A multi-signal least-squares-based optimization technique for the identification of power system oscillatory modes

In this paper, a multi-signal identification technique is developed to estimate oscillatory modes contained in power system responses. The proposed technique utilizes least-squares optimization to analyze simultaneously several system measurements and determine close-to-real-time the modal parameters of the examined power system. The Monte Carlo method is applied to synthetic signals to thoroughly quantify the impact of several parameters on the accuracy of the proposed technique and comparisons with conventional identification techniques are performed. The accuracy of the proposed method is also validated using simulated responses obtained from a combined transmission-distribution network. Finally, the scalability of the proposed technique is demonstrated using power hardware-in-the-loop experiments.