A dynamic mode decomposition framework for global power system oscillation analysis
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 12 - Engineering
- Output identifier
- 217
- Type
- D - Journal article
- DOI
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10.1109/TPWRS.2014.2368078
- Title of journal
- IEEE Transactions on Power Systems
- Article number
- -
- First page
- 2902
- Volume
- 30
- Issue
- 6
- ISSN
- 0885-8950
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
10.1109/TPWRS.2014.2368078
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper won the 2018 Prize Paper award across the 5 journals of IEEE Power and Energy Society, https://cmte.ieee.org/tpwrs/pes-prize-papers/. No methods previously existed that could, in real-time, identity the critical modes of a large electricity grid that threaten instability and power blackouts but the proposed use of Dynamic Mode Decomposition was shown to achieve this. It has been adapted by others for application to other infrastructures (https://doi.org/10.1111/mice.12314), blood flow dynamics (http://hdl.handle.net/1993/32873), speech processing & communications (https://doi.org/10.1137/19M1273256) and geoscience (https://doi.org/10.1109/ACCESS.2020.2986499).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -