During the load variation conditions the EnHBA technique manages the loss of power, total harmonic distortion (THD), and voltage instability issue respectively. In this way, the PQ system performances improved and moreover, the various qualities decreased with the support of the EnHBA method. The EnHBA techniques' performance is validated through the MATLAB platform and the implementation is calculated with the existing techniques. The method EnHBA technique displays better outcomes in all approaches like, particle swarm optimization, whale optimization algorithm and singular spectrum analysis (SSA). The proposed method's voltage sag and swell are lowered to 14% and 15%, respectively. The THD of the En HBA method is 10%, which is lesser than other existing PSO, WOA, and SSA methods. This paper proposes an Enhanced HBA (EnHBA) technique, integrating Honey Badger Algorithm (HBA) and Reptile Search Algorithm (RSA), to improve the control strategy of a unified power quality conditioner connected to a wind energy conversion system. The EnHBA method effectively addresses power quality issues, THD, and voltage instability under load variation conditions. Validated through MATLAB, EnHBA demonstrates superior performance, reducing voltage sag and swell to 14% and 15%, respectively, and achieving THD of 10%, outperforming PSO, WOA, and SSA methods. image