Detection of Periodic Forced Oscillations in Power Systems

An algorithm for the detection and frequency estimation of periodic forced oscillations in power systems is proposed. The method operates by comparing the periodogram of synchrophasor measurements to a detection threshold. This threshold is established by deriving a general expression for the distribution of the periodogram and is related to the algorithm's probabilities of false alarm and detection. Unlike classic detection algorithms designed for use with white Gaussian noise, the proposed algorithm uses a detection threshold that varies with frequency to account for the colored nature of synchrophasor measurements. Further, a detection method based on multiple segments of data is also proposed to improve the algorithm's performance as a monitoring tool in the online environment. A design approach that helps to ensure that the best available probability of detection from any one detection segment is constantly increasing with the duration of the forced oscillation is also developed. Results from application of the detection algorithm to simulated and measured power system data suggest that the algorithm provides the expected detection performance and can be used to detect forced oscillations in practical monitoring of power systems.