  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.
