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- W2507979939 abstract "Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems." @default.
- W2507979939 created "2016-09-16" @default.
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- W2507979939 date "2016-08-18" @default.
- W2507979939 modified "2023-09-26" @default.
- W2507979939 title "Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System" @default.
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- W2507979939 doi "https://doi.org/10.3390/s16081316" @default.
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