Data-Driven Online Optimization for Enhancing Power System Oscillation Damping

TL;DR

This paper introduces a data-driven online optimization approach to improve power system oscillation damping, demonstrating its feasibility and efficiency through simulations on standard power system models.

Contribution

It proposes a novel online oscillation damping optimization model that integrates data-driven methods with practical large-scale system considerations.

Findings

Verified effectiveness on 2-area 4-machine system

Demonstrated applicability on NETS-NYPS 68-bus system

Bridges online data analysis with complex power system optimization

Abstract

This paper reports an initial work on power system oscillation damping improvement using a data-driven online optimization method. An online oscillation damping optimization mod-el is proposed and formulated in a form solvable by the data-driven method. Key issues in the online optimization procedures, including the damping sensitivity identification method, its compatibility with the dispatch plans, as well as other practical issues in real large-scale system are discussed. Simulation results based on the 2-area 4-machine system, and the NETS-NYPS 68-bus system verify the feasibility and efficiency of the proposed method. The results also show the capability of the proposed method to bridge the gap between online data analysis and complex optimization for power system dynamics.