01425nas a2200193 4500008003900000022001400039245005500053210005500108260001200163300001000175520083500185653001301020100001701033700002601050700003801076700001701114700002501131856007501156 2015 d a0885-895000aFast SVD Computations for Synchrophasor Algorithms0 aFast SVD Computations for Synchrophasor Algorithms c03/2015 a1 - 23 aMany 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).10aAA13-0041 aWu, Tianying1 aSarmadi, Arash, Nezam1 aVenkatasubramanian, Vaithianathan1 aPothen, Alex1 aKalyanaraman, Ananth uhttps://certs.lbl.gov/publications/fast-svd-computations-synchrophasor01809nas a2200193 4500008003900000022001400039245006700053210006600120260001200186300001000198520122700208653001301435653000901448653001001457653001001467100002601477700003801503856007401541 2015 d a0885-895000aInter-Area Resonance in Power Systems From Forced Oscillations0 aInterArea Resonance in Power Systems From Forced Oscillations c02/2015 a1 - 93 aThis 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.10aAA13-00410aAARD10aCERTS10aRTGRM1 aSarmadi, Arash, Nezam1 aVenkatasubramanian, Vaithianathan uhttps://certs.lbl.gov/publications/inter-area-resonance-power-systems01629nas a2200217 4500008003900000022001400039245009800053210006900151260001200220300001400232490000700246520093600253653001301189653000901202653001001211653001701221653003601238100002601274700003801300856007301338 2014 d a0885-895000aElectromechanical Mode Estimation Using Recursive Adaptive Stochastic Subspace Identification0 aElectromechanical Mode Estimation Using Recursive Adaptive Stoch c01/2014 a349 - 3580 v293 aMeasurement 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.10aAA13-00410aAARD10aCERTS10aoscillations10aphasor measurement units (PMUs)1 aSarmadi, Arash, Nezam1 aVenkatasubramanian, Vaithianathan uhttps://certs.lbl.gov/publications/electromechanical-mode-estimation01705nas a2200217 4500008003900000022001400039245008300053210006900136260001200205300001100217520101800228653001301246653000901259653001001268653001701278653003601295100001701331700002601348700003801374856007501412 2014 d a0885-895000aTwo-Level Ambient Oscillation Modal Estimation From Synchrophasor Measurements0 aTwoLevel Ambient Oscillation Modal Estimation From Synchrophasor c12/2014 a1 - 103 aThis 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.10aAA13-00410aAARD10aCERTS10aoscillations10aphasor measurement units (PMUs)1 aNing, Jiawei1 aSarmadi, Arash, Nezam1 aVenkatasubramanian, Vaithianathan uhttps://certs.lbl.gov/publications/two-level-ambient-oscillation-modal