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.

%B IEEE Transactions on Power Systems %P 1 - 11 %8 08/2015 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2015.2456919 %0 Conference Paper %B 2015 IEEE Power & Energy Society General Meeting2015 IEEE Power & Energy Society General Meeting %D 2015 %T Time-localization of forced oscillations in power systems %A Jim Follum %A John W. Pierre %K AA09-002 %X In power systems forced oscillations occur, and identification of these oscillations is important for the proper operation of the system. Two of the parameters of interest in analyzing and addressing forced oscillations are the starting and ending points. To obtain estimates of these parameters, this paper proposes a time-localization algorithm based on the geometric analysis of the sample cross-correlation between the measured data and a complex sinusoid at the frequency of the forced oscillation. Results from simulated and measured synchrophasor data demonstrate the algorithm's ability to accurately estimate the starting and ending points of forced oscillations. %B 2015 IEEE Power & Energy Society General Meeting2015 IEEE Power & Energy Society General Meeting %I IEEE %C Denver, CO, USA %P 1 - 5 %8 07/2015 %R 10.1109/PESGM.2015.7286129 %0 Journal Article %J Electric Power Components and Systems %D 2013 %T A Generalized Subspace Least Mean Square Method for High-resolution Accurate Estimation of Power System Oscillation Modes %A Peng Zhang %A Ning Zhou %A Ali Abdollahi %K AA09-002 %K AARD %K Automatic Switchable Network (ASN) %K oscillations %XA generalized subspace least mean square method is presented for accurate and robust estimation of oscillation modes from exponentially damped power system signals. The method is based on the orthogonality of signal and noise eigenvectors of the signal autocorrelation matrix. Performance of the proposed method is evaluated using Monte Carlo simulation and compared with the Prony method. Test results show that the generalized subspace least mean square method is highly resilient to noise and significantly dominates the Prony method in tracking power system modes under noisy environments.

%B Electric Power Components and Systems %V 41 %P 1205 - 1212 %8 09/2013 %N 12 %! Electric Power Components and Systems %R 10.1080/15325008.2013.807896 %0 Conference Paper %B 2011 North American Power Symposium (NAPS 2011) %D 2011 %T Evaluation of mode estimation accuracy for small-signal stability analysis %A Jim Follum %A Ning Zhou %A John W. Pierre %K AA09-002 %K AARD %K Automatic Switchable Network (ASN) %K load modeling %K power system monitoring %X This paper proposes a method for determining electromechanical mode estimate accuracy by relating mode estimate error to residual values. Mode frequency and damping ratio were estimated using Prony analysis and residuals were calculated for a 17-machine model with varying levels of load noise. Mode estimate error and residuals were found to increase proportionally to each other as noise values were increased, revealing a distinctly linear relationship. The use of these results to develop appropriate confidence in models is discussed. With the relationship established, a method of predicting mode estimate error values based on residuals in the western North American power system (wNAPS) was developed. The potential of this method to evaluate the confidence level of mode estimates is examined. %B 2011 North American Power Symposium (NAPS 2011) %I IEEE %C Boston, MA, USA %P 1 - 7 %8 08/2011 %@ 978-1-4577-0417-8 %R 10.1109/NAPS.2011.6024893 %0 Conference Paper %B IEEE Power and Energy Society (PES) General Meeting %D 2011 %T A modified stepwise linear regression method for estimating modal sensitivity %A Ning Zhou %A Zhenyu Huang %A Francis K. Tuffner %A Dan Trudnowski %A William A. Mittelstadt %K AA09-002 %K AARD %K Automatic Switchable Network (ASN) %K phasor measurement units (PMUs) %K power system reliability %XSmall signal stability problems are one of the major threats to grid stability and reliability. Low damping of inter area modes is usually considered to be a result of heavy power transfer over long distances. This paper proposes a modified stepwise regression method to estimate the modal sensitivity with respect to power flow on the transmission lines based on measurement. This sensitivity is used to identify dominant transmission lines, whose power flow has significant influence on the inter-area modal damping. It is shown through simulation study that the proposed method can effectively estimate the modal sensitivity with respect to line power flow. This, in turn, provides insight on how to improve damping through adjusting tie line flow.

%B IEEE Power and Energy Society (PES) General Meeting %I IEEE %C Detroit, MI, USA %P 1 - 7 %8 07/2011 %@ 978-1-4577-1000-1 %R 10.1109/PES.2011.6039795