Real-Time stability enhancement of DDPMSG-based tidal hybrid power systems using heuristic optimization

Abstract

Abstract In this research, we analyze the optimal configuration and stability issues associated with a tidal hybrid power system employing a Direct Drive Permanent Magnet Synchronous Generator (DDPMSG). The Tidal system has become unstable since the natural tidal pattern and wind power input have been disturbed. The use of a controller for the Unified Power Flow Controller (UPFC) makes the system stable. Stability analysis, which uses Eigen and Nyquist plots, is used to see how well the proposed controllers work. Additionally, it is evident that the regulator can be effectively calibrated when the variables significantly influence the system’s performance. So, to find the best output for the suggested controller, it is best to use heuristic optimization methods like the Differential Evolution Algorithm (DEA) and the Firefly Algorithm (FA), followed by hybrid FA. The results indicate that the hybrid FA-based system demonstrates enhanced stability, evidenced by increased performance in settling time, rising time, peak overshoot, and damping. The performance and durability assessment of the controller in question is executed using real-time data via OPAL-RT 5142, a digital simulation platform tailored for real-time applications.