This paper proposes a multidimensional recursive ambient modal analysis algorithm called recursive frequency domain decomposition (recursive FDD or RFDD). The method enables simultaneous processing of a large number of synchrophasor measurements for real-time ambient modal estimation. The method combines a previously proposed multidimensional block processing algorithm FDD with a single input recursive least square (RLS) algorithm into developing a new frequency domain multidimensional recursive algorithm. First, an auto-regressive model is fitted onto the sampled data of each signal using the time-domain RLS approach. Subsequent modal analysis is carried out in frequency domain in the spirit of FDD. The conventional FDD method uses non-parametric methods for power spectrum density (PSD) estimation. The proposed method in this paper by estimating PSD with a parametric method provides smoother PSD estimation which results in less standard deviation in RFDD estimates compared to FDD. The algorithm is tested on archived synchrophasor data from a real power system.

%B IEEE Transactions on Power Systems %V 32 %P 822 - 823 %8 01/2017 %N 1 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2016.2558466 %0 Journal Article %J IEEE Transactions on Power Systems %D 2016 %T Subsynchronous Resonance Monitoring Using Ambient High Speed Sensor Data %A Khalilinia, Hamed %A Venkatasubramanian, Vaithianathan %K AA13-004 %XThis paper proposes a framework for online monitoring of subsynchronous oscillations using ambient sensor data from high speed sampling devices such as digital fault recorders (DFRs). Ambient data is continuously available in the form of routine system responses to random load fluctuations. This paper shows the usefulness of ambient data for tracking the frequency, damping ratio and mode shape of torsional modes related to subsynchronous resonance (SSR). Frequency domain decomposition (FDD) and recursive least square (RLS) algorithms are tested for ambient monitoring of SSR modes. IEEE second SSR benchmark model is used as the study system. Nonlinear and linearized equations of this system are analyzed for testing the performance of measurement based methods and to compare their results with respective linearized system modes. It is shown that both electrical and mechanical signals can be used for the SSR monitoring while the torsional modes are more observable in mechanical signals such as generator speeds. In addition to estimating the frequency and damping ratio, torsional mode shapes can be identified by implementing FDD as a multi-dimensional method on the speeds of the masses of the turbine shaft. The algorithms are tested on an archived real system data set from a DFR.

%B IEEE Transactions on Power Systems %V 31 %P 1073 - 1083 %8 03/2016 %N 2 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2015.2425876 %0 Journal Article %J IEEE Transactions on Power Delivery %D 2015 %T Fast Frequency-Domain Decomposition for Ambient Oscillation Monitoring %A Khalilinia, Hamed %A Zhang, Lu %A Venkatasubramanian, Vaithianathan %K AA13-004 %K AARD %K CERTS %K RTGRM %X This paper proposes a multidimensional ambient oscillation monitoring algorithm denoted Fast Frequency Domain Decomposition (FFDD). Based on a new theoretical result, the algorithm is offered as an improvement over previously proposed Frequency Domain Decomposition (FDD) in that FFDD does not require time-consuming Singular Value Decomposition (SVD) and it does not require cross spectrum estimates. FFDD is useful for fast real-time ambient modal estimation of large number of synchrophasor measurements. Algorithm is tested on an archived event data from a real power system. %B IEEE Transactions on Power Delivery %P 1 - 1 %8 02/2015 %! IEEE Trans. Power Delivery %R 10.1109/TPWRD.2015.2394403 %0 Journal Article %J IEEE Transactions on Smart Grid %D 2015 %T Modal Analysis of Ambient PMU Measurements Using Orthogonal Wavelet Bases %A Khalilinia, Hamed %A Venkatasubramanian, Vaithianathan %K AA13-004 %K AARD %K CERTS %K RTGRM %X This paper proposes a new method, called wavelet scale decomposition, for modal analysis of ambient synchrophasor data using orthogonal wavelet bases. Wavelet formulation of the problem enables reliable estimation results even with short data analysis windows that are a few minutes long. Also, in addition to finding the mode frequency and damping ratio of oscillatory modes, the proposed method is able to estimate their mode shapes as well. The method is tested on some archived real phasor measurement unit data sets and on simulations from Kundur two area system. The results show that the proposed method is able to track damping ratio variations in power systems effectively with short analysis windows. %B IEEE Transactions on Smart Grid %P 1 - 1 %8 03/2015 %! IEEE Trans. Smart Grid %R 10.1109/TSG.2015.2410138