Distributed generation (DG) systems are increasingly integrated into modern power networks through power-electronic interfaces. However, the presence of nonlinear loads and power-electronic converters introduces harmonic distortion, which can significantly degrade power quality, particularly in three-wire systems. This study investigates harmonic mitigation in a hybrid renewable DG system incorporating solar, wind, fuel-cell-based generation, and grid-connected operation using a Unified Power Quality Conditioner (UPQC). An Improved Bat Search–Moth Flame Optimization (IBSMFO) based control strategy is proposed for optimizing the proportional-integral (PI) controller parameters of the UPQC. The IBSMFO algorithm combines the search characteristics of the Improved Bat Search Algorithm (IBSA) with the Moth Flame Optimization Algorithm (MFOA) to minimize the selected error-based objective function and enhance the dynamic performance of the compensation system. The proposed UPQC is evaluated under ideal and non-ideal source-voltage conditions with nonlinear loads. Simulation results demonstrate effective mitigation of voltage and current harmonics and improved power quality. In particular, the source-current THD is reduced to 4.03% under the operating conditions considered, while a minimum THD of 1.01% is achieved under the corresponding compensation condition. The results confirm that the proposed IBSMFO-optimized UPQC provides effective harmonic compensation and improved power quality performance in hybrid renewable DG systems.

This paper presents a comprehensive analysis of power quality in a distributed generation (DG) system utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) and a Unified Power Quality Conditioner (UPQC). The integration of distributed generation resources, such as solar and wind power, into the electrical grid has posed significant challenges related to power quality, including voltage sags, swells, harmonics, and reactive power issues. To address these challenges, the proposed system employs ANFIS for adaptive and precise control, enhancing the performance and stability of the DG system. The UPQC is integrated to mitigate power quality disturbances by simultaneously compensating for voltage and current harmonics and providing voltage regulation. Detailed simulations are conducted to evaluate the effectiveness of the ANFIS-based control strategy and the performance of the UPQC in various operating conditions. The results demonstrate significant improvements in power quality metrics, highlighting the potential of this approach for efficient and reliable integration of distributed generation into modern power systems. The simulation findings are thoroughly examined across multiple operational scenarios and compared to Fuzzy logic control. Furthermore, the proposed system's efficacy is validated in accordance with the IEEE 1547 and IEEE 519 standards, demonstrating its performance and compliance with industrial needs.