An intelligent sensor to monitor power system stability, performance and diagnose failures

An intelligent sensor is proposed to (1) monitor, in real time, the stability and performance, and (2) detect and isolate control loop failures in an interconnected power system. The sensor consists of an information preprocessor, a knowledge-base, and an inference engine. The information preprocessor is a set of signal-processing algorithms that extract, in real time, relevant features from the data such as steady-state deviation and the frequency and degree of damping of the critical modes. The knowledge-base is a set of rules governing the relation between these features and a set of goals, namely the measurement of performance, stability, and the source of control loop failures. The inference engine uses forward chaining to monitor stability and performance, and backward chaining to isolate failures. The usefulness of the sensor is confirmed by a real-time simulation of an interconnected power system