期刊
IEEE TRANSACTIONS ON POWER SYSTEMS
卷 35, 期 2, 页码 1166-1177出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2019.2939559
关键词
Missing data recovery; phasormeasurement unit; Hankel matrix; low dimensionality; kernel technique
资金
- National Science Foundation (NSF) [1508875, 1736326, 1932196, EPRI 1007316]
- ERC Program of NSF and DoE [EEC-1041877]
- CURENT Industry Partnership Program
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1932196] Funding Source: National Science Foundation
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1736326] Funding Source: National Science Foundation
This paper develops amodel-free approach to recover the missing points in streaming synchrophasor measurements obtained in nonlinear dynamical systems. It can accurately recover simultaneous and consecutive data losses across all channels for some time consecutively without modeling the nonlinear dynamics at all. The idea is to lift the nonlinear system to an infinite-dimensional linear dynamical system and exploit the low-rank Hankel in the lifted dimension to characterize the system dynamics. The kernel technique is employed to handle the implicit lifting function. Compared with existing model-free synchrophasor data recovery methods, our approach drops the assumption of linear systems and applies to general nonlinear systems. The algorithm has low computational complexity and can be implemented in real time. The method is validated through numerical experiments on recorded synchrophasor datasets.
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