PMU-Based Estimation of Dynamic State Jacobian Matrix and Dynamic System State Matrix in Ambient Conditions
arXiv:1706.01114 · doi:10.1109/TPWRS.2017.2712762
Abstract
In this paper, a hybrid measurement- and model-based 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.
To appear in IEEE Transactions on Power Systems
References in corpus (4)
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- Applying a formula for generator redispatch to damp interarea oscillations using synchrophasors
- Analytical Studies of Quasi Steady-State Model in Power System Long-Term Stability Analysis
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- WAMS-Based Model-Free Wide-Area Damping Control by Voltage Source Converters
- Online Measurement-Based Estimation of Dynamic System State Matrix in Ambient Conditions
- A Dynamic Response Recovery Framework Using Ambient Synchrophasor Data
- Embedding Power Flow into Machine Learning for Parameter and State Estimation
- Measurement-Based Estimation of System State Matrix for AC Power Systems with Integrated VSCs
- Inference of modes for linear stochastic processes
- Estimating Participation Factors and Mode Shapes for Electromechanical Oscillations in Ambient Conditions