Combining Trajectory Data With Analytical Lyapunov Functions for Improved Region of Attraction Estimation

Author(s)

Fernandes, Lucas L. ; Jones, Morgan ; Alberto, Luis ; Peet, Matthew ; Dotta, Daniel

• Document type: Journal article
• Source: IEEE CONTROL SYSTEMS LETTERS; v. 7, p. 6-pg., 2022-06-30.

Abstract

The increasing uptake of inverter based resources (IBRs) has resulted in many new challenges for power system operators around the world. The high level of complexity of IBR generators makes accurate classical model-based stability analysis a difficult task. This letter proposes a novel methodology for solving the problem of estimating the Region of Attraction (ROA) of a nonlinear system by combining classical model based methods with modern data driven methods. Our method yields certifiable inner approximations of the ROA, typical to that of model based methods, but also harnesses trajectory data to yield an improved accurate ROA estimation. The method is carried out by using analytical Lyapunov functions, such as energy functions, in combination with data that is used to fit a converse Lyapunov function. Our methodology is independent of the function fitting method used. In this letter, for implementation purposes, we use Bernstein polynomials to function fit. Several numerical examples of ROA estimation are provided, including the Single Machine Infinite Bus (SMIB) system, a three machine system and the Van-der-Pol system. (AU)

• FAPESP's process: 18/07375-3 - Power system operation with high penetration of low inertia generation
• Grantee: Daniel Dotta
• Support Opportunities: Scholarships abroad - Research
• FAPESP's process: 19/10033-0 - Development of data-driven metodology for improvement of pperation of EPS with high penetration of wind/solar generation
• Grantee: Daniel Dotta
• Support Opportunities: Regular Research Grants