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Article overview
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Delay Aware Intelligent Transient Stability Assessment System | | James J.Q. Yu
; Albert Y.S. Lam
; David J. Hill
; Victor O.K. Li
; | | Date: |
21 Nov 2017 | | Abstract: | Transient stability assessment is a critical tool for power system design and
operation. With the emerging advanced synchrophasor measurement techniques,
machine learning methods are playing an increasingly important role in power
system stability assessment. However, most existing research makes a strong
assumption that the measurement data transmission delay is negligible. In this
paper, we focus on investigating the influence of communication delay on
synchrophasor-based transient stability assessment. In particular, we develop a
delay aware intelligent system to address this issue. By utilizing an ensemble
of multiple long short-term memory networks, the proposed system can make early
assessments to achieve a much shorter response time by utilizing incomplete
system variable measurements. Compared with existing work, our system is able
to make accurate assessments with a significantly improved efficiency. We
perform numerous case studies to demonstrate the superiority of the proposed
intelligent system, in which accurate assessments can be developed with time
one third less than state-of-the-art methodologies. Moreover, the simulations
indicate that noise in the measurements has trivial impact on the assessment
performance, demonstrating the robustness of the proposed system. | | Source: | arXiv, 1711.7651 | | Services: | Forum | Review | PDF | Favorites | |
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