Power System Oscillation Mode Prediction Data

This paper utilizes modern statistical and machine learning methodology to track oscillation modes in complex power engineering systems. The damping ratio of the electromechanical oscillation mode is formulated as a function of power of the generators and loads as well as bus voltage magnitudes in the entire power system. The celebrated Lasso algorithm is implemented to solve this high-dimension modeling problem. By the nature of the $L_1$ design, the Lasso algorithm can automatically render a sparse solution, and by eliminating redundant features, it provides desirable prediction power. The resultant model processes a simple structure, and it is easily interpretable. The precision of our sparse modeling framework is demonstrated in the context of an IEEE 50-Generator 145-Bus power network.