Optimal damping for generalized unified power flow controller equipped single machine infinite bus system for...

Area of Science:

• Electrical Engineering
• Power Systems Engineering
• Control Systems

Background:

• Low frequency oscillations (LFOs) pose a significant threat to power system stability.
• Inadequate damping torque from the rotor exacerbates LFOs, arising from imbalances between mechanical input and electrical output.

Purpose of the Study:

• To investigate the efficacy of a generalized unified power flow controller (GUPFC) in mitigating LFOs within a single machine infinite bus (SMIB) system.
• To identify the optimal combination of damping controllers and optimization algorithms for enhanced LFO mitigation.

Main Methods:

• Utilized a third-generation Flexible AC Transmission System (FACTS) device, the GUPFC, for LFO damping.
• Integrated proportional-integral (PI) and lead-lag controllers with optimization algorithms: Grey Wolf Optimizer (GWO), Differential Evolution (DE), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Chaotic Whale Optimization Algorithm (CWOA).
• Conducted performance evaluations using time-domain simulations, eigenvalue analysis, Nyquist stability tests, and quantitative analysis, supplemented by non-parametric statistical tests (Kolmogorov-Smirnov and paired t-test).

Main Results:

• The GWO-tuned lead-lag controller significantly outperformed all other controller-optimizer pairings in mitigating LFOs.
• Comprehensive analysis confirmed the robustness and effectiveness of the proposed GUPFC-based damping strategy.
• Statistical tests validated the uniqueness and distribution characteristics of the optimization algorithms.

Conclusions:

• The GUPFC, particularly when optimized with the GWO-tuned lead-lag controller, provides a highly effective solution for suppressing low frequency oscillations in power systems.
• The study highlights the importance of advanced FACTS devices and sophisticated optimization techniques for enhancing power system reliability and stability.