Power Quality Enhancement in Shipboard Microgrids

Power management in shipboard electrical systems is comparable to the difficulty of ensuring sufficient power quality in an island microgrid. In order to guarantee its appropriateness for marine applications, this paper presents an inverter control system optimized for a 13 IEEE node feeder microgrid that is built on artificial neural networks (ANNs). Reducing total harmonic distortion (THD), voltage fluctuations, and phase angle variations is the main goal in order to improve power quality and system stability during grid-connected and islanded operations. To maximize the infusion of electricity from a photovoltaic (PV) system, the suggested controller, which is based on ANN, controls the inverter through the dynamic adjustment of control parameters. By comparing it to more conventional proportional-integral (PI) controllers, Matlab-Simulink verifies the system’s performance. The results show that the controller based on ANN considerably enhances power quality in marine microgrids by regulating voltage, reducing transient THD, and maintaining stable phase angles. This study proves that compared to traditional controllers, ANN-based control offers superior responsiveness, flexibility, and efficiency. In order to improve operational efficiency and power stability under islanded conditions, the suggested technique provides a dependable solution for shipboard microgrids.