A Data-Driven Energy Storage System-Based Algorithm for Monitoring the Small-Signal Stability of Power Grids with Volatile Wind Power

TL;DR

This paper introduces a data-driven ESS-based algorithm that improves real-time small-signal stability monitoring in power grids with high wind power penetration by smoothing fluctuations and accurately estimating inter-area modes.

Contribution

It presents a novel algorithm combining ESS and WAMS technologies to enhance stability monitoring in grids with volatile wind power, a significant advancement over existing methods.

Findings

Effective smoothing of wind power fluctuations in near real-time

Accurate estimation of inter-area mode properties

Improved stability monitoring demonstrated on IEEE 68-bus system

Abstract

In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area modes that are closely related to the system's inherent stability characteristics, a novel algorithm that leverages on recent advances in wide-area measurement systems (WAMSs) and ESS technologies is developed. It is shown that the proposed approach can smooth the wind power fluctuations in near real-time using a small additional ESS capacity and thus significantly enhance the monitoring of small-signal stability. Dynamic Monte Carlo simulations on the IEEE 68-bus system are used to illustrate the effectiveness of the proposed algorithm in smoothing wind power and estimating the inter-area mode statistical properties.