Publication Type : Conference Paper
Publisher : IEEE
Source : In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1–5). IEEE.
Url : https://ieeexplore.ieee.org/document/9225579
Keywords : data-driven methods, DFT, discrete Fourier transform, Discrete Fourier transforms, DMD, dynamic mode, eigenvalues and eigenfunctions, Estimation, fast and accurate methods, Frequency estimation, Harmonic analysis, Heuristic algorithms, High resolution, Parameter estimation, power grid, Prony algorithm, Time-frequency analysis
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication
Year : 2020
Abstract : Due to harmonics, sub-harmonics, and inter-harmonics in modern electrical grid, resolution of the estimation of parameters like frequency and amplitude plays a vital role in determining the stability of the system. Fast and accurate estimation of parameters with a minimal number of data points is essential for quick real-time action in case of contingency. Dynamic Mode Decomposition (DMD) is one of the recently proposed data-driven methods used to estimate the frequency/amplitude with high-resolution, even though it is a spatiotemporal data analytics tool originated in fluid dynamics. This paper investigates the significance of DMD for a fast and accurate estimation of electric parameters with a minimal number of data points. Further, DMD is compared with DFT and Prony algorithm for electric parameter estimation based on the number of samples required for accurate estimation. This aspect is not considered so far.
Cite this Research Publication : Kumar, K. S., Krishna, U. V., Mohan, Neethu, Sowmya, V., Soman, K. et al. (2020). Investigating the significance of dynamic mode decomposition for fast and accurate parameter estimation in power grids. In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1–5). IEEE.