On Small Signal Stability Early Warning Based on Measurement Data of WAMS

This paper proposes a power system small signal (dynamic) stability early warning approach based on Case-Based Reasoning (CBR) theory, which is an artificial intelligent method. According to measurement data of Wide Area Measurement System (WAMS), this approach is able to achieve following functions: In normal operation status, it can estimate small signal stability of power grid via CBR in historical database; while low frequency oscillation occurs, operation mode is rescheduled, according to the outputs of the approach, to improve small signal stability. Case studies based on simulations and field data recorded by WAMS of a regional power grid prove that the proposed approach is simple, feasible and effective. It is helpful to dispatchers for rapid decision when emergency occurs.