Retuning control parameters based on damping assessment

This paper presents a new approach for tuning damping control parameters to improve large-signal dynamic performance of power systems. It follows two steps, damping assessment and parameter optimization. Prony analysis based on single machine equivalent (SIME) is used for identifying the critical mode and corresponding damping ratio. The damping ratio is an important index for control effect in both small and large signal analysis. If the system is poorly damped after a large disturbance, genetic algorithm (GA) combing with damping assessment procedure as part of the individual evaluation is applied for retuning the control parameters. Test results show that damping assessment extract key information from multi-machine swing curve correctly; the optimized control provides good damping to power system oscillations induced by severe disturbance and makes the system meet preassigned damping performance criterion in large-signal analysis.