Wind connected distribution system with intelligent controller based compensators for power quality issues mitigation

Due to the widespread use of power electronics-based technology in distribution systems nowadays, power quality (PQ) has become a key aspect. A compensators were placed the system to manage the PQ issues. The controlling scheme of the compensators was consider as an important for mitigating the PQ problems. In the proposed model, four different compensators were utilized to improve the power quality of the system. The compensators consider for the proposed model were UPFC, DPFC, USSC and UPQC. A real-time benchmark dataset was generated under various power quality issues such as swell, interruptions, sag and harmonics. Based on the generated dataset, a deep learning intelligent controller model was designed, which controls the system to maintain stable power flow without any problem. The compensators were individually integrated into the system to analyze performance under various conditions such as swells, interruptions, sags and harmonics. The per-formance of the proposed intelligent controller was analyzed and compared with some other present techniques such as SVM and ANN. The proposed controller provides 0.97% accuracy, and the compensators provide low harmonics content that appeared as DPFC have 0.00772%, the USSC have 0.00529%, the UPFC have 0.00340%, and the UPQC have 0.00193%. These demonstrate the proposed controller provides low harmonic with highly secure and reliable operation.