Power quality improvement of grid-connected solar power plant systems using a novel fractional order proportional integral derivative controller technique

Abstract

Recently, there has been a push to integrate renewable energy system (RES) into grid-connected load system in enhancing reliability and reducing losses. However, integrating these systems introduces power quality (PQ) issues, especially with non-linear, critical, and imbalanced loads. Addressing this, a hybrid mantis search-reptile search algorithm (HMS-RSA) combined with a unified power quality conditioner (UPQC) to mitigate PQ problems related to current and voltages in RES systems. In other words, the UPQC, enhanced by fractional order proportional integral derivative controller parameters tuned using the proposed HMS-RSA assists in enhancing the power quality. The approach has been validated by connecting a non-linear load to the system, which typically creates PQ issues. The proposed method is implemented in MATLAB/Simulink and their performance is analysed in three scenarios, such as sag, swell, and disturbance, and the total harmonic distortion is evaluated to quantify improvements in PQ. Finally, the proposed method is compared with existing approaches, such as ant colony optimization (ACO), artificial bee colony optimization (ABC), and bacterial foraging optimization (BFO). The method also outperforms ACO, ABC, and BFO in terms of convergence speed and effectiveness in mitigating PQ issues.