2015
DOI: 10.1016/j.ijepes.2014.09.024
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Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems

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Cited by 82 publications
(24 citation statements)
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“…In this filter, particles are broken into smaller samples and a new weight is attributed to each particle . Moreover, to solve particle impoverishment, several classic approaches are proposed in the literature, such as: adaptive particle filter (APF) [22][23][24][25], FBPF [15], auxiliary particle filters [26], unsecented Kalman filter based particle filters [27] etc. On the other hand, several intelligent systems based methods based on artificial neural networks and fuzzy systems are used in system [28][29] the literature to overcome particle impoverishment with low computational burden [30][31].As the main contribution, in this paper, particles are classified into three groups according to their weights; then, decisions about particles are made based on the group they are categorized to.…”
Section: -Introductionmentioning
confidence: 99%
“…In this filter, particles are broken into smaller samples and a new weight is attributed to each particle . Moreover, to solve particle impoverishment, several classic approaches are proposed in the literature, such as: adaptive particle filter (APF) [22][23][24][25], FBPF [15], auxiliary particle filters [26], unsecented Kalman filter based particle filters [27] etc. On the other hand, several intelligent systems based methods based on artificial neural networks and fuzzy systems are used in system [28][29] the literature to overcome particle impoverishment with low computational burden [30][31].As the main contribution, in this paper, particles are classified into three groups according to their weights; then, decisions about particles are made based on the group they are categorized to.…”
Section: -Introductionmentioning
confidence: 99%
“…Finally, a simulation has been given to illustrate the effectiveness of our theoretical results. Further research topics include the extension of this work to more general systems such as Markovian jumping systems [20], [30], [40], discrete-time systems and sensor networks [9], [22], [23].…”
Section: Discussionmentioning
confidence: 99%
“…To cope with the challenge of this computational burden and to relieve the communication infrastructure, a decentralized UKF-based MASE is proposed in [92] for the power system SE along with a consensus-algorithm. The authors propose a multi-area dynamic state estimator which splits the network into non-overlapping areas and carries out estimation for each area locally.…”
Section: Multi-area Dssementioning
confidence: 99%