Power Distribution System Power Quality Enhancement with Custom Power Devices Utilizing Machine Learning Techniques

An issue with power quality is one that arises from an abrupt increase in an abnormal voltage, current, or frequency. Poor power quality or non-linear loads can lead to a distribution system’s voltage sag, swell, interruptions, harmonics, and transients, among other issues. Various compensating devices are utilized nowadays to enhance power quality. To provide quick, adaptable, and effective solutions for different power disturbances which include devices like DVR Voltage Re-storer and DSTATCOM are taking into consideration advancements in power electronic technologies like converter with various magnitudes. These tools rectify magnitude, current, source disturbances brought on by various defects and loads. In order to test it and lower total harmonic distortion, they are connected to the main distribution network using the IEEE 14 Bus standard. To improve power quality in the utility, the use of sophisticated instruments for power quality analysis is becoming more and more important every day. In order to reduce harmonics in bus voltages and bus currents, DSTATCOM and DVR employ optimal PI-based neural network techniques and linear regression techniques, which are analyzed and compared in this study.