Data-Driven Subsynchronous Oscillation Suppression for Renewable Energy Integrated Power Systems Based on Koopman Operator

TL;DR

This paper introduces a data-driven control method using Koopman operator theory to suppress subsynchronous oscillations in power systems with high renewable energy penetration, enhancing stability and robustness.

Contribution

It develops a Koopman-based linear predictive control framework that accurately models nonlinear dynamics for effective SSO suppression in renewable-integrated power systems.

Findings

Effective suppression of SSOs demonstrated in case studies.

Controller outperforms existing methods in robustness and adaptability.

Provides a data-driven approach avoiding complex system modeling.

Abstract

Recently, subsynchronous oscillations (SSOs) have emerged frequently worldwide, with the high penetration of renewable power generation in modern power systems. The SSO introduced by renewables has become a prominent new stability problem, seriously threatening the stable operation of systems. This paper proposes a data-driven dynamic optimal controller for renewable energy integrated power systems, to suppress SSOs with the control of renewables. The challenges of the controller design are the nonlinearity, complexity and hard accessibility of the system models. Using Koopman operator, the system dynamics are accurately extracted from data and utilized to the linear model predictive control (MPC). Firstly, the globally linear representation of the system dynamics is obtained by lifting, and the key states are selected as control signals by analyzing Koopman participation factors. Subsequently, augmented with the control term, the Koopman linear parameter-varying predictor of the controlled system is constructed. Finally, using MPC, the proposed controller computes control signals online in a moving horizon fashion. Case studies show that the proposed controller is effective, adaptive and robust in various conditions, surpassing other controllers with reliable control performance.