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Modified Eigen-Decomposition-Based Interval Analysis (MEDIA) for Power System Dynamic State Estimation
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DOI：10.1109/TPWRS.2023.3299463.png)
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Abstract
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TheBayesian approach has been used for the dynamic state estimation (DSE) of a power system. However, due to the complexity of noise resources, it is difficult to quantify measurement and process noise using probability density functions (PDFs). To overcome the difficulty, the authors of this article propose a modified eigen-decomposition-based interval analysis (MEDIA) method, which employs bounds instead of PDFs to quantify the noise, and uses the eigen decomposition method to reduce the negative impact of the overestimation problem. Using the simulation data generated from IEEE 16-machine and IEEE 10-machine systems, it is shown that the proposed MEDIA method can estimate the hard boundaries of dynamic states in real time. Comparison with the forward-backward propagation method and the extended set-membership filter also shows that the proposedMEDIAmethod performs better by providing narrower boundaries in the DSE.
Keywords:
Dynamic state estimation
eigen decomposition
interval analysis
power system
state estimation
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7.2
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1.1W
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5.0W
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