Electromechanical mode shape estimation based on transfer function identification using PMU measurem

Electromechanical - 1 Electromechanical Mode Shape Estimation Based on Transfer Function Identification Using PMU Measurements N Zhou Senior Member

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1 Abstract – Power system mode shapes are a key indication of how dynamic components participate in low-frequency oscilla- tions. Traditionally, mode shapes are calculated from a linearized dynamic model. For large-scale power systems, obtaining accu- rate dynamic models is very difficult. Therefore, measurement- based mode shape estimation methods have certain advantages, especially for the application of real-time small signal stability monitoring. In this paper, a measurement-based mode shape identification method is proposed. The general relationship be- tween transfer function (TF) and mode shape is derived. As an example, a least square (LS) method is implemented to estimate mode shape using an autoregressive exogenous (ARX) model. The performance of the proposed method is evaluated by Monte- Carlo studies using simulation data from a 17-machine model. The results indicate the validity of the proposed method in esti- mating mode shapes with reasonably good accuracy. 1 Index Terms – Electromechanical dynamics, mode shape, small signal stability, synchronized phasor measurements, system identification. I. INTRODUCTION AND BACKGROUND LECTROMECHANICAL oscillations exist in power sys- tems [1]. If the oscillations are not well damped, the magnitude of oscillation will grow and may eventually cause system breakup [2]. This problem is known as the small signal stability problem. Modes and mode shapes are key parameters describing the This work is supported by the U.S. Department of Energy Consortium for Electric Reliability Technology Solutions (CERTS). The Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. Ning Zhou is with Pacific Northwest National Lab, Richland, WA 99352, USA (e-mail: [email protected]). Zhenyu Huang is with Pacific Northwest National Lab, Richland, WA 99352, USA (e-mail: [email protected]). Luke Dosiek is with the University of Wyoming, Laramie, WY 82071, USA (e-mail: [email protected] ). Dan Trudnowski is with Montana Tech of The University of Montana, Butte, MT 59701, USA (e-mail: [email protected]). John W. Pierre is with the University of Wyoming, Laramie, WY 82071, USA (e-mail: [email protected]). oscillations. Modes describe the system’s oscillation frequen- cy and damping behavior. Mode shapes describe the relative participation of state variables in a particular mode. They pro- vide vital information for improving system stability and re- liability. With the deployment of phasor measurement units (PMU), the global positioning system (GPS) synchronized phasor data have become an important resource for studying and monitor- ing power system small-signal stability. Mode estimation me- thods based on measurement data have been extensively stu- died [3]-[9]. The focus of this paper is placed on the mea- surement-based mode shape estimation [10, 11]. Compared to the traditional model-based eigenvalue analysis methods [1, 12], measurement-based methods do not require system dy- namic models. Obtaining accurate dynamic models for real-
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This note was uploaded on 01/29/2011 for the course ENGR 52 taught by Professor Mcmillan during the Spring '10 term at Baylor Med.

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Electromechanical - 1 Electromechanical Mode Shape Estimation Based on Transfer Function Identification Using PMU Measurements N Zhou Senior Member

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