Design of dual-dimensional controller based on multi-objective gravitational search optimization algorithm for amelioration of impact of oscillation in power generated by large-scale wind farms

This paper studies the impact of high penetration of wind generation technology on dynamic stability of power networks. A mathematical model of a multi-machine power system, including Large-scale Wind Power Generation System (LWPGS) incorporating active power oscillation due to tower shadow and wind shear phenomena is developed. Based on this model, an extended Small-Signal Scrutiny (SSS) procedure to study the impact of oscillatory modes on mechanical vibrations is proposed. The critical operating points that can be dangerous for power system performance are detected. The study is based on modified 16-machine 5-area network with lightly damped electromechanical modes. A dual-dimensional controller for LWPGS is proposed. The first and second dimensions of the designed controller are based on wide-area and local signals, respectively. Selection of the best input of the LWPGS is based on Singular Value Decomposition (SVD) analysis, while the qualified remote control signal is found by geometric approach. Multi-Purpose Gravitational Search Algorithm (MPGSA) based on fuzzy decision making is applied for the coordinated design of LWPGS controller and accelerating power PNS (PNS2B) of the synchronous machines. The simulation results are presented to elucidate the effectiveness of the well-tuned damping controller of the LWPGS.