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 Power Systems %D 2015 %T Fast SVD Computations for Synchrophasor Algorithms %A Wu, Tianying %A S. Arash Nezam Sarmadi %A Venkatasubramanian, Vaithianathan %A Pothen, Alex %A Kalyanaraman, Ananth %K AA13-004 %X Many singular value decomposition (SVD) problems in power system computations require only a few largest singular values of a large-scale matrix for the analysis. This letter introduces two fast SVD approaches recently developed in other domains to power systems for speeding up phasor measurement unit (PMU) based online applications. The first method is a randomized SVD algorithm that accelerates computation by introducing a low-rank approximation of a given matrix through randomness. The second method is the augmented Lanczos bidiagonalization, an iterative Krylov subspace technique that computes sequences of projections of a given matrix onto low-dimensional subspaces. Both approaches are illustrated on SVD evaluation within an ambient oscillation monitoring algorithm, namely stochastic subspace identification (SSI). %B IEEE Transactions on Power Systems %P 1 - 2 %8 03/2015 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2015.2412679 %0 Journal Article %J IEEE Transactions on Power Systems %D 2015 %T Inter-Area Resonance in Power Systems From Forced Oscillations %A S. Arash Nezam Sarmadi %A Venkatasubramanian, Vaithianathan %K AA13-004 %K AARD %K CERTS %K RTGRM %X This paper discusses a recent event in the western American power system when a forced oscillation was observed at a frequency that was close to a well-known 0.38-Hz inter-area electromechanical mode frequency of the western system. The event motivates a systematic investigation in this paper on the possibility of resonant interactions between forced oscillations and electromechanical inter-area oscillatory modes in power systems. When the natural oscillatory mode of a power system is poorly damped, and the forced oscillation occurs at a frequency close to system mode frequency at critical locations for the mode, resonance is observed in simulation test cases of the paper. It is shown that the MW oscillations on tie-lines can be as high as 477 MW from a 10-MW forced oscillation in Kundur test system because of resonance. This paper discusses the underlying system conditions and effects as related to resonance in power systems caused by forced oscillations and discusses ways to detect such scenarios using synchrophasors. Simulated data from Kundur two-area test power system as well as measurement data from western American power system are used to study the effect of forced oscillations in power systems. %B IEEE Transactions on Power Systems %P 1 - 9 %8 02/2015 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2015.2400133 %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 %0 Journal Article %J IEEE Transactions on Power Systems %D 2014 %T Electromechanical Mode Estimation Using Recursive Adaptive Stochastic Subspace Identification %A S. Arash Nezam Sarmadi %A Venkatasubramanian, Vaithianathan %K AA13-004 %K AARD %K CERTS %K oscillations %K phasor measurement units (PMUs) %X Measurement based algorithms for estimating low-frequency electromechanical modes serve as useful practical methods to monitor the modal properties of power system oscillations in real-time. This paper proposes a recursive adaptive stochastic subspace identification (RASSI) algorithm for online monitoring of power system modes using wide-area synchrophasor data. The proposed method gives an online estimation of mode frequency and damping ratio as well as mode shapes using multi-channel measurement data. It exploits both the accuracy of subspace identification and fast computational capability of recursive methods. An adaptive method is proposed to enable fast tracking of modal evolution under poorly damped conditions together with low estimation variance under quasi-steady-state conditions. The algorithms are tested using simulated data from Kundur two-area test power system as well as measured data from real systems. %B IEEE Transactions on Power Systems %V 29 %P 349 - 358 %8 01/2014 %N 1 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2013.2281004 %0 Journal Article %J IEEE Transactions on Power Systems %D 2014 %T Two-Level Ambient Oscillation Modal Estimation From Synchrophasor Measurements %A Ning, Jiawei %A S. Arash Nezam Sarmadi %A Venkatasubramanian, Vaithianathan %K AA13-004 %K AARD %K CERTS %K oscillations %K phasor measurement units (PMUs) %X This paper proposes a decentralized two-level structure for real-time modal estimation of large power systems using ambient synchrophasor data. It introduces two distributed algorithms that fit the structure well, namely, 1) decentralized frequency domain decomposition and 2) decentralized recursive stochastic subspace identification. As opposed to present-day oscillation monitoring methodologies, the bulk of the algorithmic computations is done locally at the substation level in the two-level framework. Substation modal estimates are sent to the control center where they are grouped, analyzed, and combined to extract system modal properties of local and inter-area modes. The framework and the proposed algorithms provide a scalable methodology for handling oscillation monitoring from a large number of substations efficiently. The two-level structure and the two decentralized algorithms are tested using simulated data from standard test systems and from archived real power system synchrophasor data. %B IEEE Transactions on Power Systems %P 1 - 10 %8 12/2014 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2014.2373172 %0 Journal Article %J IEEE Transactions on Power Systems %D 2013 %T Oscillation modal analysis from ambient synchrophasor data using distributed frequency domain optimization %A Ning, Jiawei %A Pan, Xueping %A Venkatasubramanian, Vaithianathan %K AA13-004 %K AARD %K CERTS %K oscillations %K phasor measurement units (PMUs) %X This paper provides a distributed frequency domain algorithm for real-time modal estimation of large power systems using ambient synchrophasor data. By dividing the computation between a supervisory central computer and local optimizations at the substation level, the algorithm efficiently estimates multiple dominant mode frequencies, damping ratios and mode shapes from wide-area power system measurements. The algorithm, called distributed frequency domain optimization, is tested on known test systems and archived real power system data from eastern and western power systems. %B IEEE Transactions on Power Systems %V 28 %P 1960 - 1968 %8 05/2013 %N 2 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2013.2248028