Power flow management and control using PSO-PID and fuzzy logic controllers for autonomous solar and wind hybrid systems

The growing demand for sustainable energy has made solar and wind integration a key solution for autonomous power systems, though the inherent intermittency of these sources poses stability challenges. This study proposes a hybrid control framework combining Particle Swarm Optimization (PSO)-tuned proportional-integral-derivative (PID) controllers with Fuzzy Logic Controllers (FLC) to optimize energy production, minimize power losses and enhance voltage stability. The PSO dynamically tunes PID parameters to ensure robust performance under varying conditions, while the FLC regulates power distribution based on real-time inputs such as solar irradiance, wind speed and load demands. Simulations of a standalone hybrid energy model demonstrated 30% improvement in voltage stability, 28.9% reduction in power losses and 37.9% increase in overall efficiency. These results confirm the proposed system’s effectiveness in managing power flow and maintaining dependable operation under fluctuating renewable energy inputs. This approach highlights the potential of PSO-PID and FLC integration for reliable and efficient energy utilization in autonomous hybrid systems.