Identification and Predictive Analysis of a Multi-Area WECC Power System Model Using Synchrophasors

Chavan, Govind; Weiss, Matthew; Chakrabortty, Aranya; Bhattacharya, Subhashish; Salazar, Armando; Ashrafi, Farrokh-Habibi

doi:10.1109/tsg.2016.2531637

Cited by 58 publications

(21 citation statements)

References 16 publications

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“…An aggregated five-machine dynamic equivalent electro-mechanical model of WECC power system using synchrophasor measurements is developed to bridge the gap aroused by the increasing penetration of renewable energy resources. These renewable energy resources will significantly change dynamic properties, inter-area oscillation characteristics and stability margins of WECC power systems in the near future [17]. However, this model is built from the perspective of the entire power system.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Representation of WECC Composite Load Model

Wang

et al. 2020

Journal of Modern Power Systems and Clean Energy

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Composite load model of Western Electricity Coordinating Council (WECC) is a newly developed load model that has drawn great interest from the industry. To analyze its dynamic characteristics with both mathematical and engineering rigors, a detailed mathematical model is needed. Although composite load model of WECC is available in commercial software as a module and its detailed block diagrams can be found in several public reports, there is no complete mathematical representation of the full model in literature. This paper addresses a challenging problem of deriving detailed mathematical representation of composite load model of WECC from its block diagrams. In particular, we have derived the mathematical representation of the new DER_A model. The developed mathematical model is verified using both MATLAB and PSS/E to show its effectiveness in representing composite load model of WECC. The derived mathematical representation serves as an important foundation for parameter identification, order reduction and other dynamic analysis.

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Section: Introductionmentioning

confidence: 99%

Mathematical Representation of WECC Composite Load Model

Wang

et al. 2020

Journal of Modern Power Systems and Clean Energy

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“…Specifically, the authors of [5] proposed a method to estimate the values of generator damping and/or inertia constants using estimates of system modes calculated from PMU measurements. The authors of [6] utilized the modes extracted from PMUs to estimate system parameters including inter-area transmission line impedances, intra-area Thevenin reactances, inertia and damping of the aggregated synchronous generators. The authors of [7] applied an extended Kalman filter to estimate the generator parameters using PMU data.…”

Section: Introductionmentioning

confidence: 99%

PMU-Based Estimation of Dynamic State Jacobian Matrix and Dynamic System State Matrix in Ambient Conditions

Wang

Białek

Turitsyn

2018

IEEE Trans. Power Syst.

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Abstract-In this paper, a hybrid measurement-and modelbased method is proposed which can estimate the dynamic state Jacobian matrix and the dynamic system state matrix in near real-time utilizing statistical properties extracted from PMU measurements. The proposed method can be used to detect and identify network topology changes that have not been reflected in an assumed network model. Additionally, an application of the estimated system state matrix in online dynamic stability monitoring is presented.Index Terms-dynamic state Jacobian matrix, dynamic system state matrix, phasor measurement units, topological error identification, online dynamic stability monitoring

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“…A number of recent works showed promising results in attacking this problem [3], [4], [5], [6], [7], [8], [9]. Here, we propose to extend the scope of existing works to the problem of extracting the dynamic state matrix from PMU measurements in a purely data-driven way, without assuming any knowledge of model parameters.…”

Section: Introductionmentioning

confidence: 99%

Online Learning of Power Transmission Dynamics

Lokhov

Vuffray

Shemetov

et al. 2018

2018 Power Systems Computation Conference (PSCC)

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We consider the problem of reconstructing the dynamic state matrix of transmission power grids from timestamped PMU measurements in the regime of ambient fluctuations. Using a maximum likelihood based approach, we construct a family of convex estimators that adapt to the structure of the problem depending on the available prior information. The proposed method is fully data-driven and does not assume any knowledge of system parameters. It can be implemented in near real-time and requires a small amount of data. Our learning algorithms can be used for model validation and calibration, and can also be applied to related problems of system stability, detection of forced oscillations, generation re-dispatch, as well as to the estimation of the system state.

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Identification and Predictive Analysis of a Multi-Area WECC Power System Model Using Synchrophasors

Cited by 58 publications

References 16 publications

Mathematical Representation of WECC Composite Load Model

Mathematical Representation of WECC Composite Load Model

PMU-Based Estimation of Dynamic State Jacobian Matrix and Dynamic System State Matrix in Ambient Conditions

Online Learning of Power Transmission Dynamics

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