Open AccessParticle filter‐based dual estimation for synchronous generators
Author(s) -
Cui Yinan,
Kavasseri Rajesh
Publication year - 2017
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.1294
Subject(s) - exciter , control theory (sociology) , particle filter , voltage , estimator , computer science , tracking (education) , excitation , generator (circuit theory) , noise (video) , filter (signal processing) , kalman filter , engineering , mathematics , power (physics) , physics , artificial intelligence , psychology , pedagogy , statistics , control (management) , quantum mechanics , electrical engineering , image (mathematics) , computer vision
This study proposes a particle filter (PF)‐based dual estimation method for tracking the dynamic states of a synchronous generator. The authors consider the situation where the field voltage measurements are not readily available. The PF is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. To exploit the tracking results from the estimator, the authors consider the application of use the estimated field voltage to identify internal failures in the excitation subsystem. The proposed method is tested on a 10‐machine, 39‐bus system to assess selectivity between estimation for regular external disturbances and both physical failure, and modelling abnormality within excitation system. The presented studies show that the proposed method (i) provides reasonable tracking results for the dynamic states and the field voltage simultaneously, (ii) rapidly tracks minor excitation loss due to exciter internal failure while maintaining selectivity and (iii) is robust to measurement noise.