Recursive Frequency Domain Decomposition for Multidimensional Ambient Modal Estimation

TitleRecursive Frequency Domain Decomposition for Multidimensional Ambient Modal Estimation
Publication TypeJournal Article
Year of Publication2017
AuthorsHamed Khalilinia, Vaithianathan Venkatasubramanian
JournalIEEE Transactions on Power Systems
Pagination822 - 823
Date Published01/2017

This paper proposes a multidimensional recursive ambient modal analysis algorithm called recursive frequency domain decomposition (recursive FDD or RFDD). The method enables simultaneous processing of a large number of synchrophasor measurements for real-time ambient modal estimation. The method combines a previously proposed multidimensional block processing algorithm FDD with a single input recursive least square (RLS) algorithm into developing a new frequency domain multidimensional recursive algorithm. First, an auto-regressive model is fitted onto the sampled data of each signal using the time-domain RLS approach. Subsequent modal analysis is carried out in frequency domain in the spirit of FDD. The conventional FDD method uses non-parametric methods for power spectrum density (PSD) estimation. The proposed method in this paper by estimating PSD with a parametric method provides smoother PSD estimation which results in less standard deviation in RFDD estimates compared to FDD. The algorithm is tested on archived synchrophasor data from a real power system.

Short TitleIEEE Trans. Power Syst.