Impact of FACTS Devices on Reactive Power Optimization in Hybrid Renewable-Grid Networks - Rajasree, R.; Lakshmi, D.; Batumalay, M. (Journal of Applied Data Sciences, 2025)
Renewable energy integration with conventional electric power networks creates power-quality and stability difficulties because of their inherent volatility. The reliability improvement of hybrid renewable-grid systems depends heavily on reactive power optimization for achieving voltage control as well as loss reduction. The research explores the application of Flexible AC Transmission System (FACTS) devices with special emphasis on Distribution Static Compensator (DSTATCOM) devices for distributing reactive power compensation at the distribution level. The optimization process utilizes Particle Swarm Optimization (PSO) because it demonstrates both quick convergence and strong abilities for global search within nonlinear systems. The PSO algorithm functions to determine the perfect settings of the DSTATCOM device that enables voltage regulation within safety bounds and improves power factor performance. The hybrid system connects PV array components with wind turbines for power management together with the main grid while dealing with fluctuating load requirements. Under optimized conditions simulation output shows that DSTATCOM reduces reactive power requirements in substantial amounts. DSTATCOM's implementation enables the system to achieve better voltage security together with diminished power losses and superior load power factor levels. Detailed research shows that DSTATCOM proves efficient while being attached to the main grid for real-time compensation operations. The PSO system enables it to function efficiently throughout changing conditions of power generation and load requirements. Smart grid efficiency along with resilience advances because of the combined operation of FACTS devices and swarm intelligence methods. Through its proposed method the system ensures lasting grid sustainability and manages renewable resources intermittency effectively for process innovation.